Good afternoon, everyone, and welcome to the FY 2024 New Relic Analyst Day here in New York. Super excited to see so many people here in the room. Looks very packed here. I just got a text message. We have more than 400 people online as well, following the webcast, so very much looking forward to an exciting day. My name is Ingo Friedrichs. I run Investor Relations and Corporate Finance here at New Relic. Before we go into the details, I've been asked to show the safe harbor statement. No surprise to many of you, there are some limitations that you can read. Also, for those online and here in the room, we will make the webcast available after the presentation has concluded, as well as the PowerPoint deck will be made available as well. We have a great afternoon lined up for you. We'll start with Bill Staples, our Chief Executive Officer, to talk about our vision and mission, in particular, the updates that we teed up a couple of days ago on the consumption business. We'll hand it over to Manav Khurana, our Chief Product Officer, as well as Peter Pezaris, our Chief Design and Strategy Officer, to give us an update on the product platform strategy that we have. We'll also have a demo included in there to see what it's really like. We'll take a 10-minute break after that, and then start again on the customer side. First, we'll have Ishan Mukherjee, our SVP of Growth, to discuss the PLG motion, and then Mark Dodds to wrap up the overall GTM section. Mark Dodds is, as you know, our Chief Revenue Officer. Then I'm really excited to also have some of our strategic customers here in the room. You can hear directly in their voice on how New Relic is adding value to their business. Specifically, we have representatives from Confluent, Capital One, and BlackLine here. Kristy Friedrichs, our COO, will host the customer panel for that. We'll wrap up with David Barter, Chief Financial Officer, to discuss our profitable growth outlook. After that, we'll have a short executive Q&A session, and then we'll break. The webcast will be then concluded, and we'll go here in the room into a happy hour session just next door. With that, let me hand it over to Bill Staples, our Chief Executive Officer. Hello, everyone. It is so awesome to be here with you today. It's been years in the making, actually. Welcome to the New York Stock Exchange, and welcome to the hundreds of people tuning in online. No doubt, it's a historic week for New Relic. We had our earnings a couple of days ago. Today we get a chance to unpack what we unveiled two days ago around our consumption business. We did a FutureStack Analyst Day last year. I recognize many of you from then as well. It's good to see you again. At the time, I'd only been CEO for a couple of quarters, and we announced a search for a new CFO. If you think about it, today's actually the first Analyst Day that we've had where we can talk about long-term strategy and the long-term business model for more than three years. Our goal today is to take a step back from the quarter-to-quarter execution and really help you understand our strategy and the long-term potential of this business. The big unveil at earnings on Tuesday was the long-awaited disaggregation of our business, and we heard a lot of excitement and tons of questions about the business, the key metrics that we've introduced in the investor supplemental, and the strategy behind them. The catalyst for all that excitement is pretty obvious. For the first time, we showed that we're not only nearing a billion dollars in revenue, 80% of that revenue is now coming from our consumption business, more than $700 million, and it's growing at over 30% year-over-year. We also have 12,000 of our 16,000 customers in the consumption model. Last year alone, we added 3,800 new paid platform customers, nearly a third of our total consumption base. Our paid customer base is just a portion of more than 57,000 actively engaged organizations using New Relic every day, making New Relic the most ubiquitously adopted commercial observability platform on the planet. All of those new metrics have been hidden behind our total company metrics from our subscription days. We're so excited to share them with you today and really unpack the strategy that's led to this success and our path forward. I want to start with a really basic question, especially for those who are new to New Relic, but maybe even those who've been around for a while. What is New Relic? Really simply stated, New Relic is data for engineers. Our mission is to be a source of truth for every engineer, to make decisions every day using data at every stage of the software lifecycle. We've been striving to turn observability from a collective set of reactionary, monitoring-focused tools that have been built up over the past decade. to, that really serve a limited set of production-focused engineers into a standardized, data-driven practice for every engineer that every company can benefit from. In a word, we're striving to make observability ubiquitous. New Relic participates as part of a really exciting opportunity with multiple secular tailwinds that drive demand for our product. First, we've all witnessed the massive impact of public cloud over the last 15 years. Observability is mission critical for cloud adoption. For example, when I recently spoke with a GSI that we do business with, they said, "Cloud initiatives that go wrong are the ones that lack observability from the start." For more than a decade, we've been talking about digital transformation and how, in part, every company is striving to reach more customers and grow more revenue using digital channels. In order for those investments to pay off, one must measure the impact of those investments, not only in terms of software performance, but business performance. New Relic comes into play there as well. Finally, the explosion of technology, and therefore technical complexity, continues to increase the need for engineers to have a data-driven approach to manage that complexity. New Relic benefits from all three of those secular tailwinds simultaneously. I want to dive into each one of them for just a moment and connect them with observability itself and our path for growth. Let's start with public cloud. According to Morgan Stanley, we should expect public cloud to grow from half a trillion dollars last year to $2.5 trillion in the coming decade. As that infrastructure expands, and the services on top of it, and the applications and the devices connecting to it, telemetry data is generated automatically. That data must be captured, and analyzed, and available to the engineers who are managing those digital systems in order to make sure they're running efficiently and serving customers well. As more users engage on those systems with their own devices, phones, tablets, wearables, so does the telemetry data coming off of them. Public cloud expansion drives the volume of telemetry data. I mentioned earlier, digital transformation continues to be a secular trend that drives the need for observability. This is why digital transformation remains one of the top three CIO priorities, with an estimated $2.3 trillion in spend, growing at 30% year-over-year, because every company sees the need to reach more customers and serve those customers through digital channels. Well, when a business starts doing these things, especially if they're new to digital, they're not cloud native business from the start, they must also stand up observability in order to answer really basic questions like: How is my digital business performing? Are the services up and running? Do customers love their experience? And where should I focus, optimize, and innovate next? Those questions can only be answered with a solution like New Relic. Finally, the staggering pace of technology advances continues to increase. I'm sure your news feeds, like mine at the moment, are filled with stories about artificial intelligence and its step function change in the world of technology. It's going to impact every one of our lives in the coming decade. Engineers at every company I know are now striving to wrap their heads around it and incorporate it into the applications and digital experiences that they currently own, and that's adding more complexity to their already complex stack and creating one more thing that needs to be measured and optimized. Increasingly, every piece of infrastructure, every application and service emits telemetry data through open standards, like OpenTelemetry, in the form of events, traces, logs, metrics that must be captured and analyzed in real time, and then stored for future query by millions of engineers who build these systems. Historically, this data has been captured and stored in proprietary formats and using a variety of open source or commercial tools in discrete data silos. The winning observability platform of the future will need to ingest that telemetry data at massive scale, with hyper efficiency, to serve the millions of engineers that need access to it. These secular tailwinds, public cloud, digital migration, technical complexity, drive what we believe is a massive, under-penetrated opportunity that we're just in the early days of realizing. The growth, as I just described it, comes in really two vectors. The first is the explosion of data. Data being emitted from all of those growing public cloud and consumer digital systems needs to be stored with massive scale and efficiency. This is one growth vector. The second is the adoption of observability as a standard engineering practice across millions of engineers. The engineers who build and manage these systems need to make more data-driven approaches in order to optimize, drive efficiency, and create better customer experiences. Here's a view that gives you a sense for how broad observability really needs to go. If you add up the top five leading observability companies today, you'll see what's represented in the first orange triangle. You'll see we're serving maybe 1,000 enterprises with over $1 million in spend, around 80,000 paying customers, but only, we estimate, 800 to 1.2 million active users. If you compare that to more ubiquitous developer tools like Atlassian or GitHub, you'll find that each of them already have hundreds of thousands of paying customers and tens of millions of active users. The discrepancy in the number of paying customers and users speaks to the still emerging nature of using telemetry data as part of an engineering practice. Every one of those developers that writes code and checks it in to source control, or manages that work using ticketing systems, needs data to make decisions on how effective that code is working and where they can prioritize their work next. This is why we began the bold and ambitious transformation to set up for that kind of opportunity. In the coming decade, we strive to serve tens of millions of engineers and hundreds of thousands of paying customers. In a word, our strategy is rooted in ubiquity. Today, I'm excited to share with you the progress on that transformation and unpack the performance of our new consumption business, along with the road ahead. It's important to remember, we are not starting from scratch. In fact, many of the world's leading brands across every industry vertical already use New Relic, and we're mission critical to how they do business today. We are so proud to partner with customers like the ones you see on the screen. They motivate us and inspire us to take the technology that we've built for them and bring it to every major enterprise and every entrepreneur around the world. Let's talk about the strategy to get there. First, this slide is one of my favorite slides because it talks about the real, measurable, demonstrated value by some of the biggest companies in the world that New Relic provides. I won't talk through them, but as I engage with customers, we really talk about two main ways that we add value to their business. We help them make money, we help them save money, these are documented, tangible, real value that we've brought and as we've partnered with these customers. Okay, let's dive into the strategy. The strategy really began in February of 2020, as I joined New Relic. Lew Cirne, our founder, had built this fantastic category-leading application monitoring business, or APM, he had aspirations for much, much more. We shared a passion, after decades of building software separately, apart, of using the untapped power of data to help engineers build better software. He hired me as the chief product officer at the time to help transform the company into a full stack observability platform that could be ubiquitous. We identified three massive transformations that were needed across product, go-to-market, and our business model in order to fully realize New Relic's potential and drive ubiquity. We launched this bold transformation to the public in July of 2020. In some ways, it seems like yesterday. In other ways, it seems like a lifetime ago. Executing even one of these transformations is rare for a public company to undertake. To pursue multiple simultaneously has been quite the adventure. We've made our share of mistakes along the way. We've learned and improved every quarter, and today is the opportunity to really step back and understand each of these aspects of the strategy and show the demonstrated successes that we're already having. Let's start with product. When I joined, we had 12 different products, much like our competitors do today. Inside the company, we had dozens of separate product teams. Each team had an assorted array of back-end data stores and front-end tools and experiences. The company had begun building a unifying approach called New Relic One, but it was very early days, and the strategy to bring them all together seemed quite daunting. We set our vision on delivering the world's first all-in-one platform that can truly democratize data insights for every engineer. When I spoke with customers that first few months, I realized the number one tool they were struggling with was tool proliferation. Number one problem is tool proliferation. In fact, 75% of our customers, even last year when we last ran this study, report having more than 5 tools in-house, each with their own data and each with their own tool experience, and that creates a loss of productivity and excessive cost as their engineers struggle to swivel between these different systems. We realized that in order to eliminate this problem, even for our own customers, we had to unify our platform, both the back end and the front end, in order to help them standardize on New Relic. By helping them standardize on New Relic's platform, we can not only save them money, but actually help their engineers be more productive. The transformation we began was this platform unification. We bet our business on having one place for all telemetric data, and also one experience for all insights, priced and packaged as a platform offering. Let's start with the data platform. Our transformation began by consolidating these various back-end systems that collect and store the telemetry data for all data types and all data sources into one unified data platform, with one API and one query language. We also immediately began embracing the emerging open standard of OpenTelemetry, to bring that data in as a native data source for the platform. The scale and performance of this system we knew was gonna be enormous in the coming decade. We also made the decision simultaneously to begin the move out of our data centers and into the public cloud, so that we could accommodate the scale and reach of a ubiquitous platform. We dreamed of building a platform that could not only reach every engineer in the world and serve every telemetry need, but to do it more affordably than any other vendor. They could store two to four times more data with us at the same price they would pay with a competitor. The results really speak from themselves, for themselves. You can see on the right, that's not just a fancy marketing graphic, that's actually the scale of the growth in our telemetry data over the last several years. The stats in the middle show the level of scale and efficiency we drive with our data platform. It's truly one of the most impressive pieces of software that I've had the opportunity to work on. Our work didn't stop with the data platform, though. We also began to integrate and, in many cases, rewrite our front-end user experiences across infrastructure, APM, logging, and dozens of other capabilities. We bought them together into one integrated, cohesive stack that rivals every competitor in the market. These experiences now seamlessly connect together and are sold in a all-in-one experience. Manav and Peter, after I'm finished up here, are gonna talk about what makes New Relic different than competitors, and you'll actually have a chance to see the product in action and where we're taking it with the advances of generative AI next. Let's talk about the results that we're seeing as a result of this strategy. 3 years ago, a vast majority of our customers really used us primarily for APM. We did have infrastructure and logging and a few other products or capabilities at the time, but they were under-penetrated. That's because we were best-in-class for APM, and at the time, the market was really looking for best-in-class tools across these technology silos. Today, customers adopt New Relic for the all-in-one platform. With zero friction between products, now more than nearly 90% of our customers use us for more than three capabilities, and more than half use us for 10 or more capabilities. To give you a sense of how that compares, look at what our primary competitor reports in terms of product adoption across those same product lines. Let's now focus on the next transformation, the go-to-market one. When I joined in 2020, we faced multiple quarters of revenue growth deceleration. We had record customer churn. We were losing paid customers every quarter. We had the highest sales and marketing spend in our category. These were a combination of challenges that also felt daunting, but we made a variety of different changes in response to them, to address them. First, we recognized one of the universal truths that I've come after a couple of decades of building software for developers and engineers, which is they really don't like to be sold to. The best way to sell to engineers is to let them use the product, fall in love with it at their own pace, and then choose to purchase it, and often, you know, bring their procurement teams along. The early days of New Relic were fueled with the same kind of product-led growth approach. We brought it back to New Relic and launched the first and still only free tier of observability in the market. You'll have a chance to meet the leader of this growth team that's driving our product-led growth motion, Ishan, later today, and he's gonna share more about that strategy and how we execute it. We also aligned our business model and field compensation to focus on customer value in response to the customer sentiment and churn challenges that we had. This had massive implications for our employees and for investors as we undertook this change. I'm so grateful for all of you who've stuck with us through that challenge and difficult change. Finally, we doubled down on our commitment to execution excellence, and we've been driving a culture of focus on performance and results. You'll also get a chance to meet Mark Dodds later today, our Chief Revenue Officer, who runs our go-to-market organization, and he'll unpack our sales-led strategy for helping customers expand and standardize on New Relic. Let's look at how these changes have aligned and reignited New Relic's growth. First, a look at new customers. I mentioned previously, when I joined New Relic, that we were losing customers every quarter. As we launched our new platform with the free tier, we began simultaneously migrating existing customers and winning new customers. Last year, we grew the number of pay-go customers by 67% year-over-year, adding nearly 1,000 net new customers every quarter. The decision to introduce the free tier and this product-led growth funnel pays off in another way. Over the last 3 years, we've built up a well of tens of thousands of active, engaged customers who we continue to nurture every day. In total, we have nearly 60,000 active, engaged customers on our platform, more than any competitor in our category. One of the fallacies of this free tier and product-led growth motion is that it really only attracts small and medium-sized customers. This couldn't be further from the truth. We see large government, enterprise customers across major brands and multiple segments coming in through the free tier, and Ishan and Mark are going to talk about how we nurture them to value, to paid customers, to contracts, and large paying customers over time. The improvements that we've made have also accelerated not just new customer acquisition, but look at how our large customers are growing. The number of consumption customers over $100,000 has grown by 23% last year, and by 64% for those spending over $1 million with us. Perhaps even more impressive is that we've been able to grow this new customer base and accelerate large paying customers while simultaneously reducing our sales and marketing spend. Over the last 4 years, we've decreased that spend by 11 points as a% of revenue. Let's talk about the last bold transformation, the transformation of our business model, this pivot to consumption. We drove this transformation for multiple reasons. First, I think it's important to call out the elephant in the room. In this category, we have a history of gouging customers on price. Just take a look at the current social media sentiment around our category, and you'll find certain vendors currently being customers expressing their frustrations around overages and price. We've never quite got the alignment of price to value that really can create a long-term, healthy, sustainable business. New Relic, three years ago, was in the same spot. We realized that in order to change this equation, we needed to fundamentally rethink the pricing of observability. It was necessary not only to help large customers achieve the scale of visibility that they were looking for, but to reach ubiquity as well. We needed to make the efficiency of observability much, much greater. Finally, we believe that the consumption promise of pay for what you use is a customer-favored business model, and we wanted to be the first one to pioneer that and bring it to observability. Let's talk about this business model shift first in terms of the problems that we heard from customers. In the past, we priced with hosts for APM and infrastructure, much like our competitors still do today. This is akin to how Microsoft used to sell Windows 2 decades ago, where you would buy the number of Windows licenses that you needed in your data center, whether you use them or not. Even if the servers were sitting there idle, you paid for that Windows license. Well, this is not how cloud environments work. AWS, and now even Microsoft Azure, charge based on real usage. We also had 18 plus SKUs that customers had to plan for, budget for. I believe you can't call it a platform if what you're really selling are discrete products. That's more like a product bundle. Finally, we recognized that pricing was just the beginning of the problem. When we incentivized our company and our sales teams to focus on commitments against those prices, rather than focusing on value and usage, we weren't truly aligned with our customers. We changed all 3 of those things. We moved from hosts and gigabytes and a dozen other meters to just two simple meters, data and users, with one price for all data types and sources and one price for users to access all of our capabilities. We also aligned our company and our sales organization to recognize revenue and reward teams based on customer usage, based on them actually using the software and seeing value from it. Sometimes investors ask about this pricing model and wonder if we haven't left something, giving up something or whether it's too simple for monetization. The best way to describe this pricing model is that it's horizontal in nature rather than vertical and aligned with the discrete products. For users, our price starts at $99 per user. That's for access to all 30 capabilities. Some users use a lot, others use less frequency, but it's simple and predictable for enterprises to manage. We've been piloting actually a more efficient model that also captures access by non-users in the form of scripts and other automation, with a query-based pricing meter that we'll be introducing more broadly later this year. For data, the standard data tier also is all-in-one pricing for all data types and data sources at a low $0.30 per gigabyte. This represents, if you were to do the conversion from hosts to gigabytes, represents a two to four times less expensive price and makes it easier for customers to send that much more data to our platform at the same cost. We also offer a set of premium add-ons that customers can add to that standard data price, for things like extended retention, streaming export, you know, high security scenarios, cloud provider choice. We even licensed our vulnerability management offering that we introduced this last January as an add-on price. This ensures that, as we introduce new capabilities that have additional cost, customers can opt into those at their own pace and their cost following. We cover the costs of that incremental infrastructure and R&D costs. The other thing that we do is to incentivize customers to higher levels of value. We bundle those set of add-ons into a premium SKU. We call that Data Plus. That's available at $0.50 per gigabyte and includes many of those add-ons that I talked about earlier, at a bundled, discounted rate. The adoption of both the add-ons and this bundled discount continues to increase and allows us to add more value to our customers and more revenue to the business over time. The efforts around this business model change were bold, but have already begun to pay off, especially with our customers. Gartner recently recognized that our business model is both differentiated and is disruptive, and is resonating with customers versus alternative models. I want to wrap up now with a look at the two businesses and bring it back to this disaggregation between subscription and consumption that we introduced on the earnings call. Many investors have asked kind of how we define the two, what the differences are. Let me spend a moment on that in our total company results. We have this subscription business, which we started 15 years ago, where customers' access to our platform is limited to the SKUs that they contract with us on. It's priced still with the legacy host meters and other meters, and the compensation model is not aligned. We recognize revenue ratably. We also have our new consumption business, which I've been sharing the strategy around, right? Customers in this model have access to all capabilities. They're priced on the simple user and data pricing that I just talked through, and we fully align our sales compensation on their value recognition. We also offer a shelfware guarantee in the consumption model, where you can make a commitment on our savings plan buying program. That commitment, much like it would be at Snowflake or Azure or other cloud consumption companies, is like a savings account. You draw down on that commitment over time at your own rate. Then we recognize revenue on usage rather than a ratable subscription contract. Let's look at how the business is performing on those two dimensions, subscription and consumption. First, let's look at it from a customer perspective. When we introduced the consumption business nearly three years ago, we had 15,000 paying customers in the subscription business. You can see from this chart how we progressively have been moving them from subscription in blue to the light green, migrated customers in the consumption business. Even more impressive, on top of that, you can see how we've been simultaneously winning new customers during that course of time. That's the dark green on top. Over the past 3 years, you can see we've not only been migrating customers, but nearly 65 of our consumption customer base, 65%, are net new to the platform. These new customers are more deeply engaged and stickier than our prior subscription base. From the capabilities slide, the usage slide that I showed earlier, they're using more capabilities. They're getting the full benefits of the platform. Their growth is much, much stronger. You can also see what we spoke about on Tuesday, in that our work is not yet done. We have about 4,000 customers still in the subscription business. They're made up of, I'd say, 2 cohorts. We have a limited number of large, multi-year contracts, oftentimes with customers in subscription, that we will be moving in the next 4 to 6 quarters. We have a long tail of very small customers. I think we said on the earnings call, about 1 million of them even qualify for our free tier, and we'll move them there, and we'll continue to nurture them with the goal of bringing them back to paid over time. Our goal is to exit this subscription business in the next 4 to 6 quarters, so that we are a 100% consumption company with all the growth characteristics and cost characteristics of that. Speaking of, let's talk about growth. Here's a look at the revenue of these two businesses. In the first year, we moved about 10% of our revenue to the consumption business. In FY 2022, as I became CEO, we began a more focused push and landed nearly 56% of our revenue in the new business. Not only the user and data pricing, but in consumption contracts. Even more exciting, you can see last year, we achieved, for the full year, 76% of revenue in the consumption model. We actually exited at more than 80%. You can see the growth of that as of Q4 year-over-year is 35% organic growth excluding migrations. It's been growing even faster than that in prior quarters. You can also see the effect of the subscription business in this view, and how it's offsetting that otherwise healthy growth in our consumption business and dragging on our total company revenue growth. That's why this focus on finalizing the migration from subscription to consumption is so important. While we've been executing this transformation, I think the ultimate measure of our success, throughout the process and in the coming year for investors, is our financials. We've been aspiring to build a healthy rule of 40-plus company. Over the past eight quarters, we've made steady progress towards that goal, improving our combined growth and profitability by more than 30 points. That's the kind of execution that gives me confidence that we're on a path to achieve this goal. In order to realize the goal of being a rule of 40 company, it's clear that we need to exit that subscription business and shift the remainder of customers and revenue into the consumption model. This will not only accelerate the total company revenues and profitability, but it'll help us be a simpler and more focused company. Therefore, our number one priority in FY 2024 is to do just that. We're also simultaneously investing in customer success and value realization, even more in these economic times. To help you understand our progress, we've introduced consumption revenue outlook for FY 2024 and several other meters that Dave will be talking through later today to give you more visibility into the health and growth of the consumption business. We're also simultaneously continuing to focus on the bottom line and drive more efficiency and profitability for investors. Our long-term plan for achieving Rule of 40+ is to grow top line between 20% and 25%, something that we feel is achievable given the pace of revenue growth in the consumption business today, exceeding already 30%. We also believe that we can achieve and sustain 20% operating margins. We're guiding to 15% in FY 2024. We're continuing to focus on driving more efficiency from there. Dave will unpack more of our financial plan in his closing section. Let me wrap up with this: I believe New Relic is an incredible opportunity for investors. We're competing in a category with long-term secular tailwinds. We're tackling this massive under-penetrated opportunity. We have a very efficient go-to-market motion that wins mind share and powers customer and top-line growth. We've been executing a massive transition to become the world's first and only all-in-one platform that's already outperforming the market. We've proven through this transition that we know how to execute. We see a clear path to rule a 40-plus company in the coming years. I hope you see that picture as clear as I do. To help you get even more grounded in the strategy, let's start with product, which powers our company and delivers the value to customers. Let me hand it over to Manav Khurana, our Chief Product Officer. Thanks, Bill. Hi, everybody. Good to see you all. See some familiar faces here. You know, Bill talked about how our strategy is rooted in ubiquity, rooted in making observability a ubiquitous practice for every engineer, every day, at every stage of the software life cycle. Well, let me start with the why. Why do customers care about a ubiquitous observability practice? You know, in my role, I have the privilege of speaking with hundreds of our customers, learning from them on what problems are they trying to solve with New Relic, and what benefits do they get? I t's clear that observability plays an essential role for every engineering team in a digital business. Observability is how engineers and engineering teams are able to monitor their digital business. That's how they find, discover, and respond in near real time to any disruptions that are happening because of performance degradations or security issues. Observability is how they get the data-driven insights to get to the root cause of why a degradation is happening, and quickly validate the fix to bring their digital business back up and running for their customers. For some of our most mature customers, observability is how our customers, and especially engineering teams, are improving their practice. They're using the data-driven insights to understand how they prevent future risk in the new software that they are shipping, and how they speed up their own innovation cycles. T he stakes could not get higher. The risk and costs of the exploding technical complexity, the ongoing migration to the cloud, the ongoing digital transformation are much higher today than they were, and they continue to rise. In fact, Gartner, during their recent research, had shared that an average downtime takes about 30 minutes to recover. Compare that to how 80% of online users abandoning an experience within a minute of not getting what they want. There's a huge disparity there. In fact, over $700 billion were lost in productivity to manage downtime in a year. On the flip side, you know, there are digital teams, engineering teams, who have taken the power of observability, the power of the data they get, to improve their digital experience, get more customers, and get more value. For example, McDonald's, who's a proud New Relic customer, they're using New Relic and the data-driven insights they get to improve their digital experience in their kiosks and in their mobile app to do $4 billion of sales every hour. I say all of this to suggest that observability and a ubiquitous practice of observability is just truly business-critical. We take a lot of inspiration from that, which is why we have taken a distinct platform-centric approach to observability to drive ubiquity of observability. A few years ago, much to what Bill was saying, we have purposely built a telemetry data platform where our customers can collect all their telemetry, their metrics, events, logs, and traces in one place. Not only that, we are able to do so by giving them incredibly high performance and incredible ease of use that they cannot get elsewhere. Second, we made a very deliberate choice of not just providing high-level metrics from the data they collect. We went super deep and provide code-level analytics to our customers. We decided not just to provide dashboards, like one gets with every tool, but to go and provide deep workflows so folks can get to the root cause and get superior insights from their data. Combine these two platform investments with our pricing model, and you'll see how there are inherent and structural platform network effects with New Relic. Our new customers start with our perpetual and generous free tier, where they can collect data about their software for free. As soon as data comes into New Relic, it starts to act as a gravity well, because that's where every engineer wants to go and log in to get insights from that data. Well, unlike our competition, we don't ask for different SKUs, different licenses for those engineers to get access. Every engineer who gets access to all capabilities on the platform, getting them to all the insights they need. Invariably, when engineers get access to New Relic and get those insights, a natural thing to do is to say, "Well, let me also instrument and collect telemetry about the service that I own, or get more data to make these insights even better." Unlike our competition, we again, don't have any contract friction for customers to do so. With a very low cost per gigabyte, they're able to collect even more telemetry into New Relic, which then propagates the network effects. More data drives more users, more users drives more data, right? That's the fundamental of our platform approach combined with our pricing model. This is the reason why organizations like GigaOm, who do independent research on all the observability tools out there, call New Relic an innovation leader in our space. In fact, check this chart out. Not only is New Relic closest to the center of the bull's-eye, which is the best place to be, but it's also the only vendor that has moved as much as it did compared to all other options on the market. You know, this innovation leadership results in many benefits for our customers, which makes them love New Relic. Let me walk you through a few of them. The first one is our superiority in APM, Application Performance Monitoring. Ask any engineer who has used New Relic and a competitive APM product, and they will tell you why they love New Relic. You know, just recently, I was on a call with a prospective customer who was looking to move off of Datadog to New Relic. They proceeded to show me how they're using Datadog today, and were wondering if New Relic could do the same or could do better. They had shown me a neatly organized dashboard of all of their metrics, all of their data from their application, their infrastructure, and so on. As they were showing it to me, I asked them, "Hey, you see that little spike in one of your metrics? Why did that spike happen? How do you get to the root cause of that spike?" You know, that poor person, they clicked on one chart, clicked on another chart, clicked on another chart, and the problem kept getting worse for them because they went from one metric to thousands of long lines and traces and ended up getting lost, and in the end said: "Hey, you know, I need to call the person who owns the service. They'll know what's going on." Right? There is the exact difference with New Relic APM. We don't just offer customers dashboards, which are noisy at best, help you understand or help customers understand what is broken. We have built deep insights and workflows that help engineers drill down and narrow into the specific issue that customers have, and hand, therefore, fix it. This advantage in New Relic APM is why our customers instrument more and more of their applications, bringing data revenue, why they bring more and more users to New Relic, growing our user revenue, and in fact, is one of the main reasons why many new customers start with New Relic in the first place, growing our new logo revenue. Another key problem in the world of application performance monitoring is how the world of applications and the application architecture has changed so much. You may have heard how applications these days are built with a distributed microservices architecture. What that means is that there is, instead of one piece of code, there's many distinct, smaller components of code that work together to create a customer experience. Well, in that environment, it's very hard to know what is the root cause, which part of the code broke or which service broke. You need to understand upstream, downstream dependencies, and that's very hard to do with other APM tools. With New Relic, out of the box, our customers are able to visualize upstream and downstream dependencies because we do the hard work for them. We synthesize, we fingerprint how their environment has worked. We put it on an easy-to-follow chart so they can figure out, well, this end customer experience is not working as well as it should because of this downstream service, and they're able to go much deeper into it. That's why customers love it. As they see their own topology, it's very natural for our customers to say, "Well, you know, that's a service that has not been instrumented. Let me instrument that, get more value from New Relic out of that," which in turn grows our data revenue and attracts more engineers to New Relic. That grows our user revenue. You may have heard a common refrain about observability and APM tools, which is observability and APM is used for break-fix. It's used for incident response. Well, that's true. That's one of the main use cases, but it's not the only thing that engineers need to do their job. Engineering teams need data-driven insights to make sure that the application and the services they provide are serving their business properly for the key transactions. They need to understand the end-user experience. They need to understand the security posture. All those distinct insights are something that we now provide out of the box as part of our APM experience, not as separate experiences. That is an area that we have built on our strength to give customers even more value. As they go from just the break-fix use case to serving full lifecycle, use cases, customers end up getting more value. We see our data revenue and user revenue grow as a result of it. Another major change that has happened, especially in the last six months, is how every company is thinking through their own AI strategy, is how they harness the power of AI to build a better digital experience for their customers and stay competitive. Well, that has resulted in engineering teams having to work with either their own machine learning models that they are building or integrate with somebody else's machine learning model, most notably generative AI models, to provide a better digital experience. As they do so, as they build that next generation of the application or the next capability of their software, they need to know if their AI experience is truly solving a customer problem, is it performing the right way, and is it costing the right amount? That's something that they can now get from New Relic because we have taken a leadership position, not only with the first machine learning model monitoring solution, but also with the world's first generative AI integration monitoring solution for our customers, which again, as customers get more value, they end up instrumenting more of their applications, which grows our data revenue, even more engineers start using New Relic, which grows our user revenue. Beyond APM, especially in the last couple of years, we have seen how customers have remarked and shared about our logs capability on how they get a superior log management experience in New Relic versus other options. Logging is an interesting area. It's been around for a couple of decades, maybe even longer, logs are very voluminous. There's a lot of log lines, and it's very easy for an engineer to get lost looking through log line after log line. There's thousands and thousands of them to find what they need. Because they're so voluminous, the most log management solutions end up feeling slow to search. They end up costing a lot for IT teams to manage. Well, we solve that problem by providing our customers a centralized log management solution built on our data platform, which is very high performance. With that same relationship service that I talked to you about earlier, they're able to, with one click, get to the right log line that they care about or they should care about, right away. They don't have to sift through those changes. With the superior affordability that we offer in a data platform, IT teams love New Relic because they get a much, much lower total cost of ownership when they use logs in New Relic. As customers migrate their logging from the other solutions to New Relic and get more value, they end up sending a lot more data to New Relic, which grows our data revenue. As we have seen more and more customers use New Relic log management, we are getting exposed to a number of new use cases that we had never thought about before. One example of that, which goes beyond operational logging, is compliance. You know, there are a number of compliance and security teams that want to make sure that the log lines are retained for longer, for auditability and for compliance reasons. To do so, they want long-term storage at a much, much lower cost. We are enabling that capability for our customers this year by introducing what we're calling Live Archives. With Live Archives, our customers get not only long-term storage at a much more affordable cost, they get the ability to query those logs on an on-demand basis, making it easier for engineers than our competition, and a lot lower cost for our customers than our competition. They bring on their compliance use cases, they end up storing more logs, which grows our data revenue as well. Over the last couple of years, I've also heard a new theme, especially as we introduced our all-in-one platform pricing and our all-in-one platform packaging for our customers, which is how customers love how they can get access to all their observability tools in one place, you know. Bill had shared a statistic earlier, how 75% of organizations have 5 or more observability tools. Many customers I speak to have dozens of observability tools. That proliferation of observability tools not only costs a lot to maintain and to buy and to resubscribe, it's a painful thing for engineers to go from one screen to the other and try to reconcile which is giving me the right data. It's painful for customers. They do want to consolidate their experience into one to solve their cost problem and solve their productivity problem. Now, with 30+ tools in one platform, they're able to do so. As they do, we end up seeing customers instrumenting more of their environment, collecting more data, which drives our data revenue, and more and more of their engineering team logging into New Relic and growing our user and query revenue as well. Talking about capabilities, just last week, we introduced our new infrastructure monitoring capability. You know, every application our customers have that they're monitoring with New Relic runs on some kind of infrastructure, on some kind of server where the software is running. In the past, not every customer used New Relic for infrastructure monitoring, the underlying servers, the underlying infrastructure. They used New Relic for APM, but not the infrastructure. Well, now, with this new infrastructure monitoring capability, we're giving our customers best-in-class infrastructure monitoring capability that is a lot more affordable than any 1 of our competitors that offer similar capabilities. We have built it as an integrated capability, so customers can go from monitoring their entire estate, like an infrastructure owner does, narrowing it down to the specific application to debug issues, troubleshoot issues like 1 needs to do during an incident response time. It's an incredible experience that will allow our customers to save money on their in-infrastructure tooling, and as they do, as they instrument their infrastructure environment, get value from New Relic. That drives data into New Relic, that drives our data growth, and more and more engineers start using New Relic, which drives our user revenue. Another key capability that we added earlier this year is vulnerability management. This is the first of many security monitoring capabilities in New Relic. You know, a modern-day engineer is not just responsible for building their applications. They're also responsible to make sure that those applications are secure. That security responsibility is moving to developers. As that happens, developers want security insights about how their applications are working, not only the security team. With the telemetry that customers already had in New Relic about their applications, we were able to figure out how to unpack security insights for them and make it available for them out of the box by default, without having to do any additional work. That gave developers and security teams the confidence and the understanding of how they are doing from a security point of view, not just a performance point of view. As they did that, not only did we see more and more applications being instrumented, but as Bill mentioned, vulnerability management is an add-on, on the Data Plus. We also see our data revenue increase as a result of it. Again, this is the first of many security capabilities. In the weeks, quarters, to come, you'll see us introduce many more security capabilities to help customers with their security monitoring needs. A common concern among many engineering teams, who, especially engineering leaders, is, "Hey, I want every engineer in my team practice observability as a ubiquitous thing. Most engineers in my team are developers. They write code. They don't manage my software." Observability is a foreign concept to them. It's not a tool that they log into every day. In fact, I would say less than 10% of most engineering teams end up using observability today, right? The rest of them don't have that in their focus. We, 18 months ago, acquired CodeStream, which you'll see in a few minutes, that brings the power of observability, the power of those data-driven insights, directly into the development environment for developers, making it accessible to them, and giving them the ability to not only fix issues faster, but also verify that the code that they are writing for a future release is gonna work well in production, and it's gonna perform well in production. It's a truly unique capability. Customers that are using it are absolutely wowed by it on what value it adds for them. As they do, they end up not only getting more value from the telemetry, they end up using our platform more, which drives not only more user revenue, but also query revenue. Everything I talked about so far, superiority in APM, our logs differentiation, our 30-plus tools in one, they all require telemetry underneath. They all require data about our customers' tech stack, their software stack underneath. Historically, that has been really hard to do for customers because telemetry and data costs a lot, especially in the traditional host-based pricing model. With our low per gigabyte pricing that Bill talked about, it's very easy for our customers to eliminate those blind spots and collect all their telemetry in one place. The reason we are able to do so is that we have a very cost-efficient architecture because we purpose-built our telemetry data platform that's very high performance, and we have instilled a level of engineering discipline to manage our costs. As we lowered our costs, we transferred those savings to our customers in the form of a low gigabyte price, which is what makes observability from a siloed, bespoke practice, allows customers to look at all their telemetry and make observability into a ubiquitous practice for our customers. Building on that differentiation, we are expanding into many, many more regions and clouds for our customers. T here are some companies, some organizations who just need their data to be local to where they operate. Without that, they cannot fully adopt observability in their environment, okay? Earlier this year, we introduced our ability to store, to keep data local in Azure environments. We're building on that by supporting, giving customers the ability to go also use GCP as a cloud provider of choice and introduce several more regions. As we do, we've also innovated and introduced new capabilities behind the scenes that allow us to manage the costs of being in multiple providers and give customers one common query language, regardless of where their data is stored, so it does feel like a unified platform for them. We call that capability Flex Cloud, and we are building on it this year. That's how customers get the choice and the affordability, both at the same time, a unique differentiator for us that we are building on even further this year. Lastly, I'll mention open standards. There are many engineering teams who are frustrated by how hard it is to manage and instrument their environment. You know, it's hard for many of you to realize this, but getting the right data about a software environment requires very specific expertise and requires a lot of developer time. That's why we started building a large library of over 600 integrations, now it's one of the largest in the industry, so customers can get the data they want with a single click. Also, and much more importantly, we have taken a leadership position with OpenTelemetry, which is a vendor-agnostic way of collecting the right data for our customers, and we are making it very easy for them to use OpenTelemetry to bring data into New Relic or anywhere else that they want. Right? This leadership in OpenTelemetry is unique in our market compared to our primary competitors, but it's the right choice because this is where the world is moving to. In fact, we are so convicted that we're building on that open standards leadership in this year. First, we're introducing what we call our SuperAgent. You know, having 600 integrations, having OpenTelemetry support is great, but it also means customers have to manage 600 different types of agents. Well, we're solving that problem for our customers once and for all, with one integrated agent for all of their telemetry. They have to manage one agent. Unlike other one-agent technologies that are out there that you might be familiar with, we're doing so with open standards, with OpenTelemetry, so customers automatically get upgraded to open standards and get the vendor-agnostic approach they want and get future-proofed right away. By doing so, we unlock even more telemetry and obviously, that drives our data revenue. Next, we'll be introducing telemetry pipelines. You know, especially for larger enterprises, engineers have to abide by a number of compliance concerns. They need to make sure that the data they're collecting, the telemetry they're collecting, is secure. They need to abide by privacy rules. They need to make sure that it's not costing them too much. All of that control requires a lot of manual work today. We're gonna help our customers automate all of that with telemetry pipelines, where they can use New Relic to route, transform, enrich, protect their telemetry using technology that we provide them, provides them greater value, unlocks even more telemetry. It comes with an add-on charge, that then, therefore, also drives our add-on revenue. Third, we'll be introducing what we call Fleet Manager. You know, it's not just about installing agents to collect telemetry. We're introducing a centralized place for our customers to manage the configuration of tens of thousands or hundreds of thousands of endpoints in one place, making it extremely automated and simple for them to control what data they're collecting from where they're collecting, how they're collecting, instead of managing it endpoint by endpoint. That capability also unlocks even more telemetry for our customers that they can collect and take advantage of and get more value from, and drives our data revenue as a result. It wouldn't be a product presentation without a one more thing. It won't be a product presentation without a demo. T o do both of those, please allow me to introduce Peter Pezaris, my good friend and colleague, who's gonna talk to you about both and tell you about how we're taking advantage of generative AI, which makes observability accessible to every engineer in the world. Peter? Thanks. Thanks, Manav. Great job. I'd like to start with a quick show of hands. How many people in the room have used New Relic in person? If you work at New Relic, don't raise your hand. Okay, a few. A little more than I expected, but not too many. In the next 10 minutes, I'm gonna show you three demos: how New Relic helps our customers solve problems today, how we're expanding observability into the entire engineering organization with CodeStream, and how we're making observability truly ubiquitous with generative AI. Over the last few decades, computer systems are becoming more and more complex. We used to use mainframes, which was one big computer running one big program at a time. We all shifted to client-server architectures, which had a few more moving parts. Well, in today's world, we have cloud-based microservice architectures, and now there can be literally millions of instances of a program running or different programs running, all working together just to serve one website or one mobile app. It can get pretty complicated, and keeping all that up and running can be pretty tough. If something does go wrong, engineers will get an alert, and they'll log into New Relic to troubleshoot. In fact, as I was walking up here, I got an alert on my iPhone letting me know that my website was getting a little slow, and although it hasn't crashed yet, I'd better log into New Relic to see what's going on before things go really far south. Here you can see that New Relic gives me a bird's-eye view of my entire production estate. I can see my APM services. I can look at the hosts that they're running on. I can look at the containers and the mobile apps, basically everything that I'm using New Relic to monitor. I can also see that a couple of these services are now red, which means there's a problem. We're gonna go one level deeper into our APM capability to see what's going on. Well, here I've got an overview of this particular application. I can see all the most important metrics. The web transaction time means how long it's taking to serve customer requests. I can also see the throughput, which is how many requests are coming through, and the error rate, which is how many errors are happening. You can see over here, which over on the right, it's the most recent data, I'm seeing some spikes in web transaction time. That means the application isn't running as smoothly as it should be. In situations like this, sometimes it's the application itself that's having a problem, but sometimes it's something else, whether it's an upstream service, a downstream service, as Manav was saying. Sometimes it's the underlying infrastructure or the computer that that application is running on. We're gonna go one level deeper into our infrastructure capability to look at the host that this particular application is running on. Here I can see all the most important metrics, how the CPU utilization is, and the memory and the disks, and although there's some variation here, I can't see anything that's really taking me to the. what the problem might be. We better go one step deeper. We're gonna look at something called distributed traces. Now, a distributed trace is a way to track one transaction. For a user, you click a button, that creates a cascade of activity within a computer system. New Relic can track that one transaction as it goes through your system. I can see two different types of traces for this application, and this one is taking, on average, over 2 seconds to complete. That's probably why my website is slow. Let's click in to dig a little deeper. I can see the individual transactions on this scatter plot, and sure enough, some of them are taking quite a long time. As you go higher in this graph, it's a longer period of time. More importantly, I can see that some of these transactions have errors. Let's click into one of these transactions so we can figure out what's happening. Here, I can see an overview of how this particular transaction is moving in between the different parts of my system. Below it, a waterfall of the individual steps along the way and how long they took. In fact, it looks like this particular step in the process encountered an error. We better look into that. I can click to open up this particular span. It's called a span. I can see that sure enough, there is an error. If I click here to expand the error, I've got my first clue. I know that there's some sort of timeout error. I don't know why yet. In order to find that, I probably need to find more detail into this particular error. That can generally be found in application logs. Now, as Manav mentioned, unlike our competitors, our logs product is integrated into the other capabilities. Let's go one step deeper into our logs product by clicking on these logs, which importantly, rather than causing me to sift through gigabytes and gigabytes, and gigabytes of logs and try to find a needle in a haystack, with New Relic, it takes me directly to the log lines that are relevant to what I'm looking at in the app, in our service. In this case, there's two log lines, one of which looks like it has an error, and when I click on that, I can see the details. Finally, we've found it. We can see here in this log message that there's an error with the SQL query, and it's causing a database timeout. Now that we've identified the problem, I can contact the application engineer and share with this permalink exactly the investigation that I just went through. Somebody on my team can push some new code to production to address the problem. It's a pretty great way to be able to debug with powerful tools. One of the things that you may have noticed as I was going through this, is I used the phrase, one step deeper, a couple of times. This is a unique capability of New Relic with our all-in-one platform that captures production telemetry from every layer of your production stack and all of your data types into one set of capabilities. Contrast this with our competitors that sell individual SKUs, you have to buy those different products. You could imagine, as I was trying to troubleshoot this, when I got to that step where I had to look at the logs, well, imagine if I didn't have a seat, a licensed seat for that logs product. Production's on fire, and rather than grabbing a fire hose, I'm talking to procurement. Even if I did have a seat, because of the way our competitors' products are built as individual products, Manav was mentioning this before, they've got disconnected dashboards. Every time a New Relic that I went one step deeper and got one step closer to the problem, in our competitors' products, every time you shift from capability to capability, you're starting from the beginning again and have to go through it all. This is the power of New Relic's all-in-one observability platform. There's something else you probably noticed as we were going through this, which is that it's not that easy. It requires quite a bit of skill and training in order to do these types of investigations. In fact, we estimate that there are only 1 million-2 million engineers in the world that are capable of doing this. Contrast that with the 50 million engineers that are writing the code that ends up in production. We aim to bring observability to all of those engineers, and we're doing that by bringing production telemetry to them, rather than forcing them to use all these new tools. We're doing that with CodeStream. CodeStream is a product that integrates into the existing tools that application developers are already using. Let's take a quick look. Here I've got Visual Studio Code up, and I've got some code in my editor. This is an application that every application developer uses every day, all day long to do their job, to write code. Into VS Code, we've added CodeStream, and you can see it over here. As soon as I click on it, we can show you all the best parts of New Relic in context. This does two incredible things. Number one, it takes the relevant information for me as an application developer that's working on one thing. Rather than looking at those millions of different programs that are running in production, I can focus on the one that I've got open in my editor. The second thing is it takes all the best parts of New Relic, whether it's the golden metrics, or all the best parts of APM. I can see my service levels, I can see the errors, I can see the vulnerabilities and related services. We even go one step beyond that. We've just announced something that we called code-level metrics, and this allows me to see the performance of individual blocks of code. This is a first in the world. None of our competitors have this, where for individual methods, I can see how this method is performing in production right now. This is fantastic because now every engineer on the team gets to see how their code is running in production and how that changes over time. Now let's bring it all together with one more thing. I'm sure by now all of you have seen the magic of generative AI in products like ChatGPT. We're gonna bring that magic to our customers and make observability truly ubiquitous with a product we call Grok. Simply put, Groq allows you to ask questions in any language, actually, although I speak English, about your production system. Groq will answer you. Remember before when I got an alert because my website was slow, and we used New Relic's sophisticated tools to troubleshoot? Let's try that again. Only this time, we're gonna use Groq. I can click to open the Groq panel. The first thing I'll say is, we're gonna test my typing ability here: I got an alert. What's on fire? You can see here that Groq tells me that on one of my hosts, the CPU usage is over 95%. That's bad. It also tells me that there have been no changes on that particular host. That's kind of curious, because things generally don't go wrong, not like that, if nothing's changed. I can say, "Well, what did change?" Grok will tell me that of the applications that are running on that computer, on that host, there was a deployment, and ever since that deployment, the error rate has been elevated. Well, now we're getting somewhere. I can ask Grok: What's the error? When Grok responds, it tells me what the error group is, and because it's integrated into CodeStream, I can actually click this button to open up this error in my IDE. Now, in addition to taking me to exactly where in the code this error occurs, I can ask Grok to analyze it. This is where it gets kinda crazy, because we're gonna take production telemetry, we're gonna take the code, we're gonna take the error group, and we're gonna feed it all into a large language model. What it comes back with is not only an explanation of what's gone wrong, but literally the code to fix it. I can just click this button and apply the fix, now it even tells me what message I should use with my teammates to explain what it's done. I can click to commit those changes. As an application developer, this is just mind-blowing, right? It's going to fundamentally change how software is written and debugged in the future. New Relic is best positioned to capitalize on this fundamental shift. Production telemetry fed into the IDE and guided by generative AI. It changes the very nature of software development. Not only that, Grok makes observability truly ubiquitous. Whether you're a service reliability engineer, whether you are an application developer, whether you are a QA person or a security person, or whether you work in customer service or you're on the product team or even an executive, you can now find out what's happening in production just by asking questions. This also provides New Relic a truly differentiated product that our competitors can't match, and it gives an edge to the field in competitive head-to-head deals. I couldn't be more excited about what these changes will bring for New Relic and the value it'll deliver for our customers. With that, I'm gonna hand it back over to Manav. Isn't that incredible? I've seen that demo. I've seen every little part of that demo, the technology underneath it, a million times, and I'm amazed each time. Peter talked about the differentiation that generative AI brings to New Relic. The one thing underneath that most people won't understand is how we were able to do that. You see, New Relic, you remember the platform advantage of being able to collect all telemetry from the entire software stack in one place with very high performance? Well, that generative AI model needs that data, and that's why we were able to introduce this. Remember that ability to get superior insights from the entire stack and having access to all the capabilities? Well, generative AI needs that, and that's how we were able to build this capability faster than anyone else. This inherent advantage, the power of generative AI, is why IDC, for example, recently recognized how incredible this technology is and how much of a competitive advantage it gives New Relic. Putting it all together, you know, Bill mentioned this earlier, New Relic started as a cloud APM tool. Over the years, it went from cloud APM to a cloud APM suite with many capabilities as part of it. Over the last two years, building on top of our platform advantage, we've been innovating faster than ever to bring more value to our customers in the form of an all-in-one observability platform, which is where we are today. Looking forward, we're already working on continuing that innovation speed, maybe even accelerating it, to bring even more value to our customers. We're working on a number of new capabilities, some of which you saw today on the slides and with the demos, so that our customers get a lot more value from the all-in-one platform. They can consolidate their tools and in turn, open up new revenue opportunities for New Relic. I could not be more excited about where we are today and where we are going. It's truly built on unique platform differentiation and incredible execution with partners like Peter and Siva back there, across product to make this happen. We're going to go into a 10-minute break. When we come back, we're going to have Ishan and Mark talk to us about go-to-market. Thanks, everybody. Hello, we are starting in one minute. Please go back to your seats. There will be more Q&A opportunity later. There'll be happy hour. You should just cross it out. No way! Can you please go back to your seats? We would like to continue. Excuse me. All right, Ishan, over to you. Hello. I feel like I'm a stand-up comic coming after Dave Chappelle. Welcome back. Hopefully, you all had a great 10-minute break. Mark and I are here to do a deep dive into our go-to-market strategy. Let's dive right in. Manav talked about his extremely exciting product strategy and roadmap to achieve ubiquity. In go-to-market, we are executing a product-led land and expand motion to realize ubiquity. I'll start by walking through a simple 3-step progression as to how we do that. First, is we land new customers through product-led growth. This involves us executing the category's first at scale, free tier-based funnel. Second, is we expand consumption through broad product-led efforts, where we tap into the platform network effects that Manav talked about and overlay a sales-led effort. Third, is where our sales-led efforts drive standardization across New Relic, where our largest enterprise teams consolidate all their tools in New Relic. Let's dive into the first funnel, which is PLG. We reprioritized PLG in fiscal 21. The strategy today is acquiring customers across enterprise, mid-market, and SMBs. This is across verticals and across all geos. At the very top of the funnel, the success for PLG has been driven by us regaining mindshare leadership across practitioners globally. As you all understand, earning mindshare is fundamental for engineers across the world to explore and evaluate tools when you're operating in a multi-tool market. The three charts here try to quantify what we mean by leadership in this leading indicator. The chart on the left talks about negative community sentiment. Over the last 2 quarters, we've been at historical lows, and our primary competitor has been at historical highs, primarily driven by the pricing frustrations that Bill talked about. The chart in the center talks about positive community sentiment. The last 2 quarters, we are building on our leadership, primarily driven by the improved product experience and shipping innovations like New Relic Grok. The community is hearing us, and they're really turning back. The last is press share of voice. We measure the press mentions in tier 1, tier 2, tier 3 media in our target geos, and we are pleased to announce that we've arrested the decline and now have a fair lead across our kind of competitor base. This is primarily driven by landing product innovation stories in the market that Manav talked about. Over the last two years, we've shipped 16+ major launches. This drives higher earned traffic to our top of the funnel. Let me walk you through the PLG engine. At the highest level, we have four key categories. Step 1 is driving free tier signups. This involves practitioners across all geos, verticals, and segments. As Bill mentioned, this is enterprise, mid-market, and SMB, where they sign up for our perpetual free tier to serve their observability needs. Unlike competitor kind of free tier solutions, our practitioners can use New Relic for as long as they desire. Kind of key strategic insight here is that we are building an ever-increasing pool of high-potential customers that we nurture into being paying customers. Just last year alone, we drove a 1.5x year-over-year growth, thanks to our mindshare leadership and driving efficiencies in demand gen. We've acquired a ton of signups. What's step two? Step two is driving in-product activation. This involves our customers finding more value in the platform, adding users, adding data as they attach into other capabilities in the platform to exceed our free tier limits. In New Relic, we've built a dedicated R&D function, which includes engineers, product managers, designers, and some of the best growth marketers, who maniacally execute with a data-driven approach to continuously improve our in-product onboarding and UX kind of improvements. The last year alone, this team was responsible for 80% year-over-year increase in the number of accounts that exceeded our free tier limits. That's step two. We got sign-ups. We have in-product activation. It moves to step three, which is customers entering their credit cards to become a monthly paying, pay-as-you-go customer. There's two kind of mechanics here. The primary is in-product conversion, as a customer sees a paywall and enters their credit card. The secondary motion is a human overlay with our inside sales team, where our inside sales reps help customers in that kind of credit card entry Phase if the customer reaches out for assistance. As we've reported, this stage has returned more than 800 pay-as-you-go customers per quarter. These three stages are mature, and we are confident in investing in it to scale further. The last kind of stage of this funnel is a new inside sales motion that we added last year. This is where our inside sales teams get our customers, our interested customers, on our modern buying programs, direct to contract. We're excited about the results we saw in the last fiscal. We're investing to scale this motion as well. These four stages, kind of fueled by the mindshare leadership, is what's behind this PLG growth that Bill and Dave talked about. The next obvious question is: How are we doing? Today, the PLG engine lands more than 90% of our net new lands. We're only getting started. This is the first innings. We're building the engine in a way where we achieve our long-range plan, where New Relic is the default observability platform for all engineering teams. To achieve this North Star, we're investing in three fronts. First, which is non-negotiable in our market, is how can we be the number one mindshare product? Second, is continuing to deliver on the seamless product experience. As Manav and Peter walked through, the product today is just phenomenal, and you can see it from the community sentiment. People love our product. We have to continue to kind of make it better because developers and operators appreciate that. The last is continue to scale an efficient inside sales function. Driving to ubiquity, as Bill and Manav and Peter mentioned, is fundamental as to how we're building PLG. Hopefully you have a good understanding of what's behind the charts and what's driving the PLG engine. The next step is how do we cohort customers, and how does PLG fuel kind of graduation through our customer cohort model? Let's talk about de-definitions first. Internally, we categorize customers on a metric called Total Addressable Spend, or TAS in short. This is an equivalent metric to total size of wallet. Self-serve motions support customers with a TAS of less than $150K. Sales-led motions support customers higher than $150K. What PLG does is it fuels a broad and deep customer base, which is constantly compounding, because these customers don't kind of decay out of New Relic when the trial ends. They're constantly kind of using the product. In Q4 alone, we had 41,000 active free customers. These are customers who are ingesting data, more than 100 MBs in a given quarter. The next, or maybe you could argue, the more important kind of dynamic is: How are we graduating customers from self-serve to sales-led? When we started the fiscal 2024, we graduated 1,300 customers from self-service to sales-led. Based on our estimates, these kind of sum up to a TAS of more than $1 billion. Hopefully this gives you an understanding of how we acquire customers at scale, at low cost, and help as they grow their consumption through this cohort model and hand that off to sales-led motions. T o learn more about our sales-led motion, let me hand it to Mark. Thanks, Ishan. Great to be with you. Funny story. I've never presented here before. Yesterday, we were talking about presenting here, and I realized that we were gonna wear ties. Some of us were gonna wear ties. I've not seen ties in a presentation for a while. I had a little bit of a problem today because I decided, Bill, being a fast follower, I decided Bill's got a tie, Dave Bohn has got a tie. I'll have a tie. What I didn't count on was the fact that I'd forgotten how to tie a tie. I had to go to YouTube and quickly figure out how I do it. I'm gonna spend the next 10 minutes just talking about the sales-led motion and the opportunity that we've got ahead of us, how we're trying to extract value from that opportunity, and ultimately, how we engage our customers. Manav talked about our exciting product strategy. It's an unbelievable strategy, and we're landing a ton of innovation. Ton of innovation. I'd like to cover the go-to-market strategy usage within customer environments, and secondly, how we're addressing the tool consolidation opportunity that we've got ahead, which is enormous. The first thing is, there is a few things that give us optimism. Being a CRO, as you can imagine, coming into a company, most companies have some form of outbound sales motion. It's expensive, it's usually inefficient, it's very inconsistent. Coming into New Relic, you realize that we're actually landing a high volume of enterprise customers through our PLG motion, and that gives us an opportunity to engage. We transitioned 1,300 customers into our motion, and that's getting started. Our goal there is to transition 200 customers per quarter into our sales-led motion. Ishan talked about the value of those customers. We think we've got a $3 billion opportunity with our existing customers, not new customers, not customers that we have to go out and acquire, bring into the company. Our PLG motion is landing a customer opportunity of about $3 billion of addressable spend. We worked with some management consulting companies to arrive at that number and arrive at the maths behind the number. The second thing is that we're seeing some macro trends that give us opportunity as well. Those macro trends, digital transformation, cloud migrations, what essentially Amazon and Microsoft and Google are doing is they've educated the market on the value of consumption and cloud. The hyperscalers have created a wave of opportunity. Everywhere you look, there is a huge digital transformation effort going on with customers of all sizes, and New Relic is perfectly positioned to help those customers instrument applications to support both their digital transformation and also drive their cloud migrations. We're also seeing that many of our customers are not using the full portfolio of capability. As we land more and more capability, we have an opportunity to engage our customers to solve more problems. We'll talk to that in a second. Lastly, customers are spending on competitive offerings. We've seen this proliferation of observability solutions across the market. Bill touched on it. I think Manav touched on it as well in a different way, but we know we've got an opportunity because 75% of our customers are actually using five or more tools. That comes with cost, comes with complexity, it comes with enablement issues, and managing that type of environment is extremely difficult. We know we've got an opportunity around standardization. The next thing I want to talk about is just how we create the flywheel of engagement with our customers. That engagement is really centered on consumption. When you think about our core business, our core business is driving solutions to difficult problems, and some of the things Peter talked about in his demo was amazing. Most customers have those issues. Where we start is in consumption. How do we engage our customer, our largest customers, add value to the problems that they're trying to solve, and drive consumption revenue? That is step one. All of our field organization, the entire field organization, is structured around our sales roles, our technical roles, our support roles, all of those roles, and our compensation model is aligned to helping customers grow consumption. It's never a good thing to hear the CEO of the company say, "Engineers don't like to be sold to," when you're the CRO. What I would say is, engineers do like to be sold to, but they like to be sold to by the right people. That means that you need a high preponderance of technical resources in your organization to work with engineers, to educate them on your capability and drive usage. The second piece, as we gain momentum with those customers, as we gain a stronger foothold with the customer, as we solve more problems, what we really find is we need to drive commitment in the way of contract. Ishan talked about the way we're landing contracts with customers, but overall, the sales teams anchor on that second pivot, which is, once you're driving consumption, you really need to, in any large enterprise, drive the budget that goes with that consumption. That means we're converting customers at volume, at scale, from potentially a pay-go relationship into a contractual relationship with our buying plans, volume plans, and savings plans. As we do that, we land step 3. Step 3 is to expand inside of the organization, to expand across teams, to expand across use cases, to expand in the way that we instrument more applications. That is incredibly important because what it does is, that creates the flywheel of driving further consumption and gives us an opportunity to get into renewed contractual discussions further down the road. Our goal is to have a long-term contractual relationship with every enterprise customer that we have inside of our organization. We're making good progress on that front. I also wanted to talk about the sales plays that we've deployed. The first two, really, digital transformation and cloud migrations are broad-based sales plays. They are secular tailwinds that we are taking advantage of. I've talked to those, and you'll see some customer examples where you can see a massive growth in consumption as a result of those two things pulling us through with them. The third one is much more important to us, which is, this is one that we drive. This is one where, as we engage customers on tool consolidation, it gives us an opportunity to move spend from our competitors onto our platform. That is a very important sales motion for us. The way that we train our teams, the way that we enable our teams, the way that we drive disciplined sales plays with our customers, the way that we engage our customers, potentially through partners, relates to and is aligned to tool consolidation or specialization. The last thing is how we build observability, centers of excellence. Observability is a practice, and that means that you have to have people inside of your organization that understand the technology, understand the problems that it solves, understands how to deploy it, and then understand how to take it further into your organization to instrument every application all the way up your stack. It could be your infrastructure, it could be logs, it could be any of those things, but developing the skill set to go and do that requires you to have a center of excellence. We see customers that have a center of excellence, and where we work with them, we see their consumption grow quite dramatically, and we'll see a couple of examples of that in a second. This is a customer, and it's a relative fairly fair amount of information on the slide, but I'll just talk you through it. This is the impact of consumption on a financial services company as they undertake a cloud migration initiative. The macro trend pulls through the opportunity, and it gives us an opportunity to expand into new teams and to consolidate tools. If you look at the green bars, what you can see there is they represent consumption run rate, and you can see that we're growing consumption 5x over 5 quarters. This is fairly common. You'd think that, hey, we've, you know, we've picked an opportunity with an extreme axis on it, and actually, we haven't. There are many customers that have that kind of profile and consumption growth as a result of taking on new use cases or driving instrumentation across applications. The pink line represents their commitment. That's the contractual piece where we secure a commitment and drive consumption on the back of that. What you can see there is that their commitment grows very dramatically as they go through the different steps. We were working with a partner in this instance. We worked with two of our partners. The customer, as they went through and went through the POC, you can see as they signed the new agreement, the agreement went up in value. The last thing I would say on this is, as our teams engaged on 2 or 3 different use cases, but the primary one was improving systems resilience, we helped build the practice as we were doing it, and finally, we consolidated platforms. This customer is committed to migrating 1,100 applications over the next 3 years onto our observability platform. That is an example of cloud migration in action. We're seeing that at scale. This is one example of many where customers move through cloud migration, move onto our platform, consolidate, sign a bigger agreement. The next example is, it's the impact of digital transformation on a customer. You can see this uptick is very dramatic as well. Here, the interesting one is it increases by the. consumption increases by 5x over a very short period of time. That's because we were running a POC with this customer against one of our leading competitors. I'm actually not gonna lie to you because this would be a weird story if we had lost in the shootout. You know, you actually do know the end. We actually won this one. The customer had essentially had a proof of concept running where we competed with leading competitor. As a result of being able to, 1, deliver more innovation, 2, engage the customer and engage their observability practice, we're able to win, increase our commitment, and drive our consumption. Again, this is a customer, a very large customer, an infrastructure vendor, who is really delivering digital transformation at scale. As they're delivering digital transformation at scale, what we're able to do as a team is, and you can see it represented on the slide, we engage, even if it's a proof of concept. The reason I kind of stress this piece is New Relic is an enterprise company. We have many enterprise customers. I read something the other day that said New Relic works primarily in a certain type of segment. We don't. We work in all segments with the biggest global customers, and we work in enterprise segment with the largest customers nationally. These trends that you're seeing on both cloud migration and on digital transformation are trends that we're seeing globally. I wanted to just touch on this. Bill had a different variant of this, but it's really important for the second part of our strategy. The first part is we've got secular tailwind. Good, that helps. The second piece is that we've got proliferation of tools. Proliferation of tools, when you've got 75% of customers using more than five tools, you know you've got an opportunity. You've particularly got an opportunity if you have an all-in-one platform that is built on a consumption model, and where your pricing model is very simple to understand. It's simple to understand. It's very economic. Commercially, we compare very well to our competitors, but that's an opportunity. This example is an example of where we've worked with a customer to drive consolidation of their tools, and this is a streaming provider, sports streaming provider. You can see, I don't know if you can see it from the back, but you can see from the front here, you'd be able to see the steps that they're going through, as a customer, as they add use cases and add tools and capability to the New Relic platform. You can see from the green bars there that we grow very dramatically as they go through that peak period. That peak period gives us an opportunity, to, one, prove our capability, but two, it gives us an opportunity also, to land new commitment. You can see from the pink line that their commitment, their contractual commitment as a customer is going up. This is something that is common. It is common to customers of all sizes. It's common to customers around the world. You can see that growth in consumption as a result of the consolidation exercise that they're going through. You can also see the steps that they're going through as they, as they consolidate, competitive spend onto our platform. In this instance, it was a logs vendor, large logs vendor, who had a big presence in the customer. We actually moved, all of their spend onto our platform. The last example is just developing the center of excellence for observability, and it sounds alien in this one because what you can see there is, as we work with this customer and go through adding dashboards and adding synthetics and adding application monitoring, and then we've taken it to the next level, and we've added distributed tracing, what we're doing there is we're working with that customer to develop their level of capability, their understanding of the technology, the way that they think about using the technology to get more and more benefit. That's an example of You can see those, I think some of these slides are takeaways, but you can see the steps that we went through with that customer. The interesting thing about this example is the commitment didn't change, and we're now engaged with that customer on a new contract discussion. What you can expect to see over time is that pink line will move up. I just wanted to touch on this very quickly, which is, these are just big customers, great customers that we have, that we've moved from our competitors, for logs, for APM, and for infra. We have many of these. If you looked at the slide that was in Bill's presentation, some awesome customers, and we're about to hear from some also. Those brands, many of those customers have moved from a competitor onto our technology. I wanted to finish very quickly with our partner strategy. We are building with partners, and particularly with hyperscalers. The hyperscalers are the core of our partner strategy, and we're building scale, we're building into new regions, with both AWS and with Microsoft. What you see here is the progress that we've made with AWS. We're now top, one of the top 10 ISVs on the marketplace, which means the volume of revenue going through, Amazon and through the marketplace is significant. The second one is we've now got an agreement with Azure and with Microsoft, which is awesome, and that is allowing us to reach new places, to reach new geographies, but also to reach a ton of new engineers. That gives us an opportunity as well. When we think about partner strategy, and you think about service partners, or you think about resellers and distributors, our focus is hyperscalers, and it will continue to be our focus, and that really fuels some of our direct sales engagement. What I hope you take away from this is Ishan's presentation on PLG. We really have a very efficient model of capturing new customers and bringing them into the company. We then have a great way of developing those customers as we go through our sales place. We build through consolidation and our centers of excellence. Finally, we scale. Through hyperscalers, we add to our sales effort and to our direct resources. Thank you for listening to that. This next session is the one I'm looking forward to most, because quite honestly, this is the session where you get to listen to some of our greatest customers, talking about how they use New Relic technologies to solve problems. It gives me great pleasure to introduce Kristy and the team. Great to see you, man. Thanks a lot, Mark. I am thrilled to be back here for the second year in a row, with the honor of introducing you to a couple of our fantastic customers, who are going to share their story with you, how they use the platform and how they get value from it. First, I'm going to introduce Chad Verbowsky, who joins us from Confluent. Confluent, many of you know, is an enterprise data streaming platform, and Chad is the Chief Technology Officer. Welcome, Chad. Thanks for joining. We've also got Arun Natarajan from Capital One. Many of you are probably familiar with Capital One. They provide financial products to consumers and enterprises. Welcome, Arun. Arun's a Senior Director responsible for observability on their engineering teams, and then Michael Cook from BlackLine. BlackLine provides financial software for the office of the CFO. All different industries, but uniquely passionate about being able to observe the software and make sure it runs. Let's start just by sharing a little bit. I've given the brief overview of your business and your role, but what does the company do? What's your role, and why is observability important? Oh, you need microphones. There's only two, so you'll have to share. Chad, why don't we start with you? Sure. I'm the Chief Technical Officer. I run all of engineering, all of trust and security, and the program management for Confluent. At Confluent, we build a streaming data platform for the world. Most data that's generated has to get to some system for collection and processing. That system, by default, is often Kafka. The founders of Kafka actually created Confluent to be able to build a cloud version of this that runs on all the different cloud providers and on-premise to collect all of that data. Data by itself is useless, so we also provide stream processing so you can get results in real time. Often this is for things like fraud detection in banks or just enabling you to book your Uber or get your food in real time along the way. For us, observability is at the core of what we do. It's just as important as power to the machines or the networking that keeps our services available for our customers. Without observability, we really don't know what's going on in our platforms, and that's a big problem. In fact, in one of my previous roles at a large cloud provider, when we lost observability to a data center, I made the call to move 200,000 servers, all that workload, somewhere else, because you just can't reason about what's going on. Hello, my name is Arun Natarajan. I run the observability agenda at Capital One. Building a great customer experience is a major element of Capital One's tech strategy. While there are several drivers that drive the success of that strategy, one that stands out is us being always on for our customers. We want to be able to connect any issues that our customers are experiencing with the underlying infrastructure or application issues. Gone are the days where an observability strategy had to do with, you know, lack of instrumentation or lack of data that is coming in from different layers of the app stack. With information is actually flowing from each of those different layers, and there's a ton of data that's coming in, those are table stakes. For a large and complex, forward-leaning tech organization, observability is all about racing against the speed of human interaction. There's so much data that's coming in, and humans can only get on an incident bridge so fast. Humans can only talk so fast. We're actually dealing with data that is coming in and being able to converge all of that into a platform that's actionable, that's accessible in many different ways, and all of this done at scale and all of it in real time. That's what we do at Capital One. Hello, my name is Michael Cook. I'm the Director of Observability and Service Operations for BlackLine. Being financial folks, you'll understand BlackLine. We automate the account close process, the reconciliation, closing the books for some 6,000 customers worldwide. For us, observability means I want to know when I have an incident before the incident happens. I want to be the one that finds it, lets my customer know there may be a potential problem, and hopefully fix it before it happens. I think that's critical, and you can only do that with a single pane of glass for observability, and New Relic provides that for us. Just to summarize, your customers are trying to close the books, your customers are trying to make payments or transfer funds. Your customers are running their company on your platform. The importance of being up is integral to what you're doing. Maybe let's start with the selection of an observability partner. Let's start maybe with Michael and Chad, as it's relatively recent that you've decided to standardize on New Relic. Can you talk about how you made that decision? Yes. Roughly a year ago, I started at BlackLine. I believe I was at the customer kickoff last year with New Relic, and we needed to take a look at how can we get everyone using the same information, the same data, and how can I get my meantime to detect a problem faster? I want to know everything. I want to know how everything's going. What New Relic allowed us to do was consolidate potentially 14 tools into one platform. The correlation of data when we have that tools, that kind of tool sprawl, it's encumbersome on the incident management team, it's encumbersome on the engineering team, the quality team. If we get everybody onto the same page, they're all using the same data, we're all running from one sheet of music, for lack of a better term. For us at Confluent, it's all been about massive scale. The number of just new customers, new clusters that we have for Kafka is just growing phenomenally. We have an approach of where many people are already using a similar product, so they come to us, and then that usage just grows very largely. The other piece is, as we add more capabilities to our platform, that also adds more metrics and capabilities that we have that we require. That compounded growth grows very fast. For us, our problem is really about how do we manage that scale? The scale comes in a few dimensions. One of them, of course, is cost, or do we really need all of this data? Can we afford to pay for it all moving forward? That's one element, but it's not the most important element. The next element really is complexity. For all of the pieces that we have, as we grow and evolve, how do we find those needles in the haystack? For us, that boils down to trust and reliability and being able to solve that problem very quickly, as you've heard from probably all of us here today. Our ability to grab that information and synthesize it very quickly so that we can hopefully automatically repair it, or if not, narrow that down, is just absolutely critical. Since we're across multiple clouds, and we're a global company with engineers and folks in our company around the world that need this information, we had to find a partner that was willing to grow with us. Somebody that, as we push these boundaries, is gonna be there to help evolve their platform. What we found is that was difficult to do before. We were really having to spin up a team of engineers to manage the cost so that we could differentiate and understand what pieces we needed, what we could throw away. That took a lot of work. It was also hard to build these innovations that we needed, like adopting OpenTelemetry and getting that into the platforms we were using so that we could grow and sustain that. We found that by working with New Relic through a long POC process, we just clicked. There was teams around the world that we collaborated with to make sure that what we were doing made sense, but it's not enough to just have our break-fix things in place. We really need to be proactive about understanding when we should, say, upgrade a customer's systems on our end so that it has minimal impact for them. It's more the proactive part, and it's also about integrating logs, metrics, and everything else that's going on in the environment, so we have that holistic view. Without that, we are left building a bunch of tools and piecing it together, and it requires a lot of human interactions, which, as we've heard, I mean, that's the difference between being up and being down enough that you're really damaging a lot of other businesses. For New Relic, it was really about that partnership, being able to find folks that were interested in innovating in this space and willing to grow with us as we needed these new capabilities. That's great. I know, you were looking at several technologies, and while the platform is important, the ability to scale is important, there was also some table stakes around capabilities like infrastructure, OpenTelemetry. Maybe let's talk a little bit about the capabilities that you're using today and then how they're evolving. We'll start with you, Chad, and then, Arun. I think the core part for us is really getting this information into a central place. As we've acquired companies, as we've built new technologies, it's important for us to piece these events around monitoring, understanding the infrastructure and our logging, so that we can debug across those things. Much like the demo that we saw here, which is pretty awesome, being able to quickly flip from, "This is an issue, what are the events and interactions and log pieces that led up to that?" So that we can narrow it down and optimize it. Now, the dream for anybody operating a business is that if there's a problem, it's a failure. If something's broken, you know where to look to find that issue. What New Relic helps us do, and the capabilities that we're most excited about, are solving problems like: what if a few of these requests are sometimes slow? How do you slice up the literally billions of requests per second you have to be able to optimize those pieces? What we're doing is really getting all of our telemetry on there. We're doing it through OpenTelemetry, which is really important for us because it means not just that it's done in a standard way, but that we can get people with the skills to be able to evolve and adapt these platforms. We're getting it all in there, and then we're looking at the more advanced pieces to evolve and optimize our alerting and monitoring. That's great. Thanks. Arun, just for context, you're farther along in your journey, so it's been several years since you made the decision to standardize on New Relic. You can talk about that decision and then how it's been rolled out across Capital One. Absolutely. We actually started with New Relic with a very important product feature, and that is the real user monitoring. We shared the objective of making sure that we know what's happening to our customer experience first with New Relic. That particular product feature allowed us to not only understand how many customers are getting impacted, but that actually started driving our incident severity, if you will. Then, as we made our digital transformation and our cloud transformation in the past years and completed it, we were in lockstep with getting good telemetry from New Relic around our cloud metrics, around our application metrics, and that provided great value to our developers. Thanks. Now, you've heard us talk today about ubiquity and the users of the platform. Maybe let's start with Michael. Who is using New Relic today, and how is that going to evolve in terms of the types of engineers and the types of people using the platform? Well, primarily right now, our software, site reliability engineers are the biggest consumer of what we're providing with New Relic. They're the ones that are responsible for our uptime. They're the ones responsible for making sure that our hosts are all active, that everything's going smoothly, especially at the end of month, end of quarter close. That's very important. Very important for our customers. Eventually, we're going to spin out to engineering, where engineering can look at the performance of their code, and it looks like real time. That was a great demo. Really excited about that. QE is going to use it in order to figure out where the bugs are so they can file the tickets. Future forward, we want to take a look at the customer experience journey. How can we leverage the data we're going to get out of New Relic to kind of guide that customer experience journey, to see how we can improve using the information that New Relic's going to provide, and eventually customer success. Yeah, one quick follow-up. I love how you talked about the decision to use New Relic and the ability to turn off whether it's 8 or 14 tools or somewhere in between. How you're kind of deliberately making sure you're getting it right before you roll out more broadly. I think cloud optimization and making sure that everything has high value is really on everyone's mind these days. Can you talk about how you're approaching that? Yeah, we want to do our rollout very deliberately. That's kind of been our mantra to our teams and our engineering partners and our partners in quality assurance, is we want to be deliberate. We want it to be repeatable. It'll be slow at first, but it's like any J-curve, we'll eventually ramp up, and it'll get faster and faster the more we deploy. Alerts are very important to us, but we want the alerts to be concise and actionable, and we want them to be repeatable and documented, well documented, so you don't have the noise that goes around alerts and logs. Thanks. Then, Arun, even farther down your journey and having New Relic broadly deployed, there's still opportunity to expand and new ways you're thinking of using the platform. Absolutely. While we're using a lot of real user monitoring infrastructure and APM features, we want to increase the scope of observability itself to be more upstream in extracting the data about, you know, the information that we can collect on behalf of applications even before it hits production. CodeStream is a great example of something that we're beginning to use. There's also other opportunities where we could get, you know, more metrics out of testing and kind of integrate all of that information so that, you know, we have good visibility of our customer experience and trace it all the way back to the beginning of the development of code. Thanks very much. We talked a little bit about the return on investment and how you calculate the value. Chad, you've talked about everyone using New Relic. Can you talk about how you're thinking about the value of the platform as you roll it out? Sure. I think it starts, of course, with the obvious ones. We're collecting logs, we're collecting data. We want to minimize the amount that we're spending on those pieces, so it makes sense to understand how those parts are being used. New Relic has provided a lot of insights to enable us to know not just what we're collecting, of course, but how those are being used so we can optimize and tune those pieces. Now, that's just table stakes. That's the core of what we do. The most impactful parts that we've had directly driving some of our revenue is understanding how our utilization is going in a more forecasted basis. Because of that, we can cut better deals with our cloud providers, and we can provide a better. C ustomer experience because we know when we can make changes to have minimal impact, we can minimize the headroom that we have across our massive fleet, and that's been super instrumental. The next layer of what we do is we actually track all of the capabilities in our platform and which customers are using them when. This helps push us towards a consumption model. All of our product management group understands, for the things we're developing and rolling out, how are they being used, where should we invest more, what's not working, and where do we need to make changes? This expands more to our whole paygo pipeline. We understand now from everybody who signs up, right to when they register with us or kick the tires on our products, how are they engaging? Where do they get stuck? What are the success paths for making it through our products? That involves all of our marketing and our field teams as well. Finally, we've got our support team, and we've got our field. We've got some major customers there. We have a dashboard that's based on this telemetry so that everybody understands exactly what's going on with these customers. We take it as kind of a point of pride. If we get any calls or any indication from customers that they're seeing an issue we didn't know about first, then how do we get that baked back into what we're collecting from New Relic, and we set those right alerts and thresholds. We also track this from the finance point of view, because we're, again, just like New Relic, want to understand what are our customers that are using, what are their cohorts based on their industry size, their adoption rates, where is it stalling and where is it ramping up, so that we can better engage with them to provide more value. We really see this operational data as not just the react and fix, I think we'll be out of business if we only focus on that, but really using this to drive our business forward across these functions. The key part of this, and the reason this works, is because we need a source of truth. Before, everybody had their own bastions of data that they were collecting, and things didn't quite line up. Having one source of truth is key to making this all work. That's great. Thank you. You mentioned it earlier, but I think it's worth highlighting. Just I love that future vision, a little bit of the from to. You mentioned a team of people working on managing observability versus being able to build code and the focus. I may have just stolen the headline, but did you want to say more about that? Yeah. It got to the point where we just didn't understand as well how our bills were growing. Like, we'd get a bill for observability. It was growing quite rapidly. We knew that we were adding customers and scaling, but it was just growing super linearly compared to that. We had to hire a bunch of engineers, almost like detectives, to figure out where our biggest opportunities were. What we've done, I think it was about 6 or 7 people, and we were able to cut our bill by 30%. Like, it was a massive difference. What was better is simply working with a platform that can expose how much each of the teams are using so that they can more clearly have almost like an invoice, not quite as money, but at least they know what they're producing, because it's actually quite obvious to optimize these things. It doesn't really reduce our growth. I mean, it reduces our growth overall. We still grow because we're adding new capabilities, but sometimes there's just some ridiculous things that you're logging that you might turn off, and you didn't realize it, and that's just been a huge gain. It lets me take these super sleuths that I have and have them really focus on the products versus just trying to find money that's we're leaving on the floor. Thank you. Arun, on the topic of focus, you had mentioned, thousands and thousands of dashboards that you had prior to the migration onto the New Relic platform. Yeah. Over the years, many developers, and we have thousands of developers, they have been creating dashboards and leaving the company or leaving the teams, and those dashboards were left out there decaying. With New Relic and its central management of observability, we were actually able to create, you know, one dashboard per application, right? It's a robust dashboard, it's centrally rolled out, it's automated, and it also has, you know, 99% of all of the metrics that are required by a robust cloud organization. We were able to do that, and we continue to maintain that, and it has worked out really well with the help of New Relic. That's great. Michael, I think a lot of these comments resonate with you, so feel free to expand. But also, you had mentioned that the use of observability actually improves your engineering capabilities as well. Yeah, I think it's integral for the engineering team to be able to take a look in real time at the performance of their code and how it's working, and then identify blocks, identify errors, know as they're writing code, where they need to go fix it, where they can optimize. That just improves our efficiency, makes our software respond faster, gives a better user experience, and it also helps the QE team to be able to see exactly what's happening when they're doing their testing, especially when you do load testing. You know, we're closing, you know, millions of transactions at the end of the quarter. It can get hairy out there. You got to make sure your infrastructure is robust enough and can handle the load, and the only way you can do that is with a dashboard or the proper logs in context. Everyone speaking the same language. I love it when everybody speaks the same language when it comes to data, because I hate getting data from correlated different tools. I don't know where it came from. I don't know where it's at. We're all working on the same sheet of music, is what I want. That's great. The last topic I wanted to talk through, you heard from Ishan and from Mark about how we try to partner with our customers to add value and to help them on their journeys in cloud migration and digital transformation. Can I ask each of you just to comment on what you appreciate, you all have deep partnerships with New Relic, and how we've partnered with you to help support you? You can go ahead, Arun. I can go first. We share a great vision with New Relic right from the get-go, you know, our objective to make sure that we put our customers first and have good visibility on our customer experience, New Relic has helped a lot in that space. Our cloud journey, New Relic has worked with us in lockstep to provide us with good visibility there, not to mention all of the application metrics that came with it. Most importantly, the embrace of the OpenTelemetry, open source industry format was a first. When we were talking to many of our suppliers, New Relic was the first to come in and offer us with that great capability. Not only that, we are an organization that tries to balance the reliability and sustainability of our observability solutions. New Relic plays really well in our ecosystem that has multiple products, both homegrown as well as commercial software. You know, when you wrap it all together, I think it's a great success story. Well, for us, we're just starting our journey with New Relic and moving off other tools. I think the biggest boon that I have from my account team is around the enablement, getting engineers used to using a new tool. No one likes change, right? They've been great partners with us, helping our engineers understand why would we choose this tool? Why are we going to this tool? Why are we moving away from what they have already? Will it have the same impact as the ones that they were used to? What we've been able to prove is that it's going to be better. Their experience using a true single pane of glass for observability will do nothing but improve their jobs. I think for myself, it's really the closeness of the way that we operate as a company. There's interactions that we have with Bill and David, you know, talking about some of the business and strategy parts. There's the finance people working their pieces out, their solutions part. You know, even yesterday, there was some interactions we had with engineering about, "Hey, we're seeing this, some ways that we want to grow and expand our usage. What do you think about how we can partner and work some of those pieces out?" These are emails, Slack messages, et cetera. It's not like there's a pile of these things, but when they happen, it feels like we're working with somebody else in another department of our own company. We have the same goals. If there's a challenge, we always work together, and we sort something out that works out awesome, I think, for everybody involved. That's not something you find every day. It's not like we're being sold a set of products, or we have to wrap ourselves around to make these things work. That makes a massive difference because now we can focus on doing what's best for our customers and really get things moving forward. What I like about this, predominantly, is that New Relic now is not just working with us, they're working with these folks and many others. When we have these interactions, we're learning. We're getting the best of techniques, strategies, and technology that they're building for everybody. That's more than I can build and do myself. That lets us really focus on, you know, building the best version of our product for our customers. That's great. Well, Michael, Arun, Chad, thank you so much, for coming, for representing your companies, and for sharing your stories. I really appreciate it. It's really impressive what you're all building, and happy to be partnering with you along the way. Thanks for having us. Thank you so much. I hope everyone enjoyed that. I greatly enjoyed it. I hope maybe through that, you understand just how much we love our customers, how much we love investing in our business. It's our passion. It's really what gets us fired up, really going out, building great software, empowering businesses that actually empower us, empower. Makes New Relic happen, and certainly Capital One. It makes our employees actually one of our popular credit cards. It's one of those great situations. What I'd really like to go in today, and I'd like to just take a moment to switch gears here on you. We've been spending time thinking about our vision and our strategy. We've been talking about our innovation pipeline and our innovation engine. I think I really love the presentation around PLG, a lot of this has really been leading to just what a great business model we have. What we started on, actually, Tuesday night or Tuesday afternoon, was really starting to unpack our financial model. I'd like to spend some time building on some of the disclosures, building on the 10-K and the investor supplemental, and starting to talk about that financial model and why we're so excited. For those of you that are familiar with a business model transition, you know there's always a journey. You're always investing. I was lucky I had Mark Garrett in my life, probably for my first business model transition. I thought Mark did a great job at Adobe. We've applied a lot of those same thinkings, into this. What we're excited about is we're really in that final inning. We'd like to just, if you'll indulge me, kind of go through a little bit of financial analysis and walk you through why we're going from just having a great business and a business that's really awesome for our customers, but also having a great financial model. We want to have the same great business for our shareholders, too. You know, just starting at the very top of the page, I think one of the elements that's important. It's a P&L by virtue of a business model transition that's not always well understood. That's really starting off with that shift to consumption. I think until Tuesday, nobody knew. Our consumption business, excluding the effect of migration, so just on a basic organic level, based on data and users, based on customers, has been growing over 30%, that's a byproduct of something that's very interesting. Most people would say, "Well, you're shifting your customers from subscription over to consumption." Well, that's certainly true. People are embracing a more contemporary business model, the bulk of the customers are all net new in the last couple of years. About 65% of our customers on consumption are new to New Relic. That is that hyper-efficient PLG motion that is really making it all happen. People are expanding once they get on it really starts to come. Bill called it out earlier around capabilities. Capabilities translates into more user engagement, more data, more premium features, whether it's FedRAMP, or some of the other qualities like vulnerability management that are in the cloud. Lots of great things that are going on. Somebody grabbed me earlier and said, "Well, why 4 to 6 quarters to wrap it up?" Well, one, we're really excited about the future. two, a lot of the material contracts are up for renewal in 4 to 6 quarters, we really have a wonderful opportunity, and a lot of it comes with things like Grok. A lot of it will come with new logs capabilities. Our innovation pipeline is just naturally bringing customers to the consumption business model that allows them to take a subscription contract that is restricted in terms of entitlements and allows them to open up. I think I love the way Chad described it. They're kind of consuming in a flexible way. They can turn things on and off as they need to. It's hyper-efficient and really accomplishes what they need. Moving down the P&L, I think one of the things that also is not really well known, we were a little. We got to the public cloud about 3 years ago, and we started our journey on AWS and started shifting from our data centers into AWS. What you wouldn't know is we've been actively investing, and so our New Relic in the U.S., mounted on top of AWS, is already operating at 80%. We're investing in Azure. We have an AWS data center in Germany. We're still closing down our legacy data centers. Even while we invest, we're at a 79% gross margin. A lot of it is just founded on really great engineering, and I have a page that you'll like later because it's a great example of how good our engineering is. Bill called it out earlier. We once upon a time, invested 48% of our revenue in sales and marketing. This shift to PLG, being able to graduate our accounts, has captured an enormous amount of profit, productivity. It's also yielded profitability as well, but it's also allowed us to continue and start amping up our investment in product as well. That's what you'll see. We'll continue to take savings that we generate from our business, invest more in product, and then bring some down for shareholders as well. We have a real good balance in our model. We shared about 3 months ago that we were heading towards durable double-digit margins, was a key component of our model, and at that time, we talked about it being at about 10%. Well, as we shared on Tuesday, and we've been, for those who have been tracking us, we take the world in increments of about 5. We shared an outlook of 14%-15%. We shared an outlook that we'll probably finish the year above 15%. We're always working on continuous improvement in our business. A lot of this comes from the simplification. Innovating and working with our customers one way is really unlocking an opportunity to invest more, but it's also bringing it all the way down to the bottom line. It kind of goes with that premise. We're investing a lot for our customers, we love our customers, bringing some of that economics to our shareholders as well. Every great business, I believe, ultimately produces cash, our cash flow margin ultimately tracks our non-GAAP op margin. I think we offered an outlook on Tuesday of about $150 million. We've been going through a very exciting and dynamic transition, that's all-in-one observability, shifting into the consumption business model. We're several years into it, as Bill highlighted, really just wrapped up our third year, where we've been pushing ahead. Again, in terms of things that you probably just don't know, and now that we put it in a 10-K, it makes it a little bit easier, but that's a pretty beefy document, so we'll kinda call out some of the more salient points. Again, almost 8,000 new customers have come into the business in the last 2-3 years. 4,000 customers have elected to migrate, and they've shifted from subscription to consumption. Again, what's really interesting, more data, more users, more premium features. A lot of it, all that innovation is starting to work its way through, and you see this strong push towards 76% of our revenue in consumption. Lastly, I mean, it is one where I think what excites us, really getting into that final inning of a transition, which anyone who's ever done one. I didn't know that in 2008, I'd start on Azure, and I'd start doing business model transitions for 15 years. That final inning is kind of exciting. Didn't know it would become a career path. I just thought it was an opportunity and a project. To give you a better view of where we're at, I thought it would be nice to go from an annual basis to a quarterly basis. We talked a little bit about last page, 76. Well, if you look at our last quarter, it's actually 84%. Really, and this is again, it kinda gets you into why we think we're really in that final inning, 4-6 quarters. Again, if you exclude the effect of migrations, 32%. If you were to go grab our 10-K, go through what Deloitte goes through with us, 55%. What that real, that 55% represents people taking their old subscription commitment, moving it into a consumption contract, and that's why it's a little bit higher. Again, this is a good organic view of how we've been working with our customers. We called out a little bit of churn, and this is gonna be that one element, where in, you're in your final 4-6 quarters. We will have churn. We won't ultimately get everybody over. We've been talking about that on the earnings calls. That's a good thing to keep in mind. This is one of the views that I really enjoy, and I think it's just incredibly helpful. We started off the transition with about 15,000 customers. Then again, I really call your attention to this top part, which is the PLG motion that's been driving and acquiring customers. It's a really interesting set of customers. It's the customers that are deeply engaged in consumption. They are organically expanding. They're Fortune 500, they're F 2000, they're leading public sector customers. It's a wonderful, interesting mix of customers. It's really creating a foundation for really strong organic growth. What that motion that Ishan described earlier is fascinating, as we were building our budget and building our financial model for the year, really, we double-clicked into this motion that's been going on. We started finding lots of interesting logos that you wouldn't expect, but logos that you regularly read about. That's when we really started to appreciate just how effective it's been as we started building out the plan for the next year. It's why we're this graduation motion, which we had already started, but now we're starting to perfect it in terms of having million-dollar logos, in terms of annualized spend, pretty meaningful logos. That's where I think we feel great about our ability to be ubiquitous. Ubiquitous isn't code for SMB or small customers. Ubiquitous truly is ubiquitous. That's our land motion. Let's talk about our expansion motion, because I think this is very helpful. One dimension that we've always reported on is NRR, and our dollar-based net retention, but we've used an NRR metric that is in a 12-month, well, it's a 24-month period of time, where we grab a cohort, we look back 12 months, we're looking forward 12 months, and we compare two 12-month periods, which you'll see in our disclosures with the SEC. What I thought would be helpful, because it's a question that comes up regularly, is, well, if I looked quarter-over-quarter, if I grabbed your Q4 FY23, and I compared it to Q4 of FY22, what would that expansion look like? What you'll see on the 12-month metric, it's 118 on our filings. If you had to actually did it on an apples-for-apples basis, you use this 3-month methodology, it gives you 115, which really means out of our growth, 15 points of our 18 points last quarter came from the customer base, 3 points came from net new customers. Let's take a look at it from a consumption perspective. Dollar-based net retention of 124. A chart ago, you saw 32% growth for consumption in Q4. 8 points comes from new logos, 24 points comes from the customer base. Let's talk about what else is different. Churn. A lot of deep customer intimacy, very focused, as we've really engaged and worked deeply with customers on the consumption model. Very low churn. Let's talk about some of the expansion elements. As we really went across, and we started looking at how consumption has come to life, how we work with our customers, again, it really kinda comes down to this engagement of more capabilities. From a, from a Wall Street perspective, let me do a little bit of conversion. A capability for us is what you'd probably see as a product for another company. What's different about it, our capabilities, you don't have to negotiate, you don't have to sign a purchase order, you don't have to sign a new subscription. You have access to all the capabilities. As Manav was articulating, over 30 capabilities that are in the stack, you turn them on. If it's not working for you turn it off. If it's too much telemetry, you can moderate it. All the telemetry is available to you straight away, if you look at it relative on a benchmarking perspective, I think it gives you an idea of how this product strategy really is starting to unfold. Why does it drive more users, more data, more premium features? Everything is at somebody's fingertips. They need something like FedRAMP, they have access to it. They can turn it on. If they need something like vulnerability management, they have access to it. Let's kinda shift our way down the income statement a little bit more. One area that, you know, that I think has been underappreciated about the financial model, really is this dynamic shift that's gone on between having our data centers and actually embracing public cloud infrastructure. We're at a point where primarily we work with customers on AWS, but we brought Azure online in January. A small portion of our cloud is in GCP. Really, a phenomenal amount of engineering has gone in to be able to ingest this amount of data, and then be able to operate with this level of profitability. Just for kicks, I put down here our costs on a non-GAAP basis, about $65 million, all the way down to $51 million. People talk about cloud optimization. It's really real. This is our cloud optimization. This is really great engineering. Huge credit to Steve and his team. They're doing a phenomenal job. The reason we like this, and the reason we're excited about it sets up a model where we're able to push our savings and have a highly productive cloud and be able to pass it on to our customers. When we think about our data cost or the cost of how we're running our business, we think about do great engineering, build a great product, but be able to pass that savings on. Equally, you know, I think one of the interesting dimensions that also gets lost is just how efficient product-led growth is in this graduation motion. We've been pulling down sales and marketing as a percentage of revenue, made a lot of progress, but we're not done. This is a feature that will continue to unfold as part of our economic model, certainly going into how we think about investing in product, and then certainly as you look at our G&A. Legal, HR, finance, all figuring out how to scale the business more effectively, continuing to bring down our cost as a percentage of revenue. Every business model transition goes through a period of time where you're investing in order to get to a financial outcome, or a financial model, or a combination of a financial model and a business model that you truly love. We did that. For several years, we invested. We invested thoughtfully, both in product, thoughtfully invested in terms of retooling the business. We started to see some of those dividends as we got to the second half of this fiscal year, and I think it was one where we're kind of starting to get to that point where it starts to get interesting. We'll come back to that in a second. Let's actually shift to where we are going, 'cause I think this is actually helpful for everybody. If you kind of work your way from top to bottom, we've really spent a lot of time, both in terms of not only how we build our budget, but also how we build our financial plan and our financial outlook, about thinking about where we wanna be. How do we wanna serve our customers? How do we wanna serve our shareholders? It is one where, as we wrap up this chapter and finish the final inning of a transition, we really do look at it and say, gosh, feel really good about where we've been on product, the user adoption, the data growth, the premium features. Our consumption growth has been really steady. Of course, during this opportunity. You know, during this window, where there's a little bit of macro and there's cloud optimization, I think that will continue to unfold, but that we look at and say, "We have plenty of proof points around how we can grow our business." We feel very comfortable that over the course of a long-term model, being able to grow at 20%-25% feels like a very responsible outcome for the company. You can imagine that we'll continue to invest, right now, that 79% it is burdened with still ramping Azure, still ramping in certain regions. No reason that, based on the proof points that we have, we can't operate a highly efficient cloud that is really compelling for our customers, but be able to operate it with 80%-82% margins. You can expect that we'll continue this PLG motion. We really have accomplished quite a bit in a few years, but there's a lot more, and we know how to continue fine-tuning that engine. We'll be putting more of our money into product for our customers. It's really a North Star or a guiding light for us, and we'll continue to find that efficiency in G&A. That ultimately naturally yields a level of profitability and a level of cash that we think creates an economic model that, again, good for shareholders, but it's a business model that's really great for our customers, and that's that balance that we're trying to strike. How do we get there? We actually think we're well on our way. We feel like we do have our proof points. In a few years, we've driven about 30 points of expansion, if you look at it on an exit rate basis. This is one where you'd say the initiatives between what we're doing around product, how we're going to market, how we're actually dialing in our consumption business model, all of it is really nicely coming together. I hope you're starting to see those proof points in terms of how we've built the business, because as we've planted the seeds, we actually think we're just in the early days. So if you like what you've seen so far, we think you're gonna continue liking what the business has to offer. During the, I think during this time, I think one of the elements that was on our mind was being able to try and outline and lay out maybe the breadcrumbs for how this actually starts to unfold. You've seen consumption revenue kind of gradually step up over time, as of last quarter, about 84%. As we get into FY25, we think it becomes virtually all of our revenue, and our consumption growth rate naturally becomes the total revenue growth rate for the company. We think we will naturally continue to expand post-cloud optimization, post-macro. I think we have all of the tools to ultimately drive growth. We think profitability also continues to expand. I think our allocation of capital and how we're running our clouds, how we're putting money into product, and then ultimately thoughtfully being able to invest in a highly efficient sales motion, certainly a highly efficient G&A function. We think that naturally produces a healthy amount of profit and a healthy amount of cash flow. We'll be principled about what we do. I think most important, I think it is one where winning customers, it's more than just, I'd say, winning a logo or winning a customer. It is a relationship, and I think, hopefully you heard that from our customers. It is one where we look at it and say, Gosh, there's an element around winning a customer. It's all about winning the workloads. We wanna make sure that we're doing a great job on digital transformation. We still believe there's a lot of mileage in cloud when we look across our customers in financial services, certainly in healthcare, public sector, telco. A lot of opportunity, and I think about our partnership with everybody we work with, and we think there's just tremendous real estate. We still think there's a lot of opportunity around tools consolidation, that tools, and the abundance of tools, I think the BlackLine example was a great example, where that's a dynamic we run into around bringing together platform technologies. Again, more than more There's an element of winning, but almost you want, you wanna rewin your customer almost every day where you have that opportunity to expand. Again, we're gonna continue doing this in a very thoughtful way with consumption. I think the way that the Confluent team almost monitors how everything unfolds, we wanna be very value conscious in how everything that we do. We really wanna be efficient in how we ultimately use our time and our capital to make sure that we do it well. From a shareholder perspective, we always want you to know, we actually are one of the companies, we think stock-based compensation is an expense. We actually do think about dilution. Both are very important to us. With that, I know we're actually running a little bit over. We'd love to do a little bit of Q&A, take time for some questions, and then I think after that, maybe we go have some refreshments, and we'll continue the conversation over a little bit of. I think we have some food and some drinks lined up. Bill, do you want to come up and join me? Super. Then I think, Ingo, we have a couple of mics. Okay, super. Okay, well, we'll start with this. Thank you very much. Tim Jeznach with Credit Suisse. Thank you so much for the extensive presentation. I know a lot has gone into it, and it's great to see. Maybe to kick it off, Dave, you've talked about the 20%-25% long-term growth target. Could you help us unpack that, maybe within what the core vectors of growth are that you're seeing between users and data growth over the long term? Help us understand what kind of market share gains, potentially, that guidance embeds. It's a great question. I think one technique that we've used is we've really gone and looked at common cohorts of customers. We really did take an opportunity to evaluate customers for roughly 18 months as we've looked at things almost pre-macro, because it started to impact different regions and different industries at different times. We started looking at that lens, where we looked at capabilities. How did data grow? How did users grow? How did some of the premium features that started to contribute to data price, as an example? I guess that's really what got us confident, is we used those examples, and then I actually brought them together with customer anecdotes and situations where I've been involved with customers and trying to bring together vignettes or examples together with the macro data. I guess that's what gives us confidence. Maybe, you know, maybe a final one that really I'd say is almost brings conviction is I look at where, for some of our larger customers, where they're at on cloud adoption, but where they aim to be. That level of real estate, where when I think about customers in fin services, as an example, where maybe they're at 5% or 10% penetrated, where they have a population of applications they'd like to move to the cloud, it still feels like very much early days. Hopefully, that's helpful, just in terms of kinda going micro to macro. Sanjit Singh with Morgan Stanley. Congrats on the very extensive and very thoughtful presentation. Over the last year, plus just the execution on the margins and cash flow, you guys were ahead of your software peers in terms of focusing on efficiency. Now it's kind of like all about growth, right? How do we accelerate that? My question for David is that we exited this year at 18%. Yes. You're guiding 10-11 next year. Between, let's say, macro and obviously this transition. Mm-hmm. if you could decompose, like, what% of the, you know, 8-point decel is coming from, let's just say, cautious on the macro versus the transition. As we get to the other side of that, those subscription customers that convert to consumption, are they a different profile customers? Are they also going to expand? Are they gonna be sort of accretive to the growth rate, neutral to the growth rate, or are they gonna be, potentially slower growing? That'd be my first question, then a follow-up for Bill. Okay. I guess when we were building the financial model and building a budget, 'cause, well, what can I say? I'm a CFO, I love a good budget. I took a lot of time to really go through the customers that are subscription customers. I think I, on Tuesday night, I tried to describe it almost as a pyramid between some larger customers, maybe the top 100-200, that represent the bulk of the contractual commitment, a couple thousand in the mid-tier, a couple thousand at the bottom. I guess we had conviction that those at the bottom, who almost naturally qualified for the free tier, they probably do naturally churn. Both in terms of a number, the ACR impact wasn't huge, but that comes out. We started to profile as we went up the stack and tried to figure out. We had always had a little bit of churn each quarter, and it happened for a variety of reasons, I assumed that actually would uptick a little bit. I assumed it would uptick because we're probably pressing a little bit to actually wrap it up in 4 to 6 quarters, even though contracts are up. I took churn actually up, and kinda turned the crank actually a little bit more than 2x, to get up to a level of churn that I thought would start to get me to a conservative place. I started to actually model in some optimization that I thought would occur, because I've seen people optimize as they go from a fixed commitment to a consumption commitment. I would say that was a pretty healthy piece. Then, I guess as part of the outlook, I think I shared consumption growth would be 38% in Q1, 30% on a full year. I tried to model out how I thought the cohorts would work, both in terms of additional cloud optimization, probably primarily around what I think could happen in data. I gave you probably my, you know, maybe my best, closest to the pin, just giving some puts and takes on what's, what I'm seeing cohort by cohort. That's very helpful. My question for Bill, as is for the, you know, the key architect of this, you know, consumption strategy that's been in place now for the better part of 3 years. When you look, I mean, I guess it's sort of a generative AI question, but from a business model perspective, I wanted to get your take on, as we enter this new sort of compute era, are you gonna be able to price at a premium for something like Grok, which was just, like, super impressive, right? That mix between data and seats. I think there's some concern that seat growth may be slower in this new era. I just wanna get your take on how you're thinking about those dimensions as we enter this new, super new compute era. Yeah, great question. We've been thinking a lot about Grok, not only the technology, obviously, but how it relates to our business model. As I laid out, you know, we've had user and data pricing. The data growth we've shared and has significantly contributed to our revenue growth. We've talked that user growth, how we expected it to take time, and we expected it to be more difficult to grow because it's much easier for customers to drive optimization around users. They essentially have one place to do that. They can decide when a user's provisioned or when to revoke that provisioning entitlement in order to manage cost. What's interesting about a Grok, as a capability, is it's expanding the aperture of users who can access observability data and get insights from it. We think of it as a driver of user engagement, and that will drive the demand for in-product user upgrades. By the way, any engineer can walk into New Relic and request an upgrade. Admins can decide whether that upgrade happens by default, automatically, or whether to approve it through a workflow. In either case, we believe Grok will drive demand for user engagement, which then translates to, you know, higher user growth over time. I mentioned earlier as well, that we've been piloting around user engagement, an even more efficient model for query-based access, that's also very interesting, and Grok will also drive demand for that pricing meter as we roll it out more broadly. All right. Wonderful. Rishi Jaluria, RBC. Really appreciate all the detail. This is super helpful. Maybe I just wanna think a little bit longer term about, you know, the consumption uplift. You, you've talked about some of the differences you're seeing in NRR, churn, usage patterns. If we wanna think longer term, especially, you know, just given all the features and functionality you keep adding, how should we be thinking about just a longer term opportunity of converting from subscription to consumption? What sort of overall, like, LTV, I guess, if we wanted to think about it from that perspective, that can drive? Maybe any framework there would be helpful. Then just a quick second question, as a housekeeping question. On the R&D piece, I'd love to see that going up, I think this is the first time I've seen this in an analyst day in a very long time. I'm really excited about that. What's included in that? Does that include any sales resources like SEs, is that purely actually product and engineering? Thanks. Sure. I think if I think about the components of a good long-term value, certainly the area that we study a lot is churn. It corresponds with, for us, customer success. Are we investing thoughtfully? Are we really helping our customers address all of their mission-critical problems? As we've shifted people from contractual buying programs, the legacy, when we first started consumption, we had an annual pool of funds, and now we're at a point where we have our pay go, our volume, and our savings plan. There is an element of almost friction as you go from enterprise software buying program. I think our goal is to continue managing churn actually lower, because we're getting to that point where we're coming up with very compelling ways to work with customers, ways to pass on savings. We'll continue to, from an LTV perspective, to drive churn about as low as we can. While I think we are at a pretty low level, I'm not sure we're at as low as we can go. In terms of gross margins, I feel really good being at 79, having our AWS instance in the U.S. at 80. Feel pretty good. Our engineering team has just been lights out. Getting up to 80%-82%, and then having low churn, I think it ultimately gives us and provides an opportunity for a great LTV. Great question in terms of our SEC geography. Our R&D people, they work for Cebo, they work for Pez, they work for Manav. They're engineers. It's a CS team. If you're a computer scientist, you're in our R&D org. I don't know, if you studied liberal arts, you're probably in our sales org. I don't think we have any. I'm sorry, Mark, did I leave you? Mark may have studied science. The sales guys are also scientists. Our sales guys are scientists, too. Everyone's a scientist, but in terms of our geography, that's how the personas line up. Hey, thanks. Great presentations. Pinjalim from JP Morgan. That Grok demo was really powerful. I've not seen something like that. I'm thinking about the underlying requirement for that. I think the underlying requirement would be that all the data sits in the same place, and you have the NRDB to do that. We are also hearing similar things from other companies, right? Datadog has Husky, Dynatrace is talking about Grail, Elastic is talking about Elastic Data Store. I mean, you have a edge right now with Grok. Nobody has, I think, AI assistant, for sure. How do you keep that competitive advantage? What differentiates you at that data layer across each one of them? Yeah, it's a great question. New Relic, again, mentioned earlier, this unified data platform is one of the best services, best technologies I've had the pleasure to work with, from some prior great companies that build great technology. Lou, certainly, I have to give him credit, with the R&D team, saw this even before I arrived and began the engineering effort for it. That data platform is years in the making. Since I've joined, we then have brought all of the data into the data platform. It was, you know, closing out in R&D and sort of beginning the migration and unification as I joined, and then we've moved it to public cloud and now multi-cloud, so we can scale it. In terms of the differentiation, how we keep that advantage, it's just through continued R&D. You saw a number of investments on the roadmap that was actually first unveiled to you all here, analysts and investors, before even customers, including the SuperAgent, the telemetry pipelines, and the Fleet Control, all associated with managing, you know, ingesting and managing data at scale. Many of those advances are leapfrogging what competitors have today or are completely unknown in the market. We're continuing to invest. You know, that's one of the things I think is really different and special about New Relic, is we really take a data-first approach to observability versus for many of our competitors, they think of data as an enabler for the applications they build and sell to customers, whether that's an APM monitoring tool, a logging tool, an infra tool. It's sort of an application-centric approach, and the data supports the application. For us, it's the other way around. Everything starts with data and the data platform. The capabilities then unlock the value of data. That's just a philosophical difference in why I believe we're going to continue to create and maintain that technical moat. Great. Thanks, Ingo. Rob Oliver with Baird. Also echo my thanks for all of the detail. Really helpful. Bill, this could be for you, or it could be for Manav or the product team as well. Really appreciate the disclosure you guys gave on the additional capabilities. I'll use the right nomenclature here, capabilities, not products. A long way from the old days of, "I just use New Relic for APM." Clearly progress there, but, you know, what I'm curious about is scaling those capabilities, because, you know, when we do checks, you guys clearly, you know, doing really well on APM blogs. Seems like you've had a lot of success, but I know you just did, like, a reboot of your infrastructure product. I'd be curious to know, like, where are we in terms of your ability to walk in as some of the customers we saw here that are gonna jettison 8, 10 other users, presumably some doing infrastructure, some doing other things. Where are you in that trip, that journey, in order to get to where you need to be to be able to scale all of those different capabilities? With each capability, which as Dave helped with the translation, relates to a product for most of our competitors, right? We don't use the term product because product typically denotes a package and a price, whereas with our capabilities, it's part of the all-in-one platform. Every one of them has a journey, right? Some of those we implemented three years ago or before. We've migrated from our legacy platform. Some of those, we started just the last year, and as the innovation is unlocked, there's a life cycle associated with that. For example, our vulnerability management capability we introduced in January, it was in preview for about three or four months before that. It garnered many hundreds of customers in preview. We GA'd it, made it generally available, and unlocked in-product upgrades for the add-on price to get it. We've had now hundreds of customers go through that cycle and add the add-on or upgrade to Data Plus. As Manav shared, we're now continuing to add more capabilities to our security capability set. It will just get better and better over time. That journey on security, as an example, is independent from infrastructure, from logging, from errors inbox. Every one of those has dedicated product managers and engineers that are looking at the maturity and competitive strength of that capability and how to evolve and strengthen it over time. That's one of the reasons that we're gonna continue to invest in R&D, is as the capabilities grow, they each have their own life cycle and require, you know, both investment to maintain, but also to, you know, engage with customers and invest to strengthen the capability and adoption over time. One last question, and then we break for happy hour. Oh! Hi, Kingsley Crane, Canaccord Genuity. You've talked about essentially 10X-ing your active user count to around 10 million. What implications might that have for ARPU over time? Do you view a seat-based model as a fundamental headwind to reaching ubiquity? Yeah. Good question. One of the reasons I brought up the pilots on query pricing today, as I mentioned, it's a more efficient model that allows for scale of users without that higher user price, and also captures some of the non-user interactions with data. A lot of teams build scripts and do automation against our data platform that we don't license in terms of a user seat today. We'll be capturing a lot more of that with query pricing over time. Some very large customers are already using it, and, in the coming quarters, as we've, you know, mature and harden that, you'll see that be made available as an option to customers. Actually, we believe it's gonna be a win for customers and for us, in terms of expanding the set of users we go after. All right. I don't wanna stand between them all and cocktails, so- Are we across the way? Thank you, thank you all for joining again. We're breaking now for happy hour. I'm sure we'll have some more chats with the executive team. Thank you.