Hi, everyone. Welcome to the Confluent Q4 and 2021 Earnings Conference Call. I'm Shane Xie from Investor Relations, and I'm joined by Jay Kreps, Co-founder and CEO, and Steffan Tomlinson, CFO. During today's call, management will make forward-looking statements, including statements regarding our financial outlook for the fiscal first quarter of 2022 and fiscal year 2022, increased adoption of our platform, our ability and position to capitalize on the shift to cloud, our ability to sustain relationships and integration with cloud providers, growth in revenue, customers, remaining performance obligations, and dollar-based net retention rate, our market opportunity, our go-to-market strategy, our ability to meet near-term and midterm financial targets, and our overall future prospects. These forward-looking statements are subject to risks and uncertainties, some of which are beyond our control, which could cause actual results to differ materially from those anticipated by these statements. Further information on risk factors that could cause actual results to differ is included in our SEC filings, including our Form 10-Q for the quarter ended September 30, 2021, and our Form 10-K for the fiscal year ended December 31, 2021, that will be filed with the SEC. We assume no obligation to update these statements after today's call, except as required by law. As a reminder, certain financial measures used on today's call are expressed on a non-GAAP basis. We use these non-GAAP financial measures internally to facilitate analysis of our financial and business trends and for internal planning and forecasting purposes. These non-GAAP financial measures have limitations and should not be considered in isolation from or as a substitute for financial information prepared in accordance with GAAP. A reconciliation between these GAAP and non-GAAP financial measures is included in our earnings press release and supplemental financials, which can be found on our investor relations website at investors.confluent.io. With that, I'll hand the call over to Jay. Thanks, Shane. Welcome, everyone, to our fourth quarter earnings call. We ended our first year as a public company on a very strong note, once again exceeding our guidance on all metrics. Confluent's success continues to be driven by the rise of data in motion and the shift to the cloud. Revenue in the fourth quarter totaled $119.9 million, representing growth of 71% year-over-year, a further acceleration from our 67% growth last quarter. This is our fourth consecutive quarter of revenue growth acceleration. Revenue from Confluent Cloud in the fourth quarter grew 211% year-over-year, continuing to significantly outpace the growth of our overall business. Confluent Cloud represented 28% of total revenue, up from 26% last quarter and 15% one year ago. Another milestone of note is that for the first time in the company's history, Confluent Cloud surpassed 50% of new ACV bookings. This is an important milestone. It's often a struggle for a second product to get to critical mass if the first product still shows significant growth. With this milestone, we've crossed a clear threshold point, and Confluent Cloud is now the most significant focus of our go-to-market engine. A fundamental driver of this growth is the rise of data in motion as a foundational underpinning for companies' success in digital transformation. Tech disruptors are building around real-time data streams to deliver rich digital customer experiences and are setting the standard for customer expectations. Mainstream enterprises are quickly realizing that their ability to harness data in motion is key to their survival, as this is at the heart of the customer experiences and operational capabilities they need to compete in the modern digital world. Cardlytics is a great example of one of these tech disruptors. They power reward and loyalty programs for the world's leading banks, and their approach to increased customer engagement is underpinned by data in motion. With Confluent, they analyze the real-time purchase data of more than 170 million customers and use this consumer spend intelligence to present highly relevant and timely offers within a bank's digital channels. These offers help the bank acquire new customers and increase loyalty. You couldn't do what Cardlytics does without data in motion. Central to our leadership in our space is the strength of our product. We shape our value proposition around three pillars of product differentiation, being cloud-native, being a complete offering, and being everywhere. These three pillars help express the advantages our product has, both against other competitive products as well as for internal IT teams that might otherwise attempt to do it themselves with open source components. I'll briefly recap these areas of differentiation and summarize some of the new capabilities we've launched in each of them. First, being cloud-native. It isn't enough to just offer software in the cloud. Developers today demand services that are fully reimagined in a cloud-native way. This means being massively scalable, elastic, secure, API-driven, and multi-tenant. This lets the customer ignore the low-level details of operations, move quickly, and focus on using these services to create value in their organization. In Q4, we took steps forward in this area by improving the elasticity of our Kafka offering more granular scaling for ksql, and the integration for HashiCorp's Terraform platform. These are steps that attracted Dapper Labs. They're one of the most innovative NFT companies delivering fun, and have a number of decentralized apps, but one that's risen dramatically in popularity is called NBA Top Shot. To date, there have been over 10 million digital collectible transactions, and Confluent is at the center of their data streaming architecture to facilitate these purchases. Dapper chose us to run their mission-critical workloads because of the scalability and security of our cloud solution. Our second pillar, the completeness of our product, is another area where we've continued to raise the bar for data in motion, giving customers advanced capabilities, including enterprise-grade security and governance, ksqlDB for stream processing, as well as our rich collection of connectors. Our newest fully managed connectors include Azure Synapse Analytics, Amazon DynamoDB, Databricks Delta Lake, Google Bigtable, and Redis, bringing the number of fully managed connectors to over 50. Without these connectors, integrations between systems and applications take months and require significant resources to manage. TeePublic, a customer of ours that runs the largest online marketplace for independent creators, recently shared their use case, which uses Confluent with our S3, Elasticsearch, Salesforce, and Snowflake connectors. Using these, they can act on the real-time stream of user interaction data to power product recommendations and create a more personalized shopping experience. Our third pillar is being able to run everywhere across all our customers' environments, whether on-premise, hybrid cloud, or multi-cloud. Using Confluent, customers can link together data from these disparate environments and geographic locations to create a unified fabric for data in motion that seamlessly spans all the parts of the company. Our ability to serve our customers wherever they are is unique to us and is a massive competitive advantage. We made significant progress on this dimension as well. We recently added eight more regions for Confluent Cloud, bringing the total to 66 and helping to fill out our presence in APAC. We released the 7.0 version of Confluent Platform and improvements to our Kubernetes-based private cloud integration. Customers like BMW Brilliance really benefit from running our service across clouds and on premise. They are responsible for producing, distributing, and selling BMWs in mainland China. They use Confluent to integrate their order-to-delivery services. This process spans multiple countries, many manufacturing plants, and requires clusters across AWS, Azure, Alibaba Cloud, as well as on-premises. Confluent acts as the central nervous system, bringing it all together. To truly ensure that Confluent is everywhere, we must be well integrated into each cloud in which we operate. This is a key priority for us as it makes us a natural part of the cloud environments our customers have chosen. It's also very compelling for the cloud providers as it helps their customers unlock data from their on-premises environments and take full advantage of the many data systems and services in the cloud. One very significant step towards this integration is our recently announced strategic collaboration agreement with AWS. Under this five-year agreement, Confluent and AWS have committed to increasing product integrations and development, as well as joint go-to-market initiatives to help organizations accelerate their cloud adoption journey with real-time data. We are really excited about this agreement, which will help our joint customers unlock the power of data in motion more quickly and seamlessly and take advantage of Confluent in AWS environments. We also see this relationship as a strong symbolic indication of the mutual respect between Confluent and AWS, given the willingness and desire to collaborate on such a large and meaningful agreement for both parties. A significant customer for both AWS and us is DISH Network. With their new 5G smart network, DISH is transforming how people and enterprises leverage data. They deployed Confluent Cloud over AWS to connect their network systems and customers with real-time data. This means that Confluent is a key part of their network's data backbone, starting with fault management and network resiliency functions to ensure network availability. Our enhanced collaboration with AWS is making it easier for customers like DISH to unlock data in motion everywhere. Another exciting new environment where Confluent is now helping customers is through Alibaba Cloud. As we announced in December, Confluent and Alibaba Cloud have partnered to offer the Alibaba Cloud Confluent Data Streaming Service via the Alibaba Marketplace, servicing our multinational customers with operations in China and opening the power of data in motion to domestic customers in mainland China. We've added significant differentiation in our product, but our product is not the only big differentiator for Confluent. I wanted to spend some time on the call today talking through another critical area of focus, what we call our customer growth go-to-market. This is explicitly aimed at helping to land customers and help them grow their usage of our product from early experiments to large-scale central nervous systems. Stepping back a bit, I think the ability to build around a customer's adoption journey and help ensure rapid low-risk value realization is one of the biggest innovations that cloud infrastructure enables. This may be slightly counterintuitive, so let me explain what I mean. People tend to think of cloud as being about automating operations. This is true, but it misses the bigger advantage. Cloud is a model which, when done right, can let customers adopt and realize value faster and with lower risk. This mirrors the transformation in the world of application-level SaaS, where the transition to an as-a-service model turned out to be as much about go-to-market innovation as reducing hosting costs. A well-designed SaaS go-to-market enables the company to move with their customers down a natural, low-friction, low-risk path to realize the value the product provides. The transition of the world of data infrastructure to a consumption-oriented SaaS model allows us to accomplish a similar thing. This has been a key focus for Confluent over the last few years. It's particularly important for us because data in motion has a very unique customer journey that's different in critical ways from other products, even other infrastructure products. Adoption of data in motion often starts with developers in the early phases of product experimentation. At this stage, being low friction and building developer love are the keys to success. A product needs to be available for instant usage with all the needed features and the least amount of hassle. Stopping to try to plan out the structure of a large deal or negotiate pricing at this early stage would serve a little purpose and slow down the development cycle. As a technical project starts towards production, new needs arise. Are the security, availability, connectivity, and compliance needs met? Is there predictable pricing that is economically attractive? In this phase, it's important to provide the customer with the qualifications and assurance they need to depend on the service as a mission-critical part of their infrastructure stack. Succeeding in this phase involves satisfying multiple economic and technical stakeholders. Over time, as multiple such projects emerge, the customer's use of Confluent goes through a transition. It goes from being an ingredient in one project to a layer connecting many such projects. There is a natural network effect for data in motion that helps drive this expansion and the progression between these stages. These streams go between applications. Our customers add streams to the platform, unlocking value for that use case, but also attracting other applications that need to tap into these streams. Hence, the virtuous cycle of adoption is that applications bring incremental data streams with them, which in turn attract new applications that need that data, which in turn bring new streams of data, and so on. This journey is truly unique to data in motion because of the natural virtuous cycle and network effect that comes from the sharing of data in Confluent. We've designed our product and go-to-market engine around this unique journey. At each point, we want to solve for the products and support from Confluent that will best help customers succeed and progress to the next stage. We've structured our go-to-market efforts around three key principles. First, being product-led. That is, making sure the product is present in the journey the customer takes from day one, and the in-product features and tutorials help this progression and learning at each stage. Second, being consumption-oriented. We've designed our models so that customers can start quickly with our self-service pay-as-you-go capabilities and can expand rapidly by adding additional use cases and consuming more without the need to stop and negotiate a new transaction. This is good for customers because it removes much of the risk and upfront analysis they would otherwise need to go through when deploying new products. It's good for Confluent because the reduction in friction and risk enables faster expansion. Finally, our efforts are built around the stages of the data in motion journey. Because this is our sole focus, we can bring to bear our millions of hours of experience, our learnings from thousands of customers, and our differentiated product to support customers in each phase of adoption. Using these principles, we bring together a variety of go-to-market tactics suited to each of the different stages. Self-service sign-up and adoption, as well as open source downloads, help developers get started in a low-friction way without requiring any contact with sales. This is often done with free credits or in a pay-as-you-go model that lets them start quickly and with low risk. In 2021, the traction of our self-service cloud adoption helped us grow our customer base 65% year over year to approximately 3,470 customers. Our sales team engages early in the customer life cycle to help customers that are progressing towards production to ensure their needs are met. Our customer success focus starts on day one. As a customer's project becomes part of production operations, they would likely move to a committed contract which they would lock in in exchange for discounts. The best proxy for customers in this stage is the count of customers 100K or greater, which grew 43% year-over-year to 734 customers. Our team then engages to help the spread to additional use cases and teams to ensure the data in the platform is widely available and that there's top-level buy-in for the larger architectural role that Confluent can play in the organization. Growing a strategic cross-organization platform requires a full enterprise engagement, including sales, technical resources, partners, and services. These later-stage customers are common among our 1 million-plus customer base, which grew 57% year-over-year to 88. A key aspect of our approach is that these disparate go-to-market capabilities are not deployed as disjointed silos, but rather are linked together into a continuous journey that is built to help the customer succeed with data in motion. Confluent's ability to help customers navigate this journey successfully and quickly is a key differentiator because it builds on our deep knowledge of this emerging space and the needs of customers at each stage. By being solely focused on data in motion, we are able to organize all our teams around this journey and do it far better than our competitors. Companies that work with Confluent will realize more value more quickly and with lower risk because of this. We believe this customer growth go-to-market model is a significant competitive advantage. Smaller startups struggle to operationalize this journey because they lack the field team and customer success motions to serve large customers at scale as the platform becomes critical across many lines of business and use cases. Legacy infrastructure companies struggle because they lack the self-service cloud product and product-led growth capabilities to serve developers at the early stages in the journey. The cloud providers have many of these capabilities, but they've organized them around a very different customer journey, general cloud adoption, and they're not set up to get customers to success in the new paradigm of data in motion, especially when that involves bridging into data not yet in the cloud. I wanted to go over this customer growth go-to-market model in some depth because it continues to be an area of ongoing effort and investment for Confluent, and we think it will be a critical moat. We continue to work to develop easier, low-friction adoption at the beginning of the journey, easier, more transactional project-level sales for the middle, and best-in-class enterprise sales and customer success capabilities at the end, each supported by the right product capabilities for that phase. Integrating all these capabilities to best support this journey is a significant undertaking, but it's critical for helping customers to drive the value that we can provide, and it's central to our mission to set data in motion. This combination of our product differentiation and our unique operationalization of the data in motion journey started to come together in earnest in 2021, and I think these two key differentiators helped us achieve the results we did over the course of the year. We're really just getting started and look forward even more to the year ahead. With that, I'll turn the call over to Steffan to walk through the financials. Thanks, Jay. Good afternoon, everyone. The results for the quarter and the year were very strong, and the main theme that described the year is growth acceleration. Starting with the highlights for the full year 2021, we delivered four quarters of accelerating growth in RPO and revenue and drove sequential improvement in NRR in each quarter since our IPO. Confluent Cloud revenue accelerated to 200% year-over-year growth and accounted for 24% of total revenue. This top line growth translated to better leverage than we expected as non-GAAP operating margin and non-GAAP EPS beat our original estimates for the year. Turning to the fourth quarter, we delivered an excellent quarter with results exceeding the high end of our guidance on all metrics. Q4 was highlighted by record new customer additions, a strong net retention rate, and continued top-line growth acceleration. As Jay mentioned earlier, our differentiated platform and go-to-market motion enable us to meet customers wherever they are on their data in motion journey. This dynamic helped add approximately 450 net new customers in the fourth quarter, a record high for the company. Growth in our large customer base was driven by the network effects inherent in our model with customers connecting more data and applications through our central nervous system, strong partnerships with cloud service providers, and our ability to execute our customer growth go-to-market strategy. Another key measure of customer success is dollar-based net retention rate. Driven by strong gross retention and expansion across both of our product offerings, NRR was comfortably above 130%. This marks the third consecutive quarter of exceeding both our near-term target of greater than 120% and our long-term target of greater than 130%. Our thesis that Confluent Cloud, with its consumption-based model, will have a higher NRR profile than Confluent Platform is playing out. In the fourth quarter, NRR for Confluent Cloud was meaningfully higher than the company average. In the cohort of customers running both Confluent Platform and Confluent Cloud, it has the highest NRR. We are very pleased with the progress we've made in increasing this key metric since our IPO. Going forward, our goal is to drive NRR consistently above 130%. Turning to revenue, Q4 total revenue was $119.9 million, growing 71% year-over-year, an acceleration from 67% in Q3, and our fourth consecutive quarter of revenue acceleration. Subscription revenue was $108.2 million, accelerating to 71% growth year-over-year and accounted for 90% of total revenue. Within subscription, Confluent Platform revenue was $74.4 million, accelerating to growth of 42% year-over-year and accounted for 62% of total revenue. Confluent Cloud revenue was $33.8 million, representing growth of 211% year-over-year and accounted for 28% of total revenue, up from 26% of total revenue last quarter and up from 15% a year ago. As growth in Confluent Platform accelerated, Confluent Cloud continued to grow above 200% and increase as a percentage of total revenue. This dynamic is driven by the strong demand for Confluent's complete platform to harness data in motion everywhere, the secular shift to cloud, and the enhancements in features we've continued to add to both products. Turning to the geographic mix of revenue, demand for our industry-leading platform remains robust in the U.S. and across the globe, with customers in over 100 countries. Revenue from the U.S. grew 68% year over year to $74.3 million, representing 62% of total revenue. Revenue from outside the U.S. grew 74% year over year to $45.6 million, representing 38% of total revenue, up from 37% of total revenue a year ago. Q4 was another impressive quarter of sales execution, highlighted by the strength in remaining performance obligations. We ended the fourth quarter with $500.6 million in RPO, an acceleration of growth to 91% year-over-year. Current RPO was estimated to be approximately $319.8 million, up 72% year-over-year, a further acceleration from 65% year-over-year growth last quarter. Our customers' growing desire to build towards a central nervous system with Confluent is driving an increase in multi-year deals as they look toward making a long-term commitment to us. Moving on to gross margins and profitability, I'd like to note that I'll be referring to non-GAAP results unless otherwise noted. In Q4, Confluent Cloud revenue increased as a percentage of total revenue and subscription revenue, which led to total gross margin of 68.2% and subscription gross margin of 74.7%. Both were down sequentially and year over year. The decline was anticipated as Confluent Cloud has a lower gross margin profile than Confluent Platform. With that said, we've seen substantial annual improvement in our cloud gross margin, and we remain in our early days of achieving leverage and scale for our infrastructure that supports our cloud offering. As Confluent Cloud continues to scale and account for a larger share of total revenue, we anticipate total gross margin to fluctuate near our midterm target of approximately 70%. Turning to profitability, operating margin was negative 41.4% compared to negative 31.7% a year ago. The performance is attributed to our plan to catch up on hiring given the pause we took in 2020 and our continued investment for growth. Free cash flow margin was -22.3% compared to -30.4% a year ago. The improvement was primarily driven by strong collections and the impact to timing of cash flows related to the contributions from our employee stock purchase program. Net loss per share was -$0.19 using 265.5 million basic and diluted weighted average shares outstanding. Moving on to the balance sheet, we ended the fourth quarter with $2.02 billion in cash equivalents, and marketable securities. This includes approximately $990 million in proceeds from our convertible debt issuance in December, net of issuance costs, and the purchase of cap calls. Before turning to guidance, I'm going to discuss our investment priorities and philosophy for 2022 and beyond. Coming off the strong results in 2021, where we demonstrated our disciplined investment strategy has been successful in driving growth and favorable unit economics, we're well-positioned in 2022 to continue to drive high growth while improving operating margin. Our priorities are to continue to invest in the innovation engine to extend our technology lead with a cloud-first approach, further develop our partnerships with the CSPs in the partner ecosystem, and invest in our go-to-market organization as we look to increase our footprint in geographies and theaters across the world. Looking beyond 2022, we're capitalizing on the rise of data in motion and the secular shift to cloud in a 50 billion-plus market, and we're laying the groundwork to meaningfully scale our business in the years ahead. We're committed to delivering high growth and annual improvement in non-GAAP operating margin as we drive towards our midterm target of approximately 5% and free cash flow margin target of approximately 10%. Turning now to guidance, I'd like to note two items. First, going forward, we'll be providing guidance on operating margin instead of a dollar-based operating loss or income metric. This better aligns with our philosophy of prioritizing investments for growth while driving operating leverage in our model. Secondly, we expect certain COVID-related savings we've seen over the past two years to fade in 2022. The guidance for the quarter and the year take into consideration an increase in expenses related to travel, in-person events, real estate, and facilities. For the first quarter of 2022, we expect revenue to be in the range of $117 million-$119 million, representing growth of 52%-54% year-over-year. Non-GAAP operating margin to be approximately -50% and non-GAAP net loss per share in the range of -$0.23 to -$0.21, using approximately 272 million weighted average shares outstanding. For the full year of 2022, we're raising our revenue guidance relative to the initial outlook we provided on our Q3 earnings call, and we now expect revenue to be in the range of $538 million-$546 million, representing growth of 39%-41% year-over-year. Non-GAAP operating margin to be -39% to -40% and non-GAAP net loss per share in the range of -$0.82 to -$0.74, using approximately 281 million weighted average shares outstanding. I'd also like to provide some modeling points for the year. We expect non-GAAP taxes to be in the range of $4 million-$5 million, capital expenditures in amounts capitalized for internal use software costs to be approximately 2%-3% of total revenue, and we expect more pronounced seasonality for free cash flow margin in Q1 and Q3 due to the introduction of our new corporate bonus program and employee stock purchase plan. As a result, we expect Q1 to have the lowest free cash flow margin, followed by Q3. In closing, the fourth quarter capped a momentous year for Confluent, and we're very pleased with what we accomplished in our first six months as a public company. We're still in the very early stages of a significant opportunity for data in motion, and we look forward to building on our momentum in the years ahead. With that, Jay and I will take your questions. Thank you, Steffan. If you'd like to ask a question, please raise your hand on Zoom. We will pause a few moments for our team to assemble the Q&A roster. Our first question comes from Phil Winslow of Credit Suisse, followed by UBS. Phil? Phil, are you there? Okay, let's move to Jason Ader at William Blair. Can you guys hear me? Yep. Oh, sorry. Thanks a lot. It's the beauty of a Zoom call. Zoom is great until it doesn't work. Thank you guys. My question is, where are you seeing the most friction in the monetization engine? Ask it a different way, where do you see the biggest opportunity to really accelerate things, on that data in motion journey slide that you showed? Yeah, I actually think we have opportunities at each of those stages. You know, one of the downsides of having multiple things is they're each in the earlier stages of development. I think we've shown success now at each stage. I think probably one of the bigger opportunities is to kinda open up that top of the funnel. There's still an enormous number of open source Kafka users, so we're kinda just scratching the surface on that. I think if we bring more people into that funnel, even in the early kinda phases of learning, I think that can have really big upside for us over time. Do you have any quick metrics on Kafka, kind of how broad-based Kafka adoption is? Yeah, you know, it's hard to provide kind of exact stats, and so what we have is kind of the same stuff you would find, you know, out there by looking at different leaderboards or download stats or whatever. There's not an official kinda download count number. We kinda would roughly estimate it to be in the hundreds of thousands, so. Okay. Thank you, guys. All right. Thanks, Jason. We'll take our next question from Karl Keirstead of UBS. Karl? Oh, there we go. Karl- Sorry for the trouble. I was kicked out there for a moment. Thanks for bringing me back in. Jay and Steffan, maybe I'd like to ask you about the if it wasn't asked already, apologies, the cloud platform mix in 2022. Jay, you mentioned that cloud is now over half of the new ACV bookings, and that your reps are really leading with it. When I look at your platform numbers, you've been growing pretty steadily in the 40-45% range for four or five quarters. If your reps are collectively gonna lean into cloud, should we expect the on-prem platform growth to maybe slow as the emphasis is put on the cloud? I guess I'm asking for a little bit of mix color, Steffan, on your 2022 reps guidance. Yeah, you know, I'll let Steffan, you know, speak to anything on the mix. I think broadly, you know, one thing that's critical to understand is we don't really view this as kind of a transition where we're just, you know, shifting from platform to cloud and just kind of swapping out customers from one product to the other. You know, effectively, we have to have kind of an outpost in each environment a customer is in. We expect to continue to see growth in Confluent Platform throughout this, and we think that's not a bad thing. That's a good thing. Now, obviously, as you say, you know, the field team will kind of have focus in different areas, where are the net new projects going. There may be some shifts there, but I wanna just clarify that at the opening, that it's not a pure conversion story. Got it. Okay. Karl, on the mix side of the house, you've seen Confluent Cloud take more of the revenue mix over the last several quarters and over the last year, et cetera. We anticipate that type of trend to continue, basically, you know, for the next year, for sure. Confluent Cloud will have a higher mix of revenue at the end of 2022 than it has in 2021. We don't guide specifically on individual line items on the P&L, but thematically, that's what you can anticipate. Okay, got it. Thanks for the, thoughts. Yep. Karl, we'll take our next question from Kash Rangan of Goldman Sachs. Hey, guys. Thank you very much. Steffan, I like the, you're dressed the Wall Street guy, and I'm dressed the guy. So nice outfit there. Jay, you too. Congrats on the quarter. A terrific acceleration going. Jay, I really loved the first few slides where we walked. You gave us a primer of your business model. As far as the cloud is concerned, I'm curious to get your thoughts, since the cloud is so evolved today, is the first line of engagement for an entry-level customer different than the first line of engagement for that entry-level customer had it been on the on-prem sites? Meaning, are they engaging at a higher commitment, or are they much farther along in their awareness of Confluent? If so, it looks like we're hitting the tipping point from a technology standpoint with Confluent Cloud. When technology tips over, then the business model tips over as well. How are you planning as a CEO running the company and creating targets for the long term, when there's some unknowns? It could be a good unknown, but this whole cloud thing looks like we're hitting the tipping point, and this could be a big transition. Steffan, follow-up for you. As a CFO, how are you gonna manage this transition? Because this could open the doors for an entirely new business model. Not new business model, but different implications for customer acquisition costs, profitability, revenue outcome longer term. Thank you so much. Congrats. Awesome. I'll start with the first part of that. Yeah, actually our push is almost the opposite, which is not necessarily trying to push a bigger deal, you know, for that first stage. One of the reasons I wanted to show that journey is really with the cloud what we can start to do is move the commercialization upstream, you know, so that people are engaging with our cloud product even before the first use case is identified, even as part of their learning of the skill set around data in motion. That kind of land faster and, you know, smaller, as needed and then expand from there. That's actually the push that we have internally. We think that does lead to, you know, much faster growth down that path for a whole variety of reasons, but, you know, in large part because of the obvious one that you're not sitting around waiting for servers to be ordered and provisioned and learn how to operate it and set up new infrastructure. All of that gets sped up quite significantly. That's kind of a little bit about how we're thinking about the journey. You know, there is one of the reasons I wanted to mention the 50% of new ACV is really because, yeah, there has been a big push internally to make sure that this caught on. You know, a cloud product, it's, you know, it's not just another product. It's effectively an entirely different delivery model and go to market. We knew that there was a lot of synergies in having both of these, but it's obviously a huge effort for a small company to get that going and get it to critical mass. You know, you asked a little bit about how are we operating internally. Yeah, that's been a huge push really across the entire company to make that really catch on. You know, to your point, there is a lot of uncertainty, you know, when you look out into the larger term of just even how quickly is the move to cloud gonna happen. You know, if you say, "Hey, in 2024, 2025, what's, you know, customer spend gonna be in the cloud?" I don't think we have a crystal ball, you know, any more than anybody else does. We're setting targets around that. I'm You know, Steffan, you may wanna comment on how we're doing it. Yeah, there is uncertainty around that. I mean, we're very happy with the progress, you know, the business model for both of these, and we're well set up, whatever the kind of split is, I think, to capitalize on that. Indeed, you know, for a lot of these customers, that transition is one of the drivers of adoption of data in motion because it's acting as that bridge between environments. On the second part of the question, Kash, there are a number of elements that we take a look at, but we start with a first principles approach of looking at what our customers are telling us. Mm-hmm. What our customers are telling us is by and large, they're running hybrid environments. We need to continue to be a cloud-first company, but also have products that enable customers to manage their data wherever their data resides. From a business model standpoint, the great thing about our cloud offering, which we've been very, I think, hopefully clear about, is this frictionless, seamless way to onboard customers through a pay-as-you-go model is super important. That helps with the overall economics of the company longer term, better margin profile, et cetera. It's still early days. There's the next step along that journey around those cloud customers that start in the pay-as-you-go format. When they transition over to being a committed customer, you know, we like to see that progression as well, and that's why we spent some calories during the call today talking about our sales and go-to-market model. Because in that customer journey, we need to be there for our customers at each step along the way. Over time, we believe that lifetime value and overall lifetime spend of our customers will be greatly enhanced, and therefore, that all plays into this growth and profitability framework that we outlined at the time of our IPO. You know, we're in high growth mode today. We're forecasting to continue to be in high growth mode, and we're improving operating margins. The business model basically pairs itself very well with that growth and profitability framework. Got it. Thanks, Steffan. Thanks, Jay, and thank you, Shane. Yep. Thanks, guys. Kash, we'll take our next question from Derrick Wood with Cowen, followed by Barclays. Great. Great to see you guys. Congratulations. First question, I wanted to touch on the agreement with AWS. First, can you give a little more detail around what the go-to-market looks like and how you expect that to ramp over the next 12 months? Second, what does this say about the competitive dynamics with Kinesis and MSK? I mean, I guess more specifically, what are you seeing from both a win rate and a displacement rate against these offerings? The first thing I would say, you know, this isn't entirely new. We've been partnering with AWS, as we do with each of the cloud providers, and, you know, those have been our most important partnerships for a long time. I do think this is a big deal, and it has a couple aspects, right? There's an economic aspect in terms of our discounts with them. There's a go-to-market aspect in terms of how we're taking this out to customers, and there's kind of a product and engineering collaboration side of it in terms of how we just make the things work well together. You know, each of those are actually really significant. I think the key thing that has driven this is less about, you know, Kinesis or Confluent. It's actually about the importance of data in motion in these ecosystems. Like, for them, although, yeah, there's a handful of things in AWS we compete with, there's a handful of products in each of the clouds we compete with. You know, as an organization, it's very cooperative. You know, their project is about getting data into the cloud, about connecting up all the different systems, and driving utilization in all their hundreds of data systems and offerings, driving application workloads. It's a huge win for them, you know, as an organization, as customers are using more Confluent that has a really significant spillover into their utilization and commitment rates overall. You know, that's what I would highlight. We, you know, do compete with individual kind of teams or projects in each of the clouds. Some of these are kind of small and nascent and not, you know, massive. Some are, you know, more successful. We do really well in that competition. Like, we're very happy with the win rate that we see, you know, in each of the clouds against any of the, you know, competitive offerings you would care to name. Perfect. Steffan, maybe one for you. Great job on the free cash flow in the quarter. I know you don't guide on free cash flow, but anything we should keep in mind as we build our models for 2022? I mean, should we be thinking about free cash flow margins kind of trending in a similar fashion to operating margin? Anything you can help out on that front? Yeah. Thank you. There are a couple things. The first is there's gonna be some seasonality to free cash flow, which I called out in my prepared remarks. We have the impact of our bonus program, that's happening in Q1. Then we have also new program for employee stock purchase plan. Directionally, free cash flow margin should trend like operating margin. There's gonna be some perturbations along the way, but directionally, that I think that's a good way to think about it. Derrick, our next question Thanks, guys. Congrats. All right. Thanks, Derrick. Sure. Our next question comes from Raimo Lenschow with Barclays, followed by Morgan Stanley. Thank you. One for Steffan, maybe. Like, as we get to see you as a public company and kind of understand the different quarters and how seasonality works, can you maybe speak a little bit towards the cloud progression this quarter? Because, like, one of the questions I got from investors was like, "Oh, look at the sequential revenue up was about the same as in Q3." Can you maybe talk a little bit about aspects of seasonality or something that played a role here? Then I have one follow-up for Jay afterwards. Yeah, for sure. First, we're very pleased with the 211% year-over-year growth. From a seasonality standpoint, remember, cloud is a consumption-based model. In different quarters, you're gonna see higher levels of consumption. In Q4 as an example, there are some holidays that are there. People oftentimes lock down environments before year-end. Like those dynamics are at play a little bit as well. I can tell you that from an ACV standpoint, and Jay highlighted this, greater than 50% of new ACV bookings came from cloud. That is a great leading indicator of the business. The consumption patterns within a fiscal year, they are gonna kinda ebb and flow a little bit. you know, we were really pleased with the year-over-year growth rate, and being able to post another quarter above 200% was great. like I said, the ACV numbers and the RPO numbers were very healthy. Perfect. Yeah. That's really helpful actually because that helps us to kind of square on the seasonality there. Jay, one for you. The one thing we saw with other vendors that kind of went with an open source solution and then went into the cloud was that in the cloud there was a lot of like self-serve business going on. When the cloud offering came from the proper vendor, you know, you slowly started converting that. What do you see in terms of self-serve instances for Kafka in AWS, et cetera, and the opportunity for convincing those peeps that it's much easier to work with you, and that could be a main driver for growth for you going forward? Thank you, and congrats from me as well. That's actually a phenomenal opportunity for us, and you know, these customers are actually at each stage, right? There's people just getting started, they downloaded the open source, they find out there's a cloud product and they go try it. There's people who are actually at significant scale. A lot of the you know, big Silicon Valley tech companies, you know, they've been building around this for a long time, and we're starting to see success with these, you know, very large users of Kafka. You know, the reason is very clear. Engineers are quite expensive, and having kind of your smartest team of people running some internal infrastructure layer, which is really hard to do well at scale, and to do in a cost-effective way that actually uses cloud infrastructure responsibly, is not really what they want. You know, if there is an offering that they think can meet their needs at scale, there's actually now a lot of enthusiasm even from the most technical companies, you know, about embracing that, as they have with other, you know, layers in the cloud. Yeah, I think that represents a very significant opportunity for us. Okay. Thank you. Well done. Thanks. Our next question comes from Sanjit Singh with Morgan Stanley, followed by Citi. Hey, Sanjit. I can see you there. Hi. Can you hear me now? Yep. Perfect. Thank you so much, and congrats to you, Shane, Jay, Steffan, team, on a very successful 2021. Really great to see all the numbers. What I wanted to ask you, Jay, was really sort of the pace of change. I think we all understand that there's an emerging data and application architecture that's getting reconstituted. You guys are at the heart of that. The theme of your last two earnings calls has been what you guys have been doing on the product side in terms of improving the capabilities. When you sort of have those conversations with your enterprise customers in terms of building the real time piece of this future architecture, how much of a priority is that going into 2022 versus 2021 or last year? If you can get any sense of how big a part of these conversations you're having with CIOs? Yeah. I think it's a significant priority. I mean, you know, I think this was already true, but the, you know, the pandemic seems to have kind of accelerated some of the digital transformation efforts and the move to the cloud overall. With that, you know, it's not just a matter of picking up a workload and moving it. With that does come this whole kind of rearchitecture that brings in the things that you would use if you were building it now, right? That, Confluent's a big part of that. Particularly because we kind of bridge between these environments, that often becomes really important. How are you gonna peel off that next workload and get it there while it has to connect back into things in other environments? Yeah, I would say we're a very significant part of that. We're often, you know, a critical element of that kind of hybrid or multi-cloud architecture that they're pursuing, and I think increasingly prevalent, you know, on the minds of senior technology leaders. That's my question for Steffan, to dovetail on Jay's comments. If you think about how all of us have turned to macroeconomists the last three months, and we're thinking about rates and inflation, I think the idea about focusing on profitability, focusing on unit economics, and I guess that's a topic I wanna bring to you, Steffan. As we think about the core components of your unit economics, whether it's the gross margins, which I think you've talked about at length so far, but the improvement in gross retention and net retention, can you sort of break that down for us in terms of how much of that is coming from the sort of recovery post-pandemic customers that may have downgraded to open source Kafka getting back on board with Confluent? As you guys get more successful with the strategy, building out that application ecosystem, what will that do for your gross retention and net retention rates? Like, essentially, like how much upside is there as we think about getting to your profitability targets over a midterm framework or in a longer term framework? Well, the unit economics in general are very healthy for our company. Whichever metrics we're looking at, could be gross margin, it could be the components of net retention rates like gross expansion, and retention, et cetera, as well as LTV to CAC and magic number, right? Like if you look at all of those, they're very healthy. When you look at specifically net retention rates, what gives us a lot of confidence around our ability to Move off of what our near-term target was, which was 120% and now saying, "Hey, it's 130%, and our goal is to 130% going forward," greater than 130% going forward, is the fact that Confluent Cloud net retention rate is higher than Confluent Platform. Customers who are running both cloud and platform have the highest NRR. When you peel back the layers of the onion, if you look at gross retention, gross expansion, they're very healthy and improving. The point that you made, which, you know, is good because, you know, back in June of last year, I was answering a lot of questions around, you know, like, why is net retention at 117%, etc. We spent a lot of time kind of explaining, yeah, there were some impacts of the pandemic where there were a couple of companies that cycle off the platform. That's actually a rare case these days. By the way, those numbers are out of the dollar-based net retention rate. We've sunset those. You can imagine the head of steam we have relative to new customer acquisition, the gross retention rates, and the expansion rates are very healthy. We feel good about greater than 130%. Where that takes us over time is to be determined, and there's gonna be fluctuations along the way, for sure, but we felt good enough that we have three quarters in a row of greater than 130% and three quarters of a row of sequential improvement in NRR. And that is those are good facts for us. We have to you know, we're not gonna lose sight of it. We're not planting the victory flag. We're gonna continue to take it as high as we can, but that those are some of the dynamics at play. Very encouraging. Great to hear. Thanks. Yep. Great. Thanks. Our next question comes from Tyler Radke with Citi, followed by Bank of America. Hey, thanks a lot for taking my question. Two questions from me about some of the analytics use cases, and I think last earnings call you talked about some of the data warehouse modernization use cases. Could you maybe talk about what are some of the use cases and go-to-market motions that are surprising you to the upside? You know, what are the most successful? Then the second question, I just wanted to ask you about the hiring environment. Obviously operating expenses are still growing pretty nicely, but just what you're seeing in terms of the ability to recruit, retain talent in this environment and anything we should think about on the cost side, heading into next year. Thank you. You know, look, I don't know if there's been any kind of breakout surprise on the go-to-market side. A lot of it was what I talked about in that journey. You know, with the kind of investments we planted, we're really building out the self-service kind of funnel and starting to connect that up into that overall flow. We have started to partner around different use cases and solutions, so that data warehouse modernization that you mentioned, that's feeding into a lot of these next-gen analytic systems. That's something where there's a lot of companies that are offering those products and have a you know, really critical need in terms of how they ingest things that's been successful. I don't think there's one kind of outsized use case that's you know, driving a disproportionate share. You know, across that broad spectrum of use cases, we've seen great growth. On the hiring front, yeah, we you know, we're obviously paying very close attention to both hiring and, you know, retention given kind of what you would see in a lot of other companies. You know, on the whole, that's been solid for us. We you know, we're kind of broadly on track with our hiring targets. You know, we've been happy with the retention numbers we've seen. You know, it's probably good news on that front. I don't know if you want to add anything to that, Steffan. The only thing I'd add is, given the performance that we've been able to deliver, employees want to, they wanna be part of our journey, and prospective employees wanna be part of our journey. When we post growth, like an RPO like we just did, or record new customer additions, a lot of the underpinnings of the financial model that translate into, "Hey, we are actually helping our customers achieve their goals," that's the type of journey that folks wanna sign up for. That's part of the story as well. Thank you. Okay. Our next question comes from Brad Sills with Bank of America, followed by D.A. Davidson. Great. Thanks, Shane. Hi, guys. Congratulations on a real nice quarter here. I wanted to ask about that customer cohort greater than $1 million. It really stood out as some real solid growth this quarter, acceleration it looks like to 57%. Can you remind us what those customers typically start with, and how do they get there? How quickly does a customer get to that type of ARR? Yeah. The answer unfortunately is that it varies. Part of the reason for that is the existence of the open source, right? I showed this journey. Obviously we're assuming you started with us in stage one, but some people have started with the open source. They've kind of progressed. They have some production use cases, and we're kind of converting them midstream. Depending on the point that we're picking you up, you could actually start quite large. Now, that doesn't mean that that's really when you started. You actually may have started some years ago. You know, one of the nice things about actually engaging early on in our commercial offering is we can actually help you progress and ensure you succeed. You know, it will vary based on kind of when we're picking you up and how long that's been happening. It will vary also based on cloud and on-premise. It's a lot easier to expand with cloud, and we see that in some of the numbers because you know, you're not actually having to, you know, order servers or hire a team of Kafka experts to help with operations, and that can allow you to move much faster as well. You know, unfortunately, there I don't know that there's a simple rule of thumb that covers all types of companies and all use cases. It really does vary between them, and it depends on when we pick them up. Thanks so much, Jay. Maybe one for you, Steffan. When you look at the sales and marketing line, you know, where are the top priorities? Where are you investing this coming year, for sales and marketing, please? We're definitely focused on building out our sales footprint in terms of both international and domestic headcount expansion. That's one thing. When you look at our customer success organization, which isn't technically part of, like, the S&M line, that's a key part of an investment strategy for us that plays into the overall field operations work that we're doing. Because we're trying, especially for our consumption-based business, we're trying to decrease the amount of time it takes for our customers to start to consume, and that is a key area. On the marketing side of the house, we're very much focused on demand gen, pipe gen, also building out our brand in a very meaningful way. With the leadership on the sales and marketing side with Erica and Stephanie, respectively, we feel like we're in a really good spot to have a lot of great performance over the foreseeable future. Great to hear. Thanks, Steffan. Thanks. Next question comes from Rudy Kessinger with D.A. Davidson, followed by Deutsche Bank. Hey, great. Thanks for taking the question, guys. Congrats on the quarter. Another kind of question on the customer cohorts. I guess if the average, you know, 100,000-plus ARR customer is kind of in stage two or three, and your average 1 million-plus is in stage four, is it fair to say that, you know, the bulk of or maybe, you know, the average customer that's a 100,000-plus in that stage two or three can be a 1 million-plus customer once they get to stage four? Yeah, I think that's absolutely the case. You know, even in the million-plus customers, we're seeing great expansion. Yeah, I think, you know, that is true in almost any but the very smallest companies. This can be a very significant part of the architecture. Even in, you know, smaller techy companies, this can turn into a significant line item. In large companies, just the number of systems and applications, you know, even if we've been working with them for some years, we're still in the early days of what's possible over time as these application layers turn over and start to utilize this new paradigm more. Got it. Just a quick follow-up. I know the AWS partnership's been asked on a number of times. I guess on the Alibaba deal announced back in December, just how significant of an incremental opportunity is that within both your existing customers that have you know operations over there, but also from a new customer acquisition standpoint from you know companies maybe you know headquartered over there? Just how big of a Yeah Incremental driver is that? Yeah, it's definitely a significant opportunity for us, you know, both to access that region in a better way, but also in particular because we were finding a really significant portion of our customer base has manufacturing or other operations there, and they effectively must have coverage in that environment. You know, I talked a little bit about this everywhere value proposition, and it is true, right? It's actually not great for us if we cover almost everywhere. We wanna be all the way everywhere. That was one that was kind of the holdout that a lot of customers really needed something for. You know, we could always tell them, "Oh, go run Confluent Platform yourself," but it's not that compelling if you're able to get, you know, managed offering for everything else. This, you know, kind of helps close that gap. Great. Thanks, guys. The last question comes from Patrick Colville with Deutsche Bank. Hey, thank you so much for taking the time and taking my question, and congrats on a phenomenal inaugural year. Can I just ask about Platform versus Cloud? I mean, the incoming that I've been getting from investors is that, you know, Platform this quarter was very strong, but Cloud was maybe a little bit light versus expectations. My question is, you know, can you just help me understand the consumption dynamic of that Cloud piece? You know, are there any metrics you can share? Is it the bulk of it consumption? Just help me understand that component, if possible. Yeah. Yeah. Steffan touched on this a little bit in the previous answer, but there is a bit of a dynamic here. So when you think about new revenue coming in, that's, you know, in cloud, our revenue is usage-based. And so there has to be some new software project typically that launches that's now consuming more data or using our offering or processing more streams to drive that additional consumption. So you do see a bit of a slowdown through the holidays for a variety of reasons, not least of which a lot of the software engineers are on vacation, right? You do see a little bit of the opposite on Confluent Platform, where because there isn't a, you know, it's a software offering, there's an upfront component of that, and the rest is kind of, you know, over the course of the subscription. You would see that because of the Q4 dynamic, where there tend to be more deals that close there, you would see that kind of being a little bit seasonally up in Q4. Hopefully that makes sense and, you know, sheds at least a little light on the dynamic. Just to add a couple of other things. One is you look at the comments we made around cloud being greater than 50% of new ACV in the quarter, which is a milestone for the company, and you look at the growth rate of our total RPO and current RPO. Both of those accelerated very well in the quarter. There's a lot of that is Confluent Cloud related. We feel really good about the quarter. We feel really good about the 211% year-over-year growth rate off of an incredibly tough comp a year ago. A year ago, you know, it's triple-digit growth. To grow 211%, we feel really good about. Great. Thank you so much. That's a very, very clear answer. Great. This concludes the Q&A portion of our call. Jay, back to you for closing remarks. Well, that concludes the call. Our success and momentum since our IPO would not be possible without all the hard work and the dedication of our team, our investors, and especially our customers. Thank you all for being part of the journey. The recording has stopped.