Thanks, Shane. Welcome, everyone, to our second quarter earnings call. Confluent delivered another strong quarter, exceeding the high end of our guidance on all metrics. Total revenue grew 58% year-over-year to $139 million. Confluent Cloud revenue grew 139% year-over-year and represented 34% of total revenue in the quarter. Confluent Cloud continues to increase as an overall mix of our business and is seeing rapid adoption across our customer base as reflected by strong consumption trends. We're especially proud of our performance given the uncertain macro environment we're currently operating in. I'll start by touching briefly on this topic, why Confluent continues to see strong demand despite economic headwinds. There are 2 reasons for this durability: First, our product sits in the operational stack, powering applications that directly serve critical business operations and real-time customer experiences. Given this criticality, it can't be switched off without a complete disruption to the operations of the business. Our 2022 state of data in motion report underscores this, finding that of the nearly 2,000 IT and engineering leaders surveyed, more than 80% said real-time data streams are critical to building responsive business processes and rich customer experiences. Second, one of the key value propositions of a managed cloud service such as Confluent Cloud is cost savings. Using Confluent Cloud has significant TCO advantages compared to trying to build out internal teams of engineers to attempt to build internal services around open source. SaaS Institute is a customer that perfectly illustrates these dynamics. SaaS is a marketing analytics powerhouse helping more than 80,000 businesses like Discover, Honda, Levi's and Nestle transform data into real-world intelligence, making their marketing campaigns more targeted, more personal and more relevant. SAS initially built its real-time data platform on open source Kafka, but they soon ran into scalability issues, from self-supporting open source -- that made it difficult to adjust to changing demand. Plus, the operational overhead and complexity were driving significant costs. So SAS turned to Confluent for a complete data streaming platform that scales both compute and storage on demand even amid unpredictable ebbs and flows of traffic. With Confluent now as the backbone of their next-generation Customer Intelligence 360 platform, SAS can easily stitch together data from multiple sources to find and act on fresh and timely insights for their customers. Key to this ability to serve mission-critical use cases and to help customers recognize the cost and agility advantages I described are the underlying capabilities that Confluent Cloud provides. Kafka has become ubiquitous and is the de facto standard for data in motion used by over 70% of the Fortune 500. But Confluent Cloud is not just a matter of putting Kafka in the cloud. In building Confluent Cloud, we rethought virtually every layer of the stack from how data is routed over the network, how it is processed, where it is placed and how it is stored. This deep engineering investment is necessary to provide a truly cloud-native service that can meet the needs of the most mission-critical use cases and can help customers truly step back from the operations of the service and focus on their applications. To achieve this, over the last 5 years, we've poured more than 3 million engineering hours into Confluent Cloud. Today, it represents a 10x better Kafka service with a deep competitive moat of hard technology. By making a service that is 10x better than open source Kafka, Confluent lets organizations avoid investments in low-level operations, monitoring and scaling and be able to instead rely on a service that can scale elastically with their needs. This is what drives the substantial cost savings customers see when they adopt our service. As we shared last quarter, a recent Forrester study identified TCO savings of more than $2.5 million for businesses that use Confluent, translating to an ROI of 257% in less than 6 months. Another example that demonstrates both the mission-critical nature of our use case as well as the economic value of Confluent Cloud is ETC. A leading electronic toll collection company. To support next-generation congestion management services, ETC collects real-time sensor input for millions of cars and IoT devices across city transportation corridors, totaling 2 billion toll transactions per year. By collecting and processing this data continuously and in real time with Kafka, ETC produced the first truly predictive dynamic pricing algorithm in the industry. But as their use of Kafka skyrocketed from onboarding new customers, increased traffic congestion and expanding toll and smart mobility projects, so did their total cost of operating and maintaining open source Kafka. After conducting an internal TCO analysis, ETC moved to a fully managed Kafka on Confluent Cloud. By making the move to Confluent Cloud, ETC saved an average of 20% on infrastructure costs, significantly reduced their downtime risk and was able to reallocate about 50% of their engineering and development talent that was dedicated to managing Kafka to more strategic projects that accelerate innovation. Our relationship across the software and data landscape remain core to our everywhere pillar of differentiation and are a key part of our go-to-market. We made a few notable announcements on the partnership front that deepened our key partner relationships. First, we are thrilled to announce the launch of a Confluent cloud reseller program. Organizations can accelerate their adoption of data in motion by purchasing Confluent Cloud directly from the consulting partners they already work with who know their business and can offer localized support. To start this program, we expanded our strategic collaboration agreement with AWS by joining the marketplace channel program, consulting partner private offers. Now we can work with 17 leading data streaming partners, including slower, mega zone and SBA to make it easier for our customers to unlock the full value of data streaming throughout their business. This quarter, we were also recognized by both Microsoft and MongoDB as one of their top partners for 2022. We're incredibly proud and thankful for our strong partnerships with cloud service providers and technology partners. I'd also like to spend a few minutes on work we're doing to accelerate usage for customers at the early stages of their data in motion journey. We've previously discussed our customer growth go-to-market model that builds a product-led consumption-oriented journey down the data and motion adoption path. The early stage of this journey is particularly critical for customer acquisition and for making Confluent Cloud the default starting point for developers. This early stage of adoption often starts with developers experimenting with pilots and proof of concepts or simply learning the new technology. At this stage, it's critical for the onboarding process to be low friction. So a developer can instantly gain full access to the power of our platform with minimal disruption. To make this process even easier for developers, I'm very pleased that towards the end of our first quarter, we removed the requirement of entering credit card information for the free trial of our product. This paywall removal is a strategic move that aligns well with our customer growth go-to-market model, allowing us to reduce the friction for developers to test our product, grow usage and progress to the production stage. And we are already seeing strong returns at the top of our funnel, as evidenced by the accelerating growth in Q2 sign-ups, which are up more than 130% year-over-year and up more than 50% sequentially. This paywall removal has been incredibly successful in increasing sign-ups, but it has also created some short-term noise in our total customer count metric. Users who would have incurred small amounts of spend had been previously counted as customers in their initial trial phase will now show up as just sign-ups, not paying customers, which impacts our customer count growth in Q2. This means that the change has eliminated a large chunk of preproduction customers paying us an average of less than a few hundred dollars per quarter, creating a reset of our pay-as-you-go customer count. Reset of customer count aside, it's unquestionably the right strategy for our business as our customers can now test drive Confluent risk-free. And for us, the reduction in developer risk and friction drives easier land and ultimately more paying customers as the larger cohort of trials leads to sticky production applications that grow and expand at scale. And finally, I'd like to share that after a 4-year impactful run at Confluent, Ganesh Srinivasan will be stepping back from his role as Chief Product Officer. I will be acting as interim Chief Product Officer as we search for a new leader. Ganesh, we wish you all the best, and thank you for your many contributions. Thanks again for joining us today. We remain very confident in our market opportunity and positioning headed into the second half of the year. And we look forward to seeing many of you on the road in the coming months. including at Current, a new data streaming industry event we're hosting in October. With that, I'll turn the call over to Steffan to walk through the financials.