“Dynatrace's consistent execution gives us the confidence to raise our ARR, revenue and operating income outlook for the full year.”

In context

“Rick McConnell (CEO): Thanks, Noelle, and good morning, everyone. Thank you for joining today's call. Dynatrace delivered very strong second quarter fiscal 2026 results, exceeding our guidance across every metric. ARR grew 16%. Subscription revenue grew 17% and pretax free cash flow was 32% of revenue on a trailing 12-month basis. This overachievement in performance was due to successful execution of our strategy to capture the growing demand for end-to-end observability and large-scale multi-cloud tool consolidations, including ongoing growth in our logs business. Dynatrace's consistent execution gives us the confidence to raise our ARR, revenue and operating income outlook for the full year. Jim will share more details about our Q2 financial performance and guidance in a moment. In the meantime, I'd like to devote my remarks to why we believe AI-powered observability is mission-critical to software reliability and performance, especially in an evolving agentic world. And I will also provide an update on our key growth drivers. To start, the Dynatrace platform has evolved through multiple phases from reactive operations to automated root cause to now preventive operations. Our vision has been consistent over the past years to enable a world in which software works perfectly. By definition, that means that software must always be available. And when issues do occur, the software must self-heal. Preventive operations is about anticipating and taking action on issues before they become end user impacting. Customers are increasingly seeking not just answers followed by manual resolution, but rather answer-driven automation to deliver and operate software that works optimally. The Dynatrace third-generation platform was built from the ground up to handle precisely the level of complexity and scale of modern cloud and AI native environments, including the following core elements. Grail, our massively parallel processing data lake house, is capable of analyzing billions of interconnected data points in near real time to deliver comprehensive situational awareness. Smartscape provides deep contextual insights of topology and metadata through a directed knowledge graph. Davis delivers reliable, causal and predictive AI insights to produce deterministic answers. Davis Copilot automatically generates remediation proposals. and automation engine helps orchestrate and manage intelligent automated responses across the digital ecosystem. These technologies by being part of a fully unified platform rather than a series of point products with fragmented data stores enable true end-to-end observability, which is crucial to delivering accurate analytics and recommendations. In this way, our AI-powered platform is enabling the next phase of observability for Dynatrace, which is autonomous operations. In this business transformational phase, we take preventive operations to the next level by leveraging an ecosystem of agents, both from Dynatrace and third parties to take action to maintain software reliability, security and performance. It's about deploying intelligence that enables self-healing systems to keep software operational and performant with less human intervention. Moreover, worldwide spending on AI is forecast to be nearly $1.5 trillion in 2025 according to Gartner. As organizations broadly adopt agentic AI themselves, complexity will grow further, driving even greater need for a more scalable autonomous approach. We see Dynatrace and the evolution of observability becoming a bridge to the agentic world for enterprises. As stated perhaps most succinctly, we see Dynatrace as the AI-powered observability platform for autonomous operations. With this evolution, Dynatrace will be able to orchestrate and supervise both internal and external AI agents to auto prevent, auto remediate and auto optimize. We believe that Dynatrace is unique in our ability to deliver such an observability environment. One of our superpowers lies in our ability to pinpoint the so-called needle in the haystack in understanding software availability and performance. This has always been Dynatrace's biggest differentiator. And organizations will only allow autonomous action if it's based on precise, reliable answers, not loosely correlated data points. We like to think of this as answers, not guesses. Based on this deterministic knowledge, we can then confidently conduct agentic platform-based orchestration through both Dynatrace and third-party agents to take action. In order for an autonomous approach to be effective, it has to be built on a foundation of genuine end-to-end observability that provides deep analytics and insights, ultimately enabling an automated response. Our ability to analyze all observability data types, logs, traces, metrics, real user data, topology and even business events in context is essential for generating the most accurate and trustworthy answers. Additionally, the ability to oversee all domains, including infrastructure, apps, log management, user experience, application security and business observability provides the most comprehensive perspective of an organization's IT ecosystem. Whereas metrics and logs are often the data types of choice for infrastructure management, faces a long-time strength of Dynatrace become increasingly important for end-to-end inspection of agentic systems. Combination of full stack visibility and domain breadth allows customers to operate more efficiently, reduce overall costs and increase productivity as well as the pace of innovation. Perhaps most importantly, though, we believe these elements together yield superior outcomes. And customers are rapidly extending these outcomes beyond technical analytics of software performance into true business observability. There's also a vastly growing demand for organizations needing to observe AI native workloads. Customers adopting agentic AI will need to understand the complex interactions among agents and know exactly what to do when something unpredictable happens, including the avoidance of hallucinations. In order to have that level of visibility, all telemetry, especially traces and logs, must be captured, enriched with context and analyzed in real time at massive scale to prevent or instantly remediate issues. We are enabling AI to observe AI workloads through deep end-to-end observability. In sum, Dynatrace is rapidly progressing toward a future where our AI-powered platform doesn't just observe, but empowers organizations through knowledge, reason and action. This is why organizations that are leading the evolution of AI are partnering with Dynatrace as a foundation for smarter, faster and more reliable IT operations. So let me now highlight some recent developments with third parties to help bring autonomous operations to reality. Last Monday, Dynatrace and ServiceNow co-announced a multiyear strategic collaboration to advance autonomous IT operations and scale intelligent automation for joint enterprise customers. We are bringing together Dynatrace's AI-powered observability platform with ServiceNow's AI platform for business transformation to provide proactive self-healing IT environments. This partnership enables IT management and operations with real-time trustworthy autonomous actions across the software delivery life cycle. We also announced our integration with Atlassian to help customers fully understand issues and act quickly by embedding real-time production insights directly into incident management processes. Automatically tying incidents to root cause empowers organizations to operate more efficiently and proactively in managing complex digital ecosystems. And finally, we joined GitHub's Model Context Protocol Registry. This integration helps speed up debugging efforts during development and leverages Dynatrace observed production insights to increase agentic software improvements. This also further enables us to extend left to reach cloud and AI native development and platform engineering teams. I'd like to turn next to an update on 4 key growth drivers for our business, all of which continue to trend positively. First is the massive opportunity that we continue to see in log management. We believe the logs market remains ripe for disruption given the rising cost of legacy solutions that offer little to no expansion in business value. As we have stated in the past, we have taken a very different approach to logs. Traditionally, logs were separated from other observability data types. Instead, Dynatrace provides a unified data model inclusive of logs, allowing for cross-data analytics without manual stitching, resulting in faster root cause analysis and more accurate observability insights. Log management is our fastest-growing product category and is rapidly approaching $100 million in annualized consumption, continuing to grow more than 100% year-over-year. In addition, as more customers look to migrate their existing logs to Dynatrace, we're investing to increase the speed of those migrations. Last month, we announced a partnership with Crest Data Systems to deliver a seamless automated migration experience for customers moving to the Dynatrace platform. This enabled us, for example, to meet an aggressive timeline for a global financial services company by automating 70% of their dashboard migrations. Second, the investments we made last year to align our sales coverage around strategic accounts pipeline and partners continue to pay off. Our 4-quarter pipeline for strategic accounts is up 45% versus last year. Bookings through strategic GSI partners doubled year-over-year. And we saw a 53% increase in Q2 ACV from 7-figure deals compared to last year. Here are just a few examples of large wins in the quarter. An AI native revenue intelligence company and a new logo selected Dynatrace to be their end-to-end business solution for mission-critical workloads, displacing multiple tools. Our biggest new logo deal in APAC is one of Japan's largest banks. Fragmented tools and the complexity of their architecture were making it difficult for them to reduce mean time to resolution. With Dynatrace, they will now have an end-to-end view of their ecosystem to resolve issues more quickly. A major U.S. airline expanded its existing relationship with us 18 months after adopting Dynatrace to further consolidate tools, including logs after seeing significant improvement in incident resolution and the benefits of end-to-end observability. A third growth driver is the Dynatrace Platform Subscription licensing model, or DPS. We reached a major milestone in the second quarter with 50% of our customers and 70% of our ARR now utilizing DPS. When we launched DPS over 2 years ago, our expectation was that customers with full access to the platform would leverage more capabilities and extend Dynatrace more broadly into their IT environment. This thesis has played out with DPS customers adopting 2x the number of capabilities and at nearly double the consumption growth rates of those on a SKU-based model. And finally, overall platform consumption is a strong indicator of future expansions and is the primary compensation metric for our customer success team. Total Q2 consumption growth was more than 20% and continues to outpace subscription revenue growth. To wrap up, we are pleased to have delivered a strong first half of the fiscal year. The observability market opportunity is more critical than ever given the rapid evolution of cloud and AI native workloads. We have a differentiated AI-powered platform that is enabling autonomous operations in an evolving agentic AI world. We deliver significant customer value driving accelerating platform consumption. We continue to see momentum in our core growth drivers. And we have a compelling business model, which has enabled us to deliver a sustained balance of growth and profitability. Jim, over to you.”