Greetings. Welcome to Dynatrace's Fiscal Third Quarter 2025 Earnings Call. At this time, all participants are in a listen-only mode. A question-and-answer session will follow the formal presentation. If anyone should require operator assistance, please press star zero on your telephone keypad. As a reminder, this conference is being recorded. It is now my pleasure to introduce Noelle Faris, Vice President, Investor Relations. Thank you. You may begin.
Good morning, and thank you for joining Dynatrace's Third Quarter Fiscal 2025 Earnings Conference Call. Joining me today are Rick McConnell, Chief Executive Officer, and Jim Benson, Chief Financial Officer. Before we get started, please note that today's comments include forward-looking statements such as statements regarding revenue, earnings guidance, and economic conditions. Actual results may differ materially from our expectations due to a number of risks and uncertainties discussed in Dynatrace's SEC filings, including our most recent quarterly report on Form 10-Q that we filed earlier today. The forward-looking statements contained in this call represent the company's views on January 30th, 2025. We assume no obligation to update these statements as a result of new information, future events, or circumstances. Unless otherwise noted, the growth rates we discuss today are non-GAAP, reflecting constant currency growth, and per-share amounts are on a diluted basis.
We will also discuss other non-GAAP financial measures on today's call. To see reconciliations between non-GAAP and GAAP measures, please refer to today's earnings press release and supplemental presentation, which are both posted in the financial results section of our IR website. And with that, let me turn the call over to our Chief Executive Officer, Rick McConnell.
Thanks, Noelle, and good morning, everyone. Thank you for joining us for today's call. We're proud that Dynatrace once again outperformed our guidance across all top line and profitability metrics. It is a testament to the team's discipline execution, the strength of our AI-powered observability platform, and the significant business value we provide to our customers. In Q3, ARR grew 18% YoY . Subscription revenue increased 21% YoY , and trailing 12-month free cash flow margin was 25%. Jim will share more details about our Q3 performance and fiscal 2025 guidance in a moment. In the meantime, I'd like to discuss observability market tailwinds, our platform differentiation, core growth drivers, and customer wins. To begin, our conviction in the observability market opportunity continues to strengthen based on several factors. Cloud modernization drives observability demand and is evidenced by the now more than $220 billion in annualized hyperscale revenue.
Aggressive cloud expansion has, however, contributed to tool sprawl within organizations, resulting both in operational inefficiency and high cost. It's not uncommon for companies to have more than a dozen internal and external observability tools and aim to consolidate them into a more effective, unified, and lower-cost approach. The AI revolution adds another layer of complexity as organizations look to accelerate innovation, deliver better customer service, drive efficiency, and obtain a competitive advantage. Each of these market drivers is resulting in an explosion of data, a massive increase in its scale, and complexity that are simply untenable for organizations to manage as they have previously. As a result, the need for comprehensive end-to-end observability has become mandatory, especially for larger organizations.
We believe that an AI-powered observability platform with sophisticated analytic and automation capabilities is vital in providing the visibility needed for software to work perfectly, and customer feedback reflects just that. This leads me to our primary technology differentiators. The core of the Dynatrace platform is a massive parallel processing, highly performant data store called Grail that maintains all observability, security, and business data types: logs, metrics, traces, real user data, and importantly, business events, all in context. Grail then enables us to uniquely apply AI to analyze billions of interconnected data points in real time to deliver answers, not just data and not just dashboards. We then leverage our contextual analytics and AI insights to automate responses and to help avoid incidents. It is our contextual analytics, AI, and automation that differentiate us from our peers.
Our unified architecture has enabled us to deliver new observability and security capabilities that help customers adopt cloud and AI-native technologies with confidence. These include not only the inherent benefits of full-stack observability to help customers anticipate and resolve issues in complex environments, but also enrich business data with IT context to provide insights and recommendations for improved business outcomes. We have been introducing these and other new capabilities for SREs, platform engineers, and development teams to extend this differentiation to a broader array of end users. Next, I'd like to highlight four key growth drivers for Dynatrace. Let's start with AI. As I mentioned, AI is a huge market driver of data, and with our long history in AI, Dynatrace has a unique ability to leverage this opportunity. We parse it into two distinct buckets.
First is AI Ops, which includes the core AI capabilities we use to deliver observability, security, and automation to all customers. AI Ops is and has been foundational to the Dynatrace solution for many years, and we keep innovating to enable customers to move from visibility to automation. Our AI-powered observability platform enables customers to automatically detect problems, analyze them, and drive automatic remediation actions using an AI system that we believe is the most advanced in our space. We achieve this by leveraging multiple techniques, including causal, predictive, and generative AI, to rapidly assess billions of interconnected data points to identify, resolve, and prevent issues without tedious and error-prone manual overhead. The second AI driver for Dynatrace is the observability of AI workloads themselves. The secular innovation cycle around AI is being viewed as the biggest sea change ever in the technology landscape.
What started with GenAI has quickly evolved to Retrieval Augmented Generation, or RAG, inference AI, and more recently, agentic AI. As with Dynatrace itself, this evolution illustrates a migration from information and insights to automated response. With the rapid pace of cloud and AI-native innovation, enterprises need an observability solution that can adapt to those changes in real time. With the enormous processing power of Grail, we are uniquely positioned to enable enterprises to adopt GenAI and other AI technologies successfully. Dynatrace can analyze LLM model performance and behavior, safeguard the quality of application input and output to prevent LLM misuse, deliver multi-model tracing for end-to-end observability, predict changes in cost, and calculate the business benefit and ROI. We are already engaged with hundreds of customers in observing their GenAI initiatives.