Transcript: Dynatrace Q1 2027 Earnings Conference Call

Dynatrace (NYSE: DT ) reported first-quarter financial results on Wednesday. The transcript from the company's first-quarter earnings call has been provided below. This transcript is brought to you APIs. For real-time access to our entire catalog, please visit for a consultation.

Access the full call at Summary Dynatrace Inc. reported strong financial performance in Q1 FY27, with total ARR growing 17% year-over-year and net new ARR reaching $85 million, marking 66% and 41% growth respectively on constant currency terms. The company exceeded its revenue and subscription revenue guidance, achieving a non-GAAP operating margin of 29%, driven by robust enterprise demand for end-to-end observability and AI-driven solutions. Strategic initiatives include expanding AI observability capabilities, launching the Bluebox offering for AI-first development teams, and leveraging recent acquisitions like Bindplane to enhance interoperability and data ingestion.

Dynatrace projects the AI observability market to exceed $10 billion by 2030, growing at more than 50% annually, with AI contributing to increased platform consumption and new monetization opportunities. 5% and raising full-year revenue and EPS guidance despite foreign exchange headwinds. Operational highlights included significant customer wins in various sectors, with notable expansions and new logo acquisitions contributing to growth. The company announced that CFO Jim Benson plans to retire by the end of the fiscal year, initiating a search for his successor.

Full Transcript OPERATOR Greetings, and welcome to the Dynatrace first quarter fiscal 2027 earnings conference 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 during the conference, please press star zero on your telephone keypad.

Please note this conference is being recorded. I will now turn the conference over to Noelle Farris, VP of Investor Relations. Thank you. You may begin.

Noelle Farris, VP of Investor Relations Good morning, and thank you for joining Dynatrace's first quarter fiscal 2027 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 Annual Report on Form 10-K and subsequent Quarterly Reports on Form 10—Q.

The forward-looking statements contained in this call represent the company's views on August 5, 2026. 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 year over year and 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. Rick McConnell, CEO Thanks, Noelle, and good morning everyone. Thank you for joining us today.

On our last earnings call in May, we expressed confidence that the growth drivers we put in place would drive a year of ARR acceleration in fiscal 2027. The strength we saw across the business in Q1 reinforces our conviction and ability to deliver this outcome. Here are a few of the noteworthy highlights from the quarter: total ARR grew 17%. Net new ARR was $85 million, growing 66% and 41%.

Organically, we achieved record new logo growth of more than 160%. Both total and subscription revenue exceeded the high end of our guidance, and we delivered a non-GAAP operating margin of 29%, reflecting the disciplined investment approach you've come to expect from us. Q1 strength reflected healthy enterprise demand for end-to-end observability, stronger execution, and growing complexity across customer environments. We are seeing AI contribute in three ways, which I will expand upon shortly: increasing consumption across our platform, creating demand for new AI observability capabilities, and directly monetizing agent usage.

This Q1 performance reflects both the significant market opportunity and our strong execution. To begin the fiscal year morning, I'd like to discuss the observability market, why we believe Dynatrace is built for an AI-first world, and how we expect to drive incremental AI monetization. The observability market has entered a new era. Software that once took months to build now ships in days.

AI agents are taking autonomous action across infrastructure and enterprise. Customers are now deploying AI rapidly, not because every risk has been resolved, but because standing still means falling behind. In this environment, unified observability matters more than ever. Systems are more interconnected, more autonomous, and more difficult to manage manually than ever before.

The enterprises winning in this environment are the ones that can keep complex, fast-moving systems working reliably and quickly understand when they are not. Additionally, AI workloads do not simply add volume. They behave differently. They can operate perfectly and still produce incorrect results.

That's a problem observability has never had to solve before, and addressing it represents a significant emerging opportunity. We estimate the AI observability total addressable market will exceed $10 billion by 2030, growing at more than 50% annually. We see AI observability as the next logical evolution of the broader observability market, and that evolution is already underway. What this means in practice is that observability in the age of AI has to answer far more questions than ever before.

And while the majority of enterprises are still in early phases of their AI journey, the requirements are evolving quickly. Let me walk through three of the questions that matter most today in an AI-first world. The first: Is it working? Are applications, infrastructure, and systems working as intended?

This question is about business resilience and is the same question we ask of traditional workloads. Second is new: Is it accurate? More specifically, is the AI model delivering output that can be trusted and relied upon with confidence? Answering this means evaluating AI systems for accuracy and intended behavior.

Determining whether an AI system behaves as intended before it ships is emerging as one of the most important aspects of observability. Third, are my agentic systems delivering the outcomes they were built for? Enterprises are deploying agents to build software at a pace that wasn't possible before. The advantage goes to those who can accelerate the full lifecycle and trust the results.

Code that's built well ships safely and runs reliably. The last question is where our newest offering, Bluebox, comes in. Built for AI-first teams, Bluebox helps development teams and their coding agents bring software into production in a way that customers can trust. It closes the loop between building and running.

It gives coding agents live context from running systems before a change is released. And once that change is live, its agentic SRE capability finds root cause and returns an evidence-backed fix with the developer in control across the entire AI delivery life cycle. This is the moment for which Dynatrace was built. With AI agents increasingly acting alongside humans across development and operations, both need a common source of trusted context.

Dynatrace provides that through Grail and Smartscape, giving agents and teams a unified understanding of system relationships and behavior. Dynatrace Intelligence turns that understanding into action, combining deterministic and agentic AI to deliver the precise causal insight that lets both people and agents act with confidence. These core differentiators give customers one operating foundation across both human and autonomous workflows. Our platform has a distinct advantage with this depth of insight, and as agents become a larger part of enterprise operations, that distinction becomes even more important.

Additionally, we are purposefully building for an open, interoperable ecosystem. Our newly acquired Bindplane supports the open standard for OpenTelemetry data collection. DevCycle, acquired earlier this year, supports the open standard for feature flags. These acquisitions aren't coincidental.

They reflect a deliberate commitment to open standards and interoperability. Customers are not locked into proprietary pipelines. Our platform is built to work alongside the tools enterprises already use, including partners such as ServiceNow, and to operate natively in MCP environments. As the AI ecosystem evolves, we believe openness is a competitive advantage.

It is one of the reasons enterprises trust Dynatrace as the intelligent foundation for AI-powered businesses—both powered by AI and built for AI. Our unified architecture becomes more valuable as AI increases complexity, and that growing value is reflected in higher consumption, broader platform adoption, and the following three new monetization opportunities. First, AI workloads are similar to core observability workloads in that they leverage the same types of data such as logs, traces, and metrics. But AI workloads generate dramatically more telemetry than the systems that came before them.

This is one of the reasons why log management remains our fastest growing product category, with consumption nearly doubling since surpassing the $100 million milestone just two quarters ago. Bindplane facilitates easier data ingestion, and it is already performing ahead of plan. Second, as I mentioned earlier, AI observability is an incremental monetization driver. It increases consumption of the platform as it validates whether the AI workloads are producing accurate results, behaving as intended, and operating safely and efficiently.

This is the newest capability of the platform, and adoption is expanding quickly. Third, beyond AI workloads and the data they generate, we monetize our own AI and agents. Every time a customer uses Dynatrace Intelligence to get answers through AI function calls or MCP integrations, or when one of our agents, like the SRE or Assist agent, takes autonomous action to resolve an issue, it drives DPS usage. As agents increasingly become consumers of observability, this represents a growing opportunity that didn't exist two years ago.

Today, more than 1,000 customers use Dynatrace to observe AI and LLM workloads in production, up from roughly 850 last quarter. And more than 800 are running operations autonomously with Dynatrace's agentic capabilities, up from roughly 500 last quarter. 5 times higher than that of non-AI cohort customers. Our platform integrates natively with Claude, ServiceNow, GitHub Copilot, Atlassian, and the major hyperscalers AWS, Azure, and GCP, enabling autonomous action across development and operations at scale.

Here are several examples of how customers are leveraging Dynatrace to advance their AI strategies and observability initiatives. In Q1, we signed a seven-figure ACV expansion deal, more than doubling ACV, with a top global financial institution. This customer is using Dynatrace to validate model consumption, control costs, and maintain full data lineage from prompt to response, helping it deploy AI with greater confidence while reducing compliance and audit risk. We secured a six-figure ACV expansion, also nearly doubling ACV, with a leading recreational vehicle retailer.

This customer used Dynatrace as their operational system of record while building a custom CRM application through AI-assisted development, generating approximately seven figures of savings and expanding usage of our platform. A leading digital insurance provider used Dynatrace AI observability to reduce onboarding time from days to minutes and identified an outdated model version that was driving unnecessary token consumption and costs. And finally, we secured an eight-figure ACV new logo win with one of Latin America's largest financial institutions in a highly competitive sales process.

The customer selected Dynatrace to consolidate a fragmented multi-vendor observability stack across a complex environment supporting mission-critical citizen-facing services. Our differentiation continues to be recognized by independent analysts. Gartner named Dynatrace a Leader in the Gartner Magic Quadrant for Observability Platforms for the 16th consecutive year. Gartner described Smartscape and Dynatrace Intelligence as the gold standard for real-time, high-fidelity dependency mapping to automate root cause with Dynatrace and third-party agents.

We believe this recognition validates both the strength of our architecture and our ability to help customers confidently scale AI and agentic workloads. Finally, as many of you have seen, Jim plans to retire from Dynatrace by the end of the fiscal year. We will conduct a thorough search for his successor over the coming months, and I am confident we will have a smooth transition. Jim has been an exceptional partner, playing a critical role in scaling the business, strengthening our financial profile, and positioning Dynatrace for its next phase of growth.

I am deeply grateful for his leadership and many contributions, and we will miss his valuable insights and guidance when he retires. To wrap up, Q1 was a tremendous start to FY27 and a powerful reflection of the momentum we are seeing across the business. Organizations are increasingly looking to consolidate on platforms that can help them manage growing complexity, unlock greater productivity, and realize the full potential of AI. As enterprises accelerate their AI initiatives, we believe Dynatrace is uniquely positioned to help them innovate faster, operate more efficiently, and maximize the return on their technology investments.

In an AI-first world, in which observability and autonomous operations become more critical day by day, we are more enthusiastic than ever about the opportunity. Jim, over to you. Jim Benson, CFO Thank you for the kind words, Rick, and good morning everyone. Q1 was an exceptional start to the fiscal year.

Once again, we exceeded the high end of all our top-line growth and profitability guidance metrics, fueled by record new logo ARR growth, expanding traction in LOGS, and continued robust consumption of the platform. These results reflect broad-based momentum across the business and reinforce our conviction that we are on the path to ARR acceleration this fiscal year. Let me review our first quarter results in more detail. Unless otherwise noted, all growth rates are year over year and in constant currency, starting with ARR.

14 billion, up 17% year over year. Q1 net new ARR was $85 million, adjusted for foreign exchange movements, growing 66% from a strong first quarter last year. Excluding the $13 million ARR contribution from our buying plan acquisition, Q1 net new ARR was $73 million, or 41% organic growth. This strong performance was driven primarily by record new logo ARR growth and our continued success in winning large end-to-end platform consolidation opportunities, including an eight-figure ACV land.

The maturation of our go-to-market transformation, which began in fiscal 25, is clearly reflected in improving net new ARR productivity. To help illustrate the momentum in the business, we believe trailing twelve-month net new ARR is a useful metric because it smooths the quarter-to-quarter impact of large enterprise transactions. Viewed through that lens, we have now delivered four consecutive quarters of acceleration in trailing twelve-month organic net new ARR growth. Growth reached 17% on an organic basis in Q1, up from 12% in Q4.

Demonstrating continued momentum, in Q1 we added 122 new logos to the Dynatrace platform. The average land size continues to build and was nearly $285,000, contributing to record new logo ARR growth of more than 160%. We remain focused on landing with high-quality customers with strong expansion potential. Our value proposition continues to resonate with enterprise customers that are outgrowing DIY or commercial point solutions, and AI-driven complexity is only increasing the need for a unified platform.

Customers are seeking business value through tool consolidation and opt for Dynatrace for the depth, breadth, and automation of our unified AI-powered observability platform. Simply put, we believe the Dynatrace platform was built for the AI era. Once customers experience the benefits of the Dynatrace platform, they often expand quickly. Average ARR per customer continues to increase and is now well over $500,000, reflecting broader adoption and the value we deliver.

As we have shared in the past, given the significant cross-sell and upsell opportunities within our enterprise customer base, we believe the average ARR per customer can exceed $1 million or more over the medium to long term. Gross retention rate in Q1 remained in the mid-90s, underscoring the strategic importance of Dynatrace as a mission-critical component of our customers’ operations. Net retention rate, or NRR, was 110% on a trailing 12-month basis.