Dynatrace NYSE: DT CEO Rick McConnell said the observability market is entering a new phase as artificial intelligence workloads increase the need for monitoring, analysis and automation across enterprise technology environments.
Speaking at the KeyBank Technology Leadership Forum, McConnell said AI is not affecting all software categories equally, but he views observability as an “AI winner” because AI workloads require more oversight rather than less. Traditional observability has focused on business resilience, including whether software is running and meeting expected requirements. AI observability adds questions around whether an AI system’s outputs are accurate and based on the right information, he said.
AI Raises the Importance of End-to-End Observability
McConnell said application performance management, or APM, is particularly relevant for AI observability because tracing is important for use cases such as large-language-model evaluation and experimentation. However, he said organizations also need a broader, integrated platform that combines traces, metrics, logs, real-user data and security-related information.
“The way to have confidence in your answers is by having the collection of all these domains using all data types,” McConnell said. He argued that enterprises can no longer effectively rely on separate vendors for APM, infrastructure monitoring, user monitoring, security and log management.
According to McConnell, integrated data can support increasingly automated operations. He described a process in which the Dynatrace platform identifies an incident, analyzes the cause, determines a triage plan and uses agents to execute actions. Organizations may choose to retain human review before agents act, he said.
McConnell added that the eventual goal is autonomous operations, particularly as AI agents are increasingly used to write code and enterprises manage a growing number of applications and infrastructure components.
Company Cites ARR, Log and Customer Acquisition Momentum
McConnell characterized Dynatrace’s first-quarter performance as strong across the business. He said the company reported 41% organic net-new annual recurring revenue, or ARR, growth, exceeding the high end of its guidance across metrics.
While he cautioned that the company does not expect to deliver more than 40% net-new ARR growth every quarter, McConnell said the quarter supported Dynatrace’s outlook for ARR reacceleration. He described fiscal 2026 as a year focused on stabilizing ARR growth and fiscal 2027 as a year aimed at reaccelerating it.
McConnell identified three themes behind the quarter’s results:
- Growing demand associated with AI workloads and AI-generated code.
- Rapid growth in log-management consumption.
- A record increase in new-logo ARR, which rose more than 160% year over year.
On logs, McConnell said Dynatrace had previously targeted $100 million in log consumption during fiscal 2026. The company reached that level a few quarters ago and has since surpassed $200 million in log consumption, meaning consumption doubled within two quarters.
He said customers are often considering Dynatrace for existing, rather than new, logging workloads. Cost is a major driver, according to McConnell, who said enterprises have raised concerns over rapidly rising log costs. He also cited Dynatrace’s Bindplane acquisition, which he said enables inbound log filtering and can reduce the volume of logs that must be ingested and stored.
Platform Subscription Model Supports Broader Adoption
McConnell said Dynatrace’s Platform Subscription, or DPS, has helped customers adopt the platform more broadly. Under the model, customers make an overall spending commitment and draw down that commitment based on their changing use of Dynatrace capabilities, rather than purchasing separate product-specific stock-keeping units.
DPS now represents 75% of Dynatrace ARR and is used by more than two-thirds of customers, McConnell said. He said the model can be particularly useful for customers whose usage varies by season, such as e-commerce companies that may need more observability during November and December.
As three-year DPS agreements come up for renewal, the company expects customer contract commitments to increasingly reflect consumption growth. McConnell said platform consumption continues to grow by more than 20%, compared with the company’s indicated 17% ARR growth inclusive of the Bindplane acquisition. He said the renewal cycle could support improved net revenue retention, particularly in the second half of the year.
Early AI Adoption Producing Higher Consumption
McConnell said AI deployment remains in the “early innings,” but Dynatrace is already observing AI workloads for more than 1,000 customers. The company has deployed Dynatrace agents for actions such as automatic remediation and triage at more than 800 customers, he said.
Customers using Dynatrace for AI-related workloads are consuming the platform at a rate roughly 1.5 times that of non-AI cohorts, McConnell said, partly because AI systems generate substantial telemetry data.
He said Dynatrace sees several potential AI-related monetization avenues, including increased platform consumption, AI-observability capabilities and charges associated with agent actions. However, McConnell said the company has not incorporated those incremental monetization layers into its guidance because it is still unclear how quickly they will develop.
McConnell estimated that AI observability represents a $10 billion incremental category within an approximately $80 billion overall observability market, adding that the AI-observability segment is growing at an estimated 40% to 50% rate.
About Dynatrace (NYSE:DT)
Dynatrace is a global software intelligence company specializing in application performance management (APM), cloud infrastructure monitoring, and digital experience management. Its flagship offering, the Dynatrace Software Intelligence Platform, leverages artificial intelligence to provide real-time observability across distributed environments, including on-premises data centers, private clouds, public clouds and hybrid deployments. Organizations rely on Dynatrace to detect anomalies, troubleshoot performance issues and optimize end-user experiences through automated root-cause analysis powered by the company's engine, Davis.
The Dynatrace platform comprises modules for full-stack application monitoring, digital experience monitoring, infrastructure monitoring and business analytics.
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