Dynatrace is collaborating with Google and Microsoft on the OpenTelemetry project to shape the future of open standards-based observability.
To further advance the industry and extend the reach of its Software Intelligence Platform, Dynatrace is contributing transaction tracing knowhow and manpower to the project.
OpenTelemetry is focused on providing standardized transaction-level observability through the generation, collection, and description of telemetry data for distributed cloud-native systems. As OpenTelemetry becomes more widely adopted, it will serve as an additional data source that further extends the breadth of cloud observability, including expanding the broad reach of what the Dynatrace Software Intelligence Platform already automatically collects and ingests into Davis, its explainable AI engine.
“Our goal is to ensure ‘run the business’ software underpinning digital enterprises works perfectly, so we feel it’s important to contribute our expertise to this open source project to improve and advance observability in a broader manner,” said Alois Reitbauer, Chief Technical Strategist and Head of the Dynatrace Innovation Lab. “The OpenTelemetry initiative will enable developers of cloud-native applications to build standardized observability into their software. As this gains momentum, observability will be increasingly differentiated by what can be done with data, versus simply how much data can be collected. That’s why we’re excited for the day when OpenTelemetry is widely adopted, as it will increase the breadth of the data and scope of the cloud ecosystem that organizations can observe. As a result, our customers will benefit from richer insights and more actionable answers.”
Dynatrace is working with Microsoft, Google and others as a core contributor to OpenTelemetry, providing its technical knowhow, manpower, and code to equip the project with enterprise-grade capabilities, including:
- Higher-level instrumentation APIs: offering higher-fidelity tracing code to enable developers to quickly and easily build observability into their cloud-native applications and reduce the monitoring blind-spots as new methodologies and programming languages emerge.
- Integration of universal Trace Context: supporting the availability of transactional context across hybrid multi-clouds, ensuring organizations can more easily maintain end-to-end observability across their cloud-native ecosystems.
- Runtime management: helping organizations ensure the resources needed to gain observability into the individual components and software libraries underpinning their cloud-native applications are dynamically available.
“The ultimate goal of OpenTelemetry is to become the default way that developers and operators capture performance information from their services,” said Morgan McLean, Product Manager at Google. “We cannot reach that goal without the support of a strong ecosystem. We are thrilled Dynatrace is a core contributor to OpenTelemetry. The broader community will benefit from its nearly 15 years of experience in automated and distributed tracing for enterprises.”
Hong Gao, Group Program Manager at Microsoft Corp. said, “We had a highly productive collaboration with Dynatrace on the W3C Trace Context standard, and we look forward to working together on advancing OpenTelemetry for developers.”
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...