The Cloud Native Computing Foundation® (CNCF®), which builds sustainable ecosystems for cloud native software, announced the graduation of OpenTelemetry, a vendor-neutral, open source observability framework designed to standardize the collection, processing and exporting of telemetry data—specifically metrics, logs and traces.
“As organizations increasingly scale AI and cloud native workloads, real time observability is critical for operational success,” said Chris Aniszczyk, CTO, CNCF. “OpenTelemetry’s graduation solidifies it as the essential, unified observability standard, providing the consistent visibility required to understand and oversee complex systems. Since the project’s inception, it has been incredible to witness the sheer growth and adoption OpenTelemetry has had in the cloud native community and beyond. The project creators, maintainers and community members should all be proud of this milestone.”
Formed in 2019 through the assistance of CNCF as a merger between OpenTracing and OpenCensus, OpenTelemetry (OTel) was created to eliminate a community split between the two overlapping projects. This helped solve tool fragmentation by providing a single set of APIs, SDKs, Collector agent, and semantic conventions, thus allowing organizations to switch observability backends without re-instrumenting their entire codebase.
In the seven years since its creation, OpenTelemetry has achieved the second-highest project velocity among over 240 projects in the cloud native ecosystem, second only to Kubernetes, and is widely regarded as the “de facto” standard for open source observability. OpenTelemetry’s rise in CNCF’s project velocity underscores the project’s growth trajectory and how deeply the technology resonates with developers and end users. Today, the project has grown to include over 12,000 contributors from over 2,800 companies and hundreds of maintainers across various language-specific Special Interest Groups (SIGs).
“OpenTelemetry’s graduation is the result of decades of collective effort from individuals, companies, and cloud native practitioners to make observability a built-in part of software,” said Austin Parker, OpenTelemetry governance committee and director of AI strategy, honeycomb.io. “When we launched this project, none of us expected that it would reach this level of popularity and impact. I’m incredibly thankful and indebted to our maintainers and contributors who helped get us to this point as well as the many individuals in the CNCF who have been a part of this journey.”
The project’s widespread adoption is gaining new interest as a layer to observe performance, reliability, accuracy and trustworthiness in AI workloads. In the past twelve months, the OpenTelemetry JavaScript API package was downloaded more than 1.36 billion times and the OpenTelemetry Python API package surpassed 1.3 billion downloads, with both API packages setting new monthly download records in April 2026. Organizations such as Alibaba, Anthropic, Bloomberg, Capital One, eBay, FICO Software, Heroku and others rely on OpenTelemetry to monitor and secure their systems.
OpenTelemetry continues to focus on its production readiness by recently adding support for new languages such as Kotlin and also promoting Profiles, now officially in alpha. It deeply integrates into the broader CNCF observability ecosystem and works alongside Kubernetes, Fluentd, Jaeger and Prometheus.
To officially achieve graduation, OpenTelemetry successfully engaged in a third-party independent security audit and reviews for core components such as the OpenTelemetry Collector, along with a formal governance review to confirm maturity. The project has also incorporated community feedback into updates to improve its production readiness.
Hot Topic
The Latest
Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...
For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...
Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...
Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...
For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...
New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...
Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...
In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ...
In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...
When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...