The Cloud Native Computing Foundation (CNCF) today announced that the open source OpenTelemetry (OTel) project has officially graduated a little more than seven years after its initial adoption.
Announced at the Observability North America Summit, OpenTelemetry was first donated to the CNCF in 2019 following the merger of separate OpenTracing and OpenCensus projects that sought to create an open source alternative to instrumenting code. Since then the project has expanded to collect logs, metrics, traces and, most recently, profiles that can be used to provide granular, time-based views of resource consumption and code execution.
OTel is now being more broadly used to collect telemetry data not just from applications, but also from IT infrastructure and security tools.
CNCF CTO Chris Aniszczyk said attaining graduate status provides yet another indication that OTel has become a de facto standard for collecting telemetry data.
While most organizations are still a long way from unifying the management of all that telemetry data, OTel has created a unique opportunity to further centralize the management of IT operations, noted Aniszczyk.
Additionally, OTel will play a major role in instrumenting artificial intelligence (AI) agents that will soon be generating massive amounts of telemetry data, he added.
Many organizations are also looking to Extended Berkeley Packet Filter (eBPF) technologies embedded in the Linux kernel to provide another source of telemetry data, which will ultimately be exposed in an OTel format, noted Aniszczyk.
There is, of course, still work to be done to make OTel simpler to deploy. Much of that work, however, is being assumed by the providers of OTel distributions that have a long history of deploying telemetry data collectors, added Aniszczyk.
Mitch Ashley, vice president and practice lead of software lifecycle engineering at the Futurum Group, said regardless of how OTel is adopted there is now a de facto standard for collecting telemetry data just as agentic AI applications are about to generate orders of magnitude more signal than previous generations of applications. OTel will help prevent fragmentation when volume and signal types are expanding, he added.
It’s not clear at what rate IT teams are moving past traditional monitoring of pre-defined metrics to adopt observability platforms that make it easier to analyze logs, traces and metrics to discover the root cause of a specific application issue. However, a recent Futurum Group survey finds well over a third (36%) plan on spending more than $1 million on observability in 2026, with 7% planning to spend in excess of $5 million.
As application environments continue to become more complex, the one certain thing is existing monitoring tools are no longer enough. DevOps teams need to be able to determine the dependencies that exist between components and services to improve overall reliability. Otherwise, it’s only a matter of time before one or more preventable issues adversely impact application performance or, worse yet, make applications unavailable for reasons that, in the final analysis, could have been easily avoided.