Blog | Prometheus

September 21, 2026 by Dhruv Ahuja (@dhruv-ahuja), Andrej Kiripolsky (@andrejkiri), Ana Muenz (@vampirarte), Arthur Silva Sens (@ArthurSens)
We ran a survey asking users of OpenTelemetry and Prometheus how they collect, process, and store metrics. The goal was to understand, with real usage data rather than assumptions, how far the ecosystem has moved and whether the interoperability still causes friction.
June 30, 2026 by Uzochukwu Winnie (@wineshuga)
I joined the LFX mentorship expecting to spend three months writing documentation. A few weeks later, I was deploying OpenTelemetry Collectors across AWS EC2 instances, debugging networking problems between machines, and trying to understand why a pipeline that looked healthy wasn't sending metrics.
I went from having zero knowledge about observability to building and troubleshooting systems. This made the LFX Mentorship one of the most effective and exciting learning experiences I've had in engineering. I was exposed to how systems behave in reality. That difference is what makes it one of the most effective ways to grow into cloud-native engineering.
April 22, 2026 by Arthur Silva Sens (@ArthurSens)
Prometheus documentation now includes a new Kapa.ai integration. This is available as part of the partnership between CNCF and Kapa.ai , which helps CNCF projects make their documentation and knowledge more accessible.
You can now use the Ask AI entry on prometheus.io to ask questions in natural language and get answers grounded in Prometheus documentation. For the Prometheus team, it is also a useful way to understand what people are trying to learn from the docs and where the docs still need work.
April 8, 2026 by Amy Super
Prometheus has always prioritized solving complex technical challenges to deliver a reliable, performant open-source monitoring system. Over time, however, users have expressed a variety of experience-related pain points. Those pain points range from onboarding and configuration to documentation, mental models, and interoperability across the ecosystem.
At PromCon 2025, a user research study was presented that highlighted several of these issues. Although the central area of investigation involved Prometheus and OpenTelemetry workflows, the broader takeaway was clear: Prometheus would benefit from a dedicated, ongoing effort to understand user needs and improve the overall user experience.
Recognizing this, the Prometheus team established a Working Group focused on improving user experience through design and user research. This group is meant to support all areas of Prometheus by bringing structured research, user insights, and usability perspectives into the community's development and decision-making processes.
March 5, 2026 by Ayoub Mrini (@machine424)
Do you find yourself constantly looking up the difference between container_memory_usage_bytes, container_memory_working_set_bytes, and container_memory_rss? Pick the wrong one and your memory limits lie to you, your benchmarks mislead you, and your container gets OOMKilled.
You're not alone. There is even a 9-year-old Kubernetes issue that captures the frustration of users.
The explanation is simple: RAM is not used in just one way. One of the easiest things to miss is the page cache semantics. For some containers, memory taken by page caching can make up most of the reported usage, even though that memory is largely reclaimable, creating surprising differences between those metrics.
February 14, 2026 by Bartłomiej Płotka (@bwplotka)
Over the last year, the Prometheus community has been working hard on several interesting and ambitious changes that previously would have been seen as controversial or not feasible. While there might be little visibility about those from the outside (e.g., it's not an OpenClaw Prometheus plugin, sorry 🙃), Prometheus developers are, organically, steering Prometheus into a certain, coherent future. Piece by piece, we unexpectedly get closer to goals we never dreamed we would achieve as an open-source project!
This post starts (hopefully!) as a series of blog posts that share a few ambitious shifts that might be exciting to new and existing Prometheus users and developers. In this post, I'd love to focus on the idea of native storage for the composite types which is tidying up a lot of challenges that piled up over time. Make sure to check the provided inlined links on how you can adopt some of those changes early or contribute!
December 16, 2025 by Arve Knudsen
Enriching metrics with metadata labels can be surprisingly tricky in Prometheus, even if you're a PromQL wiz! The PromQL join query traditionally used for this is inherently quite complex because it has to specify the labels to join on, the info metric to join with, and the labels to enrich with. The new, still experimental info() function, promises a simpler way, making label enrichment as simple as wrapping your query in a single function call.
In Prometheus 3.0, we introduced the info() function, a powerful new way to enrich your time series with labels from info metrics. What's special about info() versus the traditional join query technique is that it relieves you from having to specify identifying labels, which info metric(s) to join with, and the ("data" or "non-identifying") labels to enrich with. Note that "identifying labels" in this particular context refers to the set of labels that identify the info metrics in question, and are shared with associated non-info metrics. They are the labels you would join on in a Prometheus join query . Conceptually, they can be compared to foreign keys in relational databases.
Beyond the main functionality, info() also solves a subtle yet critical problem that has plagued join queries for years: The "churn problem" that causes queries to fail when non-identifying info metric labels change, combined with missing staleness marking (as is the case with OTLP ingestion).
Whether you're working with OpenTelemetry resource attributes, Kubernetes