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By Marko Bachvarovski
If you’ve built your telemetry pipelines around OpenTelemetry Collectors, you’ve already invested in a collector distribution, YAML configuration, and a deployment model that fits your infrastructure. As that deployment grows, managing it means keeping shared configuration consistent, accommodating different workloads, and understanding whether your collectors are healthy. Fleet Management in Grafana Cloud brings those tasks together in one place.
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By Virginia Cepeda
As your use of Grafana Cloud Synthetic Monitoring grows, so does the number of checks you need to manage across services, environments, and teams. Eventually, a single flat list of checks becomes difficult to navigate, and even simple questions get harder to answer: Which checks belong to the payments team? Can I disable everything in staging during a maintenance window? Who should be able to edit the checks for this service?
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By Tiffany Jernigan
Building on the major release of Tempo 3.0, Tempo 3.1 is here, delivering community-contributed Kafka client improvements, query-based trace redaction, sampling-aware TraceQL metrics, and more. Together, the updates in 3.1 make it easier to operate Tempo, get accurate insights from your trace data, and investigate issues more efficiently. You can continue reading and check out the video below to learn more about the latest features.
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By Ivana Huckova
At Grafana Labs, observability is what we do. So as we started building AI agents, we naturally reached for the same instincts we bring to every system: measure it, set targets, and make reliability something you can reason about instead of hope for. That instinct led us somewhere unexpectedly useful. It turns out one of the oldest ideas in reliability engineering, the error budget, maps beautifully onto one of the newest problems in software: how do you know if an AI agent is actually any good?
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By Matt Jacobson
Alert routing often starts simple. A team creates a few contact points, adds some label matchers, and builds a notification policy tree that sends each alert to the right destination. But alerting configurations rarely stay simple. As an organization grows, its notification policy tree must accommodate more teams, services, and routing requirements. Changes for one team still require editing a global configuration, making ownership less clear and independent provisioning harder.
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By Bukola Ayodele
When something breaks in production, the questions that matter most are also the toughest to answer from metrics alone: who was affected, what did they actually see, and is this worth waking someone up for? Answering those questions requires a fuller picture of the issue and its impact on your users. That’s where Digital Experience Monitoring (DEM) in Grafana Cloud comes in.
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By Anant Sharma
Labels are a powerful way to organize telemetry and define policies across Grafana Cloud, helping to streamline alerting, attribution, access control, and more. But traditionally, custom labels in Synthetic Monitoring have worked a little differently: they only lived on a single sm_check_info metric, and Grafana Cloud prefixed each one with label_.
If your Cypress suite has tests that fail more often or run slower, you know it can be hard to figure out the pattern from a single job. It could be one spec that slowed down, or a single test that fails, or maybe the entire suite is trending slower. The root cause could be a bug in the app, or a flaky test, or something else.
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By Arpit kumar
Modern engineering teams instrument everything, with metrics, logs, traces, and profiles flowing from hundreds of services at once. But full-stack observability isn’t really about collecting more telemetry; it's about having a single, unified picture of how your services connect to every layer beneath them, including their dependencies, the pods and nodes they run on, and the logs, traces, and profiles that explain their behavior.
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By Luccas Quadros
Starting an experiment with an LLM has never been easier. Keeping a growing collection of those experiments consistent is another matter. Earlier this year, as more teams began exploring AI features here at Grafana Labs, we repeatedly encountered the same pattern: a new experiment would start, move quickly, and build its own client for whichever model provider it needed. The next experiment would do the same, with a slightly different abstraction for streaming, tools, errors, or provider configuration.
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By Grafana
In this Pyroscope community call, we look at what eBPF is, where it came from, and how the OpenTelemetry eBPF profiler uses it to profile supported workloads without application code changes.
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By Grafana
There are times when you have a panel which does not show any data because there is none and it might be a good idea to hide it until it start showing. Learn how to do this in Grafana.
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By Grafana
As we get into the full swing of prime Aurora viewing season, hear how this Golden Grot Award-winning project by Mohamed Adem uses free, public data and Grafana Assistant to explore whether an aurora will actually be visible.
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By Grafana
The Grafana Mobile App lets you triage alerts with help from Assistant from your phone. You can declare an incident or trigger an investigation into an incident in order to get more information so that by the time you get to your desktop, everything is ready for you. Grafanistas Ignacio and Florian go through a use case deep dive, demonstrating the value of the Grafana Mobile Companion app by triggering an investigation, talk to Assistant, and have all the data you need to resolve an incident - all from your phone.
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By Grafana
With the plan mode you can get a preview what kind of panels you want to have in your dashboard that safe a lot of tokens, efforts and computing resources when using Grafana Assistant AI.
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By Grafana
In the September edition of the Kubernetes Monitoring Helm chart office hours, we discuss the version 4.4 and 4.5 releases, the upcoming 4.6 feature release, and the next 5.0 major release.
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By Grafana
Grafana's Knowledge Graph builds a contextual layer on top of your telemetry data, automatically extracting entities and relationships so you can see how your services actually connect. In this deep dive, Jia show how it powers root-cause investigation both in the Grafana UI and through agentic workflows using gcx and Claude Code. Learn more about Grafana's observability tools and try Knowledge Graph for your own telemetry data at grafana.com.
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By Grafana
In this episode of the Grafana OTel Community Call, we're joined by Sonal Gaud, code owner of otelhttp on opentelemetry-go-contrib. We'll trace her path from writing test-coverage PRs to owning the instrumentation library that most Go services use to get HTTP traces and metrics for free — and go deep on how otelhttp actually works under the hood: context propagation, metrics/attributes via the Labeler, route cardinality, and how the library evolves alongside HTTP semantic conventions.
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By Grafana
Join us for a follow-up Grafana Campfire to explore what we’ve built in Git Sync since December 2025. We’ll cover new and improved Git provider integrations and authentication options, smoother dashboard editing and pull request workflows, and more control over changes through signed commits, user attribution, and PR and commit conventions. We’ll also explore improvements to folder organization and permissions, READMEs alongside your dashboards, and clearer synchronization status.
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By Grafana
The open source server connects any AI assistant to everything in your Grafana - dashboards, metrics, logs, alerts, on-call, incidents - and it can make changes for you, not just look things up. Grafana Cloud takes minutes, and you stay in control - choose exactly what the AI can see and do, including a view-only mode.
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Grafana provides a powerful and elegant way to create, explore, and share dashboards and data with your team and the world. Grafana is most commonly used for visualizing time series data for Internet infrastructure and application analytics but many use it in other domains including industrial sensors, home automation, weather, and process control.
Grafana has a robust plugin architecture built for extensibility. Visualize data from more than 40 data sources, including commercial databases and web vendors, and add new graph panels with rich data visualization options. There is built in support for many of the most popular time series data sources. It works with Graphite, Elasticsearch, Cloudwatch, Prometheus, InfluxDB and more.
Grafana Labs is the company behind Grafana, the leading open source software for visualizing time series data. Grafana Labs helps users get the most out of Grafana, enabling them to take control of their unified monitoring and avoid vendor lock in and the spiraling costs of closed solutions.