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By Thanos Karachalios
In January, we announced that Grafana Labs had assumed maintenance of the business intelligence (BI) plugins created by Volkov Labs, and committed to a six-month maintenance period. Today, we’re sharing an update: we're extending our maintenance commitment through the end of 2026. As announced earlier this year, that commitment includes maintaining compatibility with recent Grafana releases while handling bug fixes, security updates, and community contributions on a best-effort basis.
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By Jake Batty
One of the primary reasons organizations adopt Grafana Cloud is to create a single pane of glass across the data they collect from self-hosted systems, cloud providers, and third-party platforms. Bringing those signals together enables richer correlations, reduces tool sprawl, and makes it easier for teams to understand what's happening across their environment. But as observability grows and becomes more centralized, access management becomes more important.
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By Victor Padilla
Many times, the hardest part of troubleshooting isn’t fixing the actual problem. It’s figuring out where to start. As engineers, it’s easy to lose count of how many times we’ve opened logs, then 10 metrics tabs, and another 10 tabs with trace queries, only to end up back in the logs trying to find a root cause.
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By Grafana Labs Team
Earlier this year, Grafana 13 laid the groundwork for making it easier and faster than ever to turn your data into actionable insights. With our latest minor release, Grafana 13.1, we're building on that foundation, expanding observability as code, bringing Grafana Assistant to more data sources, and streamlining the everyday workflows teams rely on to visualize, analyze, and act on their data. Download Grafana 13.1 Below are just some of the highlights from Grafana 13.1.
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By Maurice Rochau
You can use Grafana Assistant Investigations to automatically discover incidents and help find root causes—and this AI-powered Grafana Cloud feature recently got a major upgrade to give you even more confidence in its findings. You can read more about the behind-the-scenes effort in our new engineering blog Unprompted, where we get into harness engineering, context compaction, benchmarking, and keeping agents alive and working well in long-running sessions.
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By Matt Wimpelberg
For many development teams, a load test starts with a set of assumptions. You pick 100 virtual users because it sounds reasonable. You ramp for 30 seconds because that's what the tutorial showed. You set a 500ms threshold because it feels like a good target. The test passes, you ship the release, and production falls over at 6 p.m. on a Tuesday because your synthetic load never resembled how real users interact with your application.
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By Tiffany Jernigan
Tempo started with a simple goal: make distributed tracing easier to run at scale. As tracing adoption has grown, however, so have the challenges, including higher data volumes, more complex architectures, and increasing demand for real-time insights directly from traces. Over the last year, we’ve been evolving Tempo’s architecture to meet that moment. And today, we’re sharing the results of those efforts with the release of Tempo 3.0.
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By Beverly Buchanan
Kubernetes Monitoring in Grafana Cloud comes out of the box with preconfigured alert rules that notify you about issues like CPU throttling, crash-looping pods, and nodes going offline. These rules are installed automatically when you set up the app, and they start evaluating immediately. But if you've recently reinstalled the Kubernetes Monitoring app and your alert notifications stopped arriving, or started looking different, you're not alone.
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By Kevin Minutti
The ability to schedule regular tasks, such as cron jobs, has been around for decades. So why are we still running the same AI prompts by hand every day? As you use Grafana Assistant, our AI-powered observability agent, to stay on top of the state of your system, you likely find yourself asking the same questions. Maybe you want to know what changed overnight, or whether yesterday's deployment hurt latency, or which dashboards or skills are drifting out of date.
Performance testing is critical to ensure your applications stay reliable under load, but writing the scripts themselves often feels like a chore. Most engineers already know the scenario they want to test; the hard part is translating that intent into a working performance test. Even experienced developers who use k6 can lose time looking up syntax, configuring load stages and thresholds, or debugging boilerplate code before they can run a meaningful test.
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By Grafana
In this episode of Grafana's Big Tent, hosts Mat Ryer (Senior Director of AI, Grafana Labs) and Tom Wilkie (CTO, Grafana Labs) sit down with Eric Burns, Field Executive Architect at Anthropic, to talk about building trust between tech and business execs, why Anthropic bet early on running across every major cloud, and what it was like watching large language models go from "interesting" to "obviously the future" in real time.
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By Grafana
In the June edition of the Kubernetes Monitoring Helm chart office hours, we discuss the version 4.1 release, the upcoming 4.2 feature release, and we discuss the deprecation of the 1.x and 2.0 versions.
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By Grafana
Can you actually trust an AI agent? In this pre-recorded episode of The Context Window, Nicole van der Hoeven sits down with Yas Ekinci, an engineer on the Grafana AI team, to talk about evals — how Grafana measures the quality and reliability of the AI it ships. They get into the difference between online and offline evals, why reviewing AI-generated code has become the real bottleneck, the "final answer problem" of plausible-but-wrong outputs, and o11y-bench, Grafana's open benchmark for observability agents. Along the way.
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By Grafana
Learn the two main ways to get data into Grafana Cloud. In this video, we break down how Grafana Cloud connects to over 150 external data sources (like Salesforce, Postgres, and CloudWatch) where your data stays in place, and how you can send raw telemetry into Grafana’s fully managed databases for logs, metrics, traces, and profiles.
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By Grafana
Grafana 13.1 cuts down on GitOps pain by making Git Sync stronger — import dashboards to Git with a click, see your repo READMEs inside Grafana, and sign every commit for security-strict teams.
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By Grafana
Trust is everything when AI gets personal. Golden Grot Award winner and NeoSapien co-founder and CEO Dhananjay Yadav shares how his team uses Grafana Assistant to ensure the privacy-first AI wearable delivers a seamless, reliable experience without compromising its mission. Because when AI moves closer to our everyday lives, teams need to know what’s happening — and users need to trust that it’s working as intended.
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By Grafana
The Grafana AI team (Engineers Ivana Huckova and Sonia Aguilar) share what's new in AI Observability this week: a new way to instrument and visualize agent workflows, plus a neat trick for jumping straight from a metric spike to the exact conversation that caused it using Prometheus exemplars. In this episode: We're showing parts of our team meetings to build in public in some small way and give you a sneak preview of what's to come. But not all features we show may make it to production! You've been warned. :)
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By Grafana
Our distributed tracing journey from the inception of Tempo to 3.0. Can't comment in the chat? You may need to create a channel. Grafana Cloud is the easiest way to get started with Grafana dashboards, metrics, logs, traces, and profiles.
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By Grafana
Want to try Grafana without installing anything? Jump into Grafana Play, our free sandbox environment where you can explore dashboards, experiment with features, and see Grafana in action, no login or setup required.
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By Grafana
Asimov's Three Laws of Robotics are missing one — and when it comes to testing and observing AI, Nicole van der Hoeven argues that missing rule changes everything: before a robot can avoid harm, obey orders, or protect itself, there has to be a Zeroth Law: a robot must be observable. Because if you can't see what a system is doing, you have no way of knowing whether it's following any rule at all.
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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.