Operations | Monitoring | ITSM | DevOps | Cloud

Behind the magic of auto-instrumentation (Grafana OpenTelemetry Community Call)

You add the OpenTelemetry Java agent, restart your app - and like magic, observability appears. But is it really magic? What’s actually enabled by default? What telemetry should you expect to see? What’s missing? And what might you want to tweak, tune, or even turn off?

Block Builder: a new Mimir Component (Mimir Community Call February 2026)

At today’s community call, we will hear from David Grant, one of the engineers who has brought a new component, the Block Builder, into Mimir. Using the Ingest Storage architecture in Mimir 3.0, the Block Builder takes over the block-building responsibility from the Ingester. This feature is experimental in Mimir today, but is rolling out to production inside of Grafana Labs now. This is a great time to introduce the component, discuss the motivation, and show where it fits in the larger architecture.

Grafana Campfire - Back to Basics - (Grafana Community Call - Feb 2026)

Grafana Campfire Community Calls are back. We are starting with *Back to the Basics.* Even though you heard it so many times, but some of you are either new to or not very experienced with terms such as monitoring, observability, metrics, tracing, profiling etc. The good news is that you're not alone, and we've got this!! This will be a perfect learning opportunity to gain understanding during this live call and ask questions if anything is not clear.

The Grafana Labs operating system: Introducing our Guiding Principles

Matt Toback is the VP of Culture at Grafana Labs. We published our original company values back in December 2020. We were a young company, growing fast, and fully remote. Our values at the time were aspirational, and painted a picture of the kind of company we wanted to be. Those values did real work and they mattered. You could hear them used in everyday conversations, and they helped get us to where we are today. But growth has a way of revealing gaps.

The rise of agentic AI in production: Can observability systems run themselves?

Sometimes the biggest shifts in technology aren’t about collecting more data — they’re about who (or what) gets to act on it. In this episode of “Grafana’s Big Tent” podcast, host Tom Wilkie, Grafana Labs CTO, is joined by Spiros Xanthos, Founder & CEO of Resolve AI, Manoj Acharya, VP of Engineering for Observability at Grafana Labs, and Cyril Tovena, Principal Engineer on the Grafana Assistant team, to discuss agentic AI in observability.

From RCA to Autonomous Ops: The Future of AI in Observability | Big Tent S3E7

SREs are famously skeptical of AI — so how do you convince them to trust agents in production? In this episode of Grafana’s Big Tent, Tom Wilkie talks with Spiros Xanthos (Resolve AI), Manoj Acharya (Grafana Labs), and Cyril Tovena (Grafana Assistant team) about agent-first observability. They unpack knowledge graphs, LLM reasoning, autonomous debugging, pricing models, and the “Claude Code moment” for observability. Is autonomous production ops closer than we think?

Grafana 12.4 TL;DR - The Final 12.x Release

As the final minor release in the Grafana 12 series, 12.4 builds on our shift toward scalable, as-code workflows and a dramatically improved user experience. From bi-directional Git workflows to smarter dashboard layouts and stronger governance controls, this release is all about helping teams move faster with less friction.

Grafana 12.4 release: faster and easier data visualization, observability as code updates, and more

As we gear up for Grafana 13, the next major release of the open source data visualization platform that we’ll announce at GrafanaCON this April, our engineering team is still shipping some powerful new features along the way. Case in point: Grafana 12.4 is officially here, and there’s a lot to be excited about. The latest minor release includes a ton of updates that help you build and design dashboards faster than ever, as well as manage and scale those dashboards seamlessly over time.

The Grafana Cloud identity blueprint: balancing security and scale

If you've ever rolled out Grafana Cloud to a growing engineering organization, this pattern may sound familiar: Everything feels simple at first. You invite a few teammates, give them access, and dashboards start appearing. Then the team grows. Then the number of stacks grows. Over time, a model that once felt fast and empowering starts to feel risky, difficult to understand, and even harder to undo. This post is about avoiding that moment.

Use AI to turn any JSON API into a dashboard in minutes with the Infinity data source plugin and Grafana Assistant

The internet is full of fascinating data just waiting to be visualized and queried. And with the latest update to Grafana Cloud, you can start doing it in minutes. Through public APIs, you can access information about global earthquake activity, weather forecasts, music catalogs, and millions of other datasets. And then there's all the data that sits inside company APIs, partner services, and internal platforms that power everyday products and operations.

OpenTelemetry support for .NET 10: A behind-the-scenes look

At Grafana Labs, we are fully committed to the open source OpenTelemetry project and are actively engaged with the OTel community. Many Grafanistas spend a large proportion of their time contributing directly to OpenTelemetry upstream projects, helping make observability more powerful, reliable, and accessible for everyone as part of our big tent philosophy.

The evolution of OpenTelemetry: A deep dive with co-founder Ted Young

Sometimes the biggest challenges in software aren’t about code — they’re about consensus. What do we call things? What do we standardize? And how do you evolve a system that thousands of companies depend on without breaking everything along the way?

OpenTelemetry Deep Dive: Standards, Tracing, and the Future of Observability | Big Tent S3E6

OpenTelemetry co-founder Ted Young joins Grafana’s Big Tent podcast to explain how observability evolved beyond logs, metrics, and traces. Learn why tracing is just logging with context, how OpenTelemetry became a standard, and what’s next for zero-touch instrumentation and AI-driven observability.

Investigate Issues in Slack: Grafana Cloud Slack App with AI

The Grafana Cloud app for Slack brings observability and incident response closer to where you and your teams already collaborate Ask questions about system health, alerts, on-call schedules, and Grafana Cloud features; manage incidents and alerts; and collaborate with full context.

How to run checks on internal services with Grafana Cloud Synthetic Monitoring

Many critical services run inside private networks, where traditional monitoring tools and practices can’t offer full visibility. This makes it difficult to validate service availability and performance before problems impact your users. Synthetic Monitoring — a Grafana Cloud solution that helps you proactively monitor the performance of your applications and services — addresses this gap with a feature known as private probes.

Build, buy, or open source? Understanding your options with Grafana's AI-powered observability

Some questions in engineering never go away. Here’s one that every team eventually confronts: Do we roll up our sleeves and build the tooling ourselves, or do we buy something built for us? It’s a choice that has the power to speed teams up or hold them back. With the rise of AI-powered observability, this familiar software dilemma has re-emerged with higher stakes and faster-moving technology.

Continuous profiling in production: A real-world example to measure benefits and costs

Continuous profiling offers deep visibility into production environments, revealing exactly how applications consume CPU and memory. It’s the go-to observability practice for directly connecting system behavior and performance to specific lines of code. But when teams consider deploying continuous profiling more broadly, a common question comes up: what’s the overhead? Is it safe to run continuous profiling on my production services 24/7, or does the cost outweigh the benefits?

How we built Grafana Assistant - a conversation about AI development for observability

This conversation with Grafana Labs engineers, Mat Ryer, Cyril Tovena and Sven Großmann, dives deep into the engineering behind Grafana Assistant, exploring how agentic AI is transforming the observability landscape. From hackathon origins to sophisticated backend agents, the team shares candid lessons on building, scaling, and refining AI tools for engineers.

Grafana dashboards as code: How to manage your dashboards with Git

Note: This blog post originally published in May 2025 and was updated in February 2026 to reflect that Git Sync is now available in public preview in Grafana Cloud. As your Grafana instance scales, so does the challenge of maintaining dashboards. Managing dozens—or hundreds—of dashboards through the UI alone can quickly become overwhelming. Tracking changes gets murky, dashboards multiply, and consistency suffers.

Add skills to agents: Use Assistant playbooks for faster answers, investigations

Grafana Assistant is the most general-purpose tool we’ve delivered since dashboards. People use our Grafana Cloud LLM to understand unfamiliar areas of their stacks, generate dashboards and beautiful visualizations out of thin air, build queries, and support investigations.

Observing agentic AI workflows with Grafana Cloud, OpenTelemetry, and the OpenAI Agents SDK

As agentic AI applications are used more broadly in production, they introduce new operational models, combining multi-step reasoning, tool execution, and autonomous decision-making into a single workflow. SRE teams need visibility into how these agents behave, where they fail, and how they perform over time.

Grafana Assistant: Why you can trust our agent-and yourself-in an era of AI hallucinations

Let’s be real: AI can hallucinate. And in observability, that feels risky. No one wants an assistant that sends your SREs chasing ghosts. At best, that burns expensive engineering time. At worst, it slows incident response in production and pushes teams toward the wrong remediation path. So here’s the big question: What makes Grafana Assistant different, and why should you trust it? Let’s start by acknowledging the fear. AI hallucinations are a real issue.

How Prometheus Remote Write v2 can help cut network egress costs by as much as 50%

Back in 2021, Grafana Labs CTO Tom Wilkie (then VP of Products) spoke at PromCON about the need for improvements in Prometheus' remote write capabilities. “We use between 10 and 2 bytes per sample to send via remote write, and Prometheus only uses 1 or 2 bytes per sample on the local disk so there’s big, big room for improvement,” Wilkie said at the time.