Short on Nicole van der Hoeven

What Does a Grafana AI Offsite Look Like?

Wed, 28 Oct 2026 09:00:00 +0100

A quick behind-the-scenes short: what actually happens when Grafana’s AI team gets together in person for an offsite.

Resources

My notes on Grafana Assistant

When to use Grafana Assistant vs MCP vs GCX: Grafana GCX

Fri, 21 Aug 2026 09:00:00 +0100

Three AI tools people confuse: Assistant, MCP, and GCX. Last time I talked about the easy hand — the MCP server. Now the power hand: GCX, a CLI built for AI agents.

If Assistant is the brain and Grafana MCP is the easy hand, then GCX is the power hand — a CLI built for an agent to drive. (Quick refresher: a CLI is a command line interface — no clicking, just typed commands.)

So when does GCX win?

When you’re using terminal coding agents — Claude Code, Cursor, Codex. It writes code, pulls the exact log or metric, and verifies against it — without leaving the editor.
When you need everything. GCX wraps the entire Grafana Cloud API — SLOs, Synthetics, IRM, k6, Fleet — the esoteric corners MCP skips. The full banana.
When you want automation and CI/CD. Dry-run mode, JSON output, and exit codes an agent can act on — built for GitOps.

Do you need Grafana Assistant for this? No — not even a subscription. Bring your own brain, same as MCP: metrics, logs, dashboards, and alerts run on nothing but a service account token. You only really pay for Assistant if you call gcx assistant directly — which taps its reasoning, billed separately.

So there’s your map: Assistant’s the brain, MCP’s the easy hand, GCX is the power hand. It’s not one versus another — they work really well together to give you the best choice in how to access your Grafana stack.

Transcript

I’m differentiating Assistant, Grafana MCP and GCX and in this one I’m talking about GCX. If Assistant is the brain and Grafana MCP is the easy hand, then GCX is the power hand — a CLI built for AI agents.

Quick refresher: a CLI is a command line interface — no clicking, just typed commands. GCX is a CLI built for an agent to drive.

So when does GCX win?

When you’re using terminal coding agents — Claude Code, Cursor, Codex. It writes code, pulls the exact log or metric, and verifies against it — without leaving the editor.
When you need everything. GCX wraps the entire Grafana Cloud API — SLOs, Synthetics, IRM, k6, Fleet — the esoteric corners MCP skips — the full banana.
When you want to do automation and CI/CD. Dry-run mode, JSON output, exit codes an agent can act on — built for GitOps.

Do you need Grafana Assistant for this? No — not even a subscription. Bring your own brain, same as MCP: metrics, logs, dashboards, alerts run on nothing but a service account token. You only really pay for Assistant if you call gcx assistant directly — which taps its reasoning, billed separately.

So there’s your map: Assistant’s the brain, MCP’s the easy hand, GCX is the power hand. It’s not one versus another. They actually work really well together to give you the best choice in how to access your Grafana stack.

Resources

When to use Grafana Assistant vs MCP vs GCX: Grafana MCP

Wed, 19 Aug 2026 09:00:00 +0100

Three AI tools people confuse: Assistant, MCP, and GCX. Last time I talked about the brain — Assistant. Now hand number one: the MCP server, the easy hand.

Grafana MCP — Model Context Protocol — lets any AI client reach into Grafana. The magic part: you bring your own brain.

Using MCP requires two pieces:

The client is your AI app — the brain you bring: claude.ai, ChatGPT, Cursor.
The server is the door into Grafana that exposes the tools.

There are two ways to get that server. The easiest is the Grafana Cloud hosted one — already running, auth built in, just connect and go. But you can also self-host the open-source one on your own infra.

So when do you reach for Grafana MCP?

When you’re using hosted chat tools with no terminal — claude.ai, ChatGPT, your phone. No shell means no CLI, so MCP is the only way in.
When you want to bolt Grafana onto a tool you already use — already in Cursor or Claude? Just add the server. No new workflow.
When you want the best discovery out of the box — the tools describe themselves up front, so even smaller or cheaper models just know what’s available. No trial-and-error.

One honest catch: those tool definitions can eat some context if you load everything — but modern hosts fix that with lazy tool search.

MCP is deliberately curated — it doesn’t expose every corner of Grafana. So what do you do when you need the esoteric stuff? That’s exactly what the power hand, GCX, is for — next up.

Transcript

Three AI tools people confuse: Assistant, MCP, GCX. Last time, I talked about the brain — Assistant. Now hand number one: the MCP server, the easy hand.

Grafana MCP — Model Context Protocol — lets any AI client reach into Grafana. The magic part: you bring that AI client - you bring your own brain.

Using MCP requires two pieces. The client is your AI app — the brain you bring: claude.ai, ChatGPT, Cursor. The server is the door into Grafana that exposes the tools.

Two ways to get that server: the easiest way is to use the Grafana Cloud hosted one — already running, auth built in, just connect and go. But you can also self-host the open-source one on your own infra.

So when do you reach for Grafana MCP?

When you’re using hosted chat tools with no terminal — claude.ai, ChatGPT, your phone. No shell means no CLI, so MCP is the only way in.
When you want to bolt Grafana onto a tool you already use — already in Cursor or Claude? Just add the server. No new workflow.
When you want the best discovery out of the box — the tools describe themselves up front, so even smaller or cheaper models just know what’s available. No trial-and-error.

One honest catch: those tool definitions can eat some context if you load everything — but modern hosts fix that with lazy tool search.

But MCP is deliberately curated — it doesn’t expose every corner of Grafana. So what do you do when you need the esoteric stuff? That’s exactly what the power hand is for. Next up is GCX.

Resources

When to use Grafana Assistant vs MCP vs GCX: Grafana Assistant

Mon, 17 Aug 2026 09:00:00 +0100

Grafana has three AI things people keep confusing — Assistant, MCP, and GCX. They’re not competitors. Think of it as a brain and two hands. In this short, I start with the brain: Grafana Assistant.

Assistant isn’t just a chatbot — it’s the reasoning layer. It manages context and knows your Grafana: your dashboards, your data sources, a knowledge graph of your infrastructure. Instead of clicking around, you tell Assistant what you want to do and it figures out the how.

Reach for the Assistant when the work is visual or exploratory:

Building a dashboard? Assistant.
“Teach me how to do this” or “where is this in the UI”? Assistant.
A real incident that needs root-cause analysis across multiple data sources? Assistant. That’s its sweet spot — it forms a hypothesis, correlates your signals, and can even open a pull request with the fix.

Here’s the key thing though: Assistant is Grafana’s own brain — but it’s not the only brain that can drive Grafana. That’s where the two hands come in, and I’ll cover the first of those (the MCP server) next.

Transcript

Grafana has three AI things people keep confusing — Assistant, MCP, and GCX. I’m going to talk a bit about each one so you know which one is best for your use case.

Spoiler: They’re not competitors. Think of it as a brain and two hands.

Let’s start with Grafana Assistant, which is the brain.

It’s not just a chatbot — it’s the reasoning layer. It manages context, it knows your Grafana: your dashboards, your data sources, a knowledge graph of your infrastructure. So instead of you clicking around to do something, you can say what you want to do to Assistant and it figures out the how.

Reach for the Assistant when the work is visual or exploratory.

If you’re building a dashboard? Assistant.
“Teach me how to do this” or “where is this in the UI”? Assistant.
You have a real incident where you need root-cause analysis across multiple data sources? Assistant.
- That’s its sweet spot — it forms a hypothesis, correlates your signals, and can even open a pull request with the fix.

Here’s the key thing though: Assistant is Grafana’s own brain — but it’s not the only brain that can drive Grafana. That’s where the two hands come in… and I’ll show you those next.

Resources

Grafana Assistant (product page)
My notes on Grafana Assistant
My notes on GCX
Unlearnings from building Grafana Assistant — my Context Horizon piece

AI Week Day 5: Collaborating (Grafana AI Week — Friday)

Fri, 31 Jul 2026 09:00:00 +0100

The final day of AI Week is about collaborating — using AI right where your team already works, no context switching required. Grafana Assistant in Slack is now generally available: investigate issues, ask follow-up questions, and query your metrics and logs from the channel where the incident conversation is already happening. And that’s just one place Assistant now meets you — also announced: the Grafana mobile app is GA (with Assistant on mobile in public preview), Assistant Desktop in public preview, Microsoft Teams support in private preview, and context-aware Assistant Search in public preview. Add it all up and Assistant is now wherever you are: the Grafana UI, the API, your terminal, your coding agent, Slack, Teams, mobile, desktop, and search. That’s a wrap on five days of announcements.

Transcript

It’s the final day of Grafana Labs’ AI Week, and Friday is all about collaborating — using AI right where your team already works, no context switching required.

Today, Grafana Assistant in Slack is generally available. Investigate issues, ask follow-up questions, query your metrics and logs — all from the channel where your incident conversation is already happening.

And that’s just one place Assistant now meets you. Today we also announced: the Grafana mobile app is GA, with Assistant on mobile in public preview. Assistant Desktop is in public preview. Microsoft Teams support is in private preview. And Assistant Search — deeper, context-aware search — is in public preview too.

Add it all up, and Assistant is now wherever you are: the Grafana UI, the API, your terminal, your coding agent, Slack, Teams, mobile, desktop, and search.

That’s a wrap on five days of announcements — and I know it was a lot. So if you missed a day, or you just want the full picture of where AI at Grafana stands today, I made a video for exactly that: everything you can do with AI in Grafana Cloud, including everything we shipped this week. It’s linked below and pinned in the comments.

One last time: grafana.ai for all of it. Thanks for spending AI Week with me.

AI Week Day 4: Evaluating (Grafana AI Week — Thursday)

Thu, 30 Jul 2026 09:00:00 +0100

Day four of AI Week is all about evaluating — because building an agent is the easy part; trusting it is where things get hard. The headline: Grafana Agent Observability is now generally available — the tool Grafana built for itself while scaling Assistant, once it grew too complex to evaluate with unit tests. Instrument your agent with the SDK and your conversations, tool calls, traces, latency, token use, and cost all become observable in one place; add evaluators (LLM judges plus deterministic checks) to score quality on live traffic, feed low-scoring conversations into your test suite, and gate CI on experiments comparing a candidate against a baseline. And because evaluator metrics land in Prometheus, you can get paged when a bad prompt change tanks quality. The fun bonus: k6 agentic testing — describe a browser test in plain language and an agent embedded in k6 drives the browser, no script required (they proved it by getting it to beat Wordle).

Transcript

It’s day four of Grafana Labs’ AI Week, and Thursday is all about evaluating — because building an agent is the easy part. Trusting it is where things get hard.

The big news: Grafana Agent Observability is now generally available. This is the tool we built for ourselves while scaling Grafana Assistant, when it grew too complex to evaluate with unit tests. Now it’s available to everyone on Grafana Cloud.

Here’s how it works: instrument your agent with the SDK, and your conversations, tool calls, traces, latency, token use, and cost all become observable in one place. Then add evaluators — LLM judges plus deterministic checks — to score quality on live traffic. Low-scoring conversations feed your test suite, and experiments let you compare a candidate against a baseline before you ship — you can even make it a CI gate. And because evaluator metrics land in Prometheus, you can get paged if a bad prompt change tanks quality in production.

But my favorite part of today? k6 agentic testing. Describe a browser test in plain natural language, and an agent embedded in k6 drives the browser for you — no script at all. And to prove it, we gave it one job: beat Wordle. Go watch that video. I’ll wait.

Everything’s at grafana.ai — see you tomorrow for the finale: using AI where your team already works.

AI Week Day 3: Operations & Maintenance (Grafana AI Week — Wednesday)

Wed, 29 Jul 2026 09:00:00 +0100

Day three of AI Week is about operations and maintenance — because once code reaches production, the operational work is still surprisingly manual: someone’s watching dashboards, deciding whether an error spike is real, and writing up what happened, every single day. Two Grafana Assistant features went GA to take that off your plate. Assistant Automations handle recurring work — save a prompt and run it on a schedule (like a morning brief on your service’s health), each run keeping its own history and able to notify you in Slack. Assistant Investigations is for when something actually breaks: it digs across metrics, logs, traces, and profiles, develops and tests hypotheses, and hands you a structured report you can follow along with in a Workspace. You’re offloading vigilance, not accountability — the evidence is always there to review, and you still make the call.

Transcript

It’s day three of AI Week, and Wednesday is all about operations and maintenance. Because here’s the thing: once your code reaches production, the operational work is still surprisingly manual. Someone’s watching dashboards, someone’s deciding whether that error spike is real, and someone’s writing up what happened — every single day.

Today, two features of Grafana Assistant are now generally available to take that burden off your plate: Investigations and Automations.

Assistant Automations handle the recurring work of operating a system. Save an Assistant prompt and run it on a schedule — like a morning brief that summarizes the operational health of your service over the last 24 hours. Every run keeps its own conversation and history, and it can notify you in Slack when it’s done or needs approval.

Assistant Investigations is for when something actually breaks. Investigations digs into issues across your metrics, logs, traces, and profiles, develops and tests hypotheses, and hands you a structured report. You can follow along in a Workspace, see what’s been ruled out, and add guidance while it works.

You’re offloading vigilance, not accountability — the evidence and reasoning are always there to review, and you still make the call.

Everything’s at grafana.ai — see you tomorrow for day four: evaluating your agents.

AI Week Day 2: Building (Grafana AI Week — Tuesday)

Tue, 28 Jul 2026 09:00:00 +0100

Day two of AI Week is all about building — the AI tools that help you write software with confidence. Two big announcements went generally available: gcx (the Grafana CLI) and the Grafana MCP server. Both connect your coding agents — Claude Code, Cursor, and friends — to your Grafana telemetry. The MCP server gives agents opinionated, ready-made tools for the common cases (querying metrics and logs, reading and updating dashboards); gcx is the more flexible, less opinionated option, built for agents from the ground up with read-only guardrails and its own bundle of agent skills. Both work for OSS and Grafana Cloud. The point: when an agent writes your code, it shouldn’t be guessing — it should be looking at how your system actually behaves in production. That’s telemetry-driven development.

Transcript

It’s day two of Grafana Labs’ AI Week, and Tuesday is all about building — the AI tools that help you build software with confidence.

Today we have two big announcements: gcx and the Grafana MCP server are both now generally available.

Both of them connect your coding agents — think Claude Code or Cursor — to your Grafana telemetry. So what’s the difference?

The Grafana MCP server gives your agent opinionated, ready-made tools for the most common use cases: querying your metrics and logs, reading and updating dashboards, that kind of thing. You can run it yourself, or use the hosted MCP server with your Grafana Cloud stack — so yes, it works for both OSS and Grafana Cloud.

gcx is the Grafana CLI, and it’s the more flexible, less opinionated option. Agents can explore it and build their own workflows, and it was designed for agents from the ground up, with read-only guardrails so your agent can’t touch anything you didn’t approve. It works with Cloud stacks and self-managed instances, and it even ships with its own bundle of agent skills.

Why does this matter? Because when an agent writes your code, it shouldn’t be guessing — it should be looking at how your system actually behaves in production. That’s telemetry-driven development.

Head to grafana.ai for everything we’re shipping this week, and I’ll see you tomorrow for day three.

AI Week Day 1: Planning (Grafana AI Week — Monday)

Mon, 27 Jul 2026 09:00:00 +0100

It’s day one of Grafana Labs’ AI Week, and Monday is all about planning — getting the clarity you need on what’s going on in your system so you can figure out what to build. Kicking things off is Workspace for Grafana Assistant: a full-page view of Assistant so your conversations and generated graphs aren’t crammed into the little right-hand sidebar. It’s a much less cluttered place to run investigations and to be agent-first. On top of that, Assistant is now easier to try — enable it in Grafana 13 for OSS without linking a Grafana Cloud account, or try it with no signup or download at all on Grafana Play.

Transcript

Hi everyone! I’m Nicole van der Hoeven and I’m really excited to welcome you to AI Week. Today is Monday, which is planning day, where we give you the tools you need to get clarity on what even is going on in your system so that you can figure out what to build.

Now we’re kicking things off with a feature called Workspace for Grafana Assistant. Now if you’ve used Assistant before, you’ll know that it comes up on the little sidebar on the right side of Grafana. Well, that can start to get cramped if you have multiple conversations or if you’ve asked Assistant to generate multiple graphs for you. Well, we’ve heard you, and now we’re giving you a full page view of Assistant. So you’ll have all of your conversations on the left, and this is also an excellent place to run investigations from. You can also zoom in on any of those graphs, and it’s just a much less cluttered view if you want to be agent-first.

Speaking of Assistant, the second thing I want to tell you is that you know, Assistant was already available everywhere. But now, Assistant is available… in more places than everywhere? And also more easily. So Assistant was already available for OSS, but you had to link your Grafana Cloud account, which was not so handy if you wanted to try it out. But not anymore. Now if you download Grafana 13 and enable Assistant, then you’ll just be able to go and try it out and chat with Assistant without doing anything else. It’s still not free or open source, but it IS a lot easier to try it out.

And if you don’t want to download anything, that’s what Grafana Play is for. Grafana Assistant is now available to try out on Grafana Play without any signup or any download required. Try it out at play.grafana.org. I really love seeing it there. Tune in tomorrow where we’re going to talk about everything we’re announcing to help you start to build.