New York, NY, USA
2014
  |  By Yuna Verheyden
Tracing is one of the richest observability signals, but it's also noisy and susceptible to data bloat. In a busy system, the vast majority of traces describe the same healthy, fast, successful request over and over, so most organizations downsample their traces to cut costs. But that approach has consequences, since the sampling strategy you choose determines whether you get a faithful picture of your whole system, or just a smaller, blurrier copy of your busiest endpoints.
  |  By Thanos Karachalios
Here's a scenario that will likely sound familiar: You’re building an executive overview dashboard that you would put on a wall-mounted screen so the whole room can see how the business is doing at a glance. It’s for a Shopify online store, and displays a mix of business and application signals, including latency panels, error-rate panels, and a big stat panel for revenue-per-week. It looked great. But something is missing.
  |  By Rajesh Mahalingaswamy
When a Terraform run feels slow, most teams are flying blind. The run log in HCP Terraform tells you what happened, but not what took so long—and it certainly doesn't roll up across hundreds of runs so you can spot a trend.
  |  By Jack Gordley
Observing fast-growing agentic workloads is no small feat, especially if you try to build your own monitoring stack or rely solely on tools built for a time before LLMs. At Grafana Labs, we know this all too well.
  |  By Mat Ryer
Thank you for spending AI Week with us. We’re thrilled by the reaction and we all enjoyed replying to your questions. Thanks for engaging.
  |  By William Dumont
Continuous integration and continuous delivery (CI/CD) have dramatically changed how we ship software. But once code reaches production, the operational work is still surprisingly manual. Engineers continually monitor systems, investigate unexpected behavior, and decide which issues require action. And that is where the next opportunity for AI-driven automation lies. For example, in today's CI/CD workflows, someone refreshes the pipeline page to see whether the queue has moved.
  |  By Dafydd Thomas
You’re about to click "Merge" on a PR, but you feel more anxious about it than you used to. Why?
  |  By Sven Großmann
It's Monday afternoon and that feature you've been working on is mostly done. There's just one item still sitting untouched at the bottom of the ticket: "Add monitoring." You know you should. You also know the sprint ends tomorrow, nobody on the team is an observability expert, and figuring out what to measure—let alone how to write the PromQL for it—feels like a project all on its own. So it gets the same treatment it always does: "We'll add it when it breaks.".
  |  By Mat Ryer
Observability has traditionally been tacked on after your code hits production, but with agentic operations on the rise, that's no longer sustainable. Agents have dramatically increased the rate of change as they write more code, ship more changes, and operate more systems—all at a speed that compounds scale and complexity.
  |  By Logan Smith
As AI agents accelerate software development and spin up applications at scale, visibility into what's happening behind the scenes, including query performance and database health, has never been more important. Gaining that level of insight requires observability that can keep pace.
  |  By Grafana
We will look at some new features: Call Tree, Heat Map, & Adaptive Profiles Can't comment in the chat? You may need to create a channel. Join us live for an introduction to flame graphs. We’ll cover what they are, how to read them, and how to use them to find performance bottlenecks in your applications. Bring your questions! Grafana Cloud is the easiest way to get started with Grafana dashboards, metrics, logs, traces, and profiles. Our forever-free tier includes access to 10k metrics, 50GB logs, 50GB traces and more.
  |  By Grafana
Understand the basic building blocks of the Grafana Stacks as how all the elements (tools) combine together to give you a complete visual to your platform Thanks for watching!
  |  By Grafana
We will look at some new features: trace diff and span pruning Can't comment in the chat? You may need to create a channel. Join us live for an introduction to flame graphs. We’ll cover what they are, how to read them, and how to use them to find performance bottlenecks in your applications. Bring your questions! Grafana Cloud is the easiest way to get started with Grafana dashboards, metrics, logs, traces, and profiles. Our forever-free tier includes access to 10k metrics, 50GB logs, 50GB traces and more.
  |  By Grafana
Friday, the last day of AI Week, is all about collaboration. Here's what we're announcing today! Check out grafana.ai for more details on everything we announce this week.
  |  By Grafana
Senior Developer Advocate Nicole van der Hoeven explains how we're thinking about observability and AI at Grafana Labs. She talks about how you can use AI with observability across the entire SDLC and the different tools you can use for both AI for observability and observability for AI.
  |  By Grafana
Grafana AI Observability is our new database and platform for observing AI Agents. Over the past year at Grafana Labs, we built Agents and we needed a way to understand how they are performing, what are the costs associated with them, what's the error rate or time to the first token as well as how they are behaving. Grafana Staff Engineer, Ivana Hučková provides a deep dive demo on how Grafana AI Observability connects our experience building Agents with our experience building observability systems.
  |  By Grafana
Senior Software Engineer William Dumont demonstrates how we test Assistant Investigations by pitting two versions of the same agent against each other to correctly identify and remediate a production incident we've already resolved.
  |  By Grafana
Thursday is about testing and evaluation. Here's what we're announcing today! Check out grafana.ai for more details on everything we announce this week.
  |  By Grafana
Staff Software Engineer Alexander Sniffin demonstrates how you can use Assistant Investigations to automatically start an investigation for you when an alert fires in Grafana. When you receive an alert, Investigations can do the work to figure out the root cause so that you don't have to spend your time doing so. Assistant Investigations is now generally available for Grafana Cloud.
  |  By Grafana
Wednesday is about operations and maintenance. Here's what we're announcing today! Check out grafana.ai for more details on everything we announce this week.

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.