Grafana Labs Crosses 10,000-Customer Milestone as AI Adoption Accelerates Growth Across the Platform

Grafana Labs was recently recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Observability Platforms for the third consecutive year, launched six AI-native products during its inaugural AI Week, and surpassed $600M in Annual Recurring Revenue.

Grafana Labs, the company behind the open observability cloud, today announced it has crossed 10,000 customers worldwide and surpassed $600 million in annual recurring revenue, as organizations standardize on open observability for the AI era.

Teams need AI to help them understand their own systems faster, especially as complexity and overhead remain the top observability concern cited in Grafana Labs' 2026 Observability Survey – a need reflected by the adoption of Grafana Assistant, Grafana Cloud's context-aware AI agent for exploring and troubleshooting observability data, now used by more than 18,000 organizations. Teams also need observability purpose-built for AI systems themselves: When teams move AI into production, models drift, agents take unexpected actions, token costs spike without warning, and the latency and error signals that caught problems for the last decade don't explain what went wrong. The same survey found 57% of organizations are now implementing LLM observability in some capacity. Those two pressures are compounding as fast as AI itself is scaling, and it's the driving force behind the past year at Grafana Labs.

“Every organization is at a different stage of the observability journey, but AI has added new obstacles to navigate that weren't there before: Are you using AI to observe your systems, and do you also need to observe the AI itself?” said Anthony Woods, co-founder of Grafana Labs. “The honest answer, for almost everyone now, is both, and that’s what's driving the growth behind these milestones.”

Momentum across the business

• Customers: 10,000+ organizations worldwide, including some of the world’s largest AI-native enterprises.
• Revenue: ARR significantly surpassed $600M, driven by Grafana Cloud expansion and adoption of the company’s AI-powered solutions, including Grafana Assistant, Assistant Investigations, and Adaptive Telemetry.
• Platform depth: Average products used per contracted customer nearly doubled in two years, from 2.3 to 4.4, with 87.8% of contracted customers now using two or more products and 64.9% using four or more.
• AI adoption: More than 18,000 organizations are actively using Grafana Assistant across paid and free plans. In the first half of 2026, a majority of self-serve and contracted new customers used Grafana Assistant to speed up onboarding and improve time to value.
• Cloud scale: Monthly active Grafana Cloud users grew from roughly 127,000 to more than 251,000 over the past two years, with over 1.1 million distinct people logging in during that window. Self-serve monthly active organizations grew from about 42,000 to 66,000 over the same period.
• Product-led growth: More than 500,000 Grafana Cloud signups over the past two years. As AI lowers the barrier to instrumenting systems, Grafana Cloud's free tier is becoming the fastest on-ramp into the platform.

“What stands out this year isn't just that customers are adopting AI, it's that they're going deeper with us once they do,” said Raj Dutt, co-founder and CEO of Grafana Labs. “The average customer now runs more than four of our products, up from just over two years ago, and that's not an accident. When teams bring AI into production, they don't want another point solution bolted on; they want a platform they can grow into. Crossing 10,000 customers tells us that bet is paying off.”

Building Observability for AI and AI for Observability

Grafana Labs held its inaugural AI Week from July 27 to 31, bringing six capabilities to general availability at once, each one answering a different piece of the same problem: once AI is in production, teams lose visibility into what it's actually doing.

Grafana Assistant Investigations coordinates multiple AI agents to explore a team's observability stack when something goes wrong, correlating signals across metrics, logs, and traces into a complete investigation report often before an on-call engineer finishes reading the alert. Where Investigations handles the moment something breaks, Grafana Agent Observability watches the systems that could break in the first place: it brings the same discipline Grafana has long applied to infrastructure — monitoring, alerting, and cost control — to the AI agents and models teams now run in production, tracking latency, token usage, and agent decision behavior alongside the rest of the stack.

Both depend on engineers and their tools being able to reach Grafana Cloud in the first place, which is where the Grafana Cloud MCP server and gcx (Grafana Cloud CLI) come in: they give AI agents and coding tools native access to Grafana Cloud — the same capabilities engineers use in the UI, at machine speed. Rounding out the GA releases, Grafana Assistant Workspace brings Assistant into a full-page experience where engineers can chat, browse, and build visualizations side by side instead of working in a narrow sidebar, and Grafana Assistant Automations lets teams save an Assistant prompt and schedule it to run again on its own, turning a one-off investigation into a recurring check.

“When our backup infrastructure failed three days before the World Cup opener, Grafana Cloud is what got us through it,” said Neha Kumar, Consultancy Team Lead, Observability and Felix Mohnke, Observability Lead at Deutsche Telekom. “We built an AI-powered situation room that let our team see the whole picture and keep millions of viewers online with zero downtime. That's the kind of platform we've come to rely on. Grafana Assistant already cut our dashboard builds from four months to a single day, so by the time we actually needed it under pressure, we trusted it. That's the combination that matters: AI that makes you faster day to day, and observability solid enough to hold up when it counts most.”

Turning down the noise with Adaptive Telemetry

As AI systems add new telemetry on top of existing infrastructure and application data, the cost of storing signals nobody looks at grows just as fast as the systems themselves. Grafana Cloud's Adaptive Telemetry suite, now complete across metrics, logs, traces, and profiles, has optimized away 28.5 billion metric series and reduced log volumes by 26PB. The result: the broader Adaptive Telemetry suite cuts telemetry costs by 30 to 50% on average without sacrificing the insights teams rely on.

“The economics of observability break down when every new AI workload just adds more data to store and more noise to sort through,” said Tom Wilkie, CTO at Grafana Labs. “Adaptive Telemetry exists so cost scales with the value of your data, not the volume of it. This matters more as AI systems generate telemetry at a pace no team can review manually.”

A year of platform investment and industry recognition

Beyond AI, Grafana Labs shipped major platform updates over the past year: the Grafana Cloud Knowledge Graph, which automatically maps relationships between services, infrastructure, and telemetry; Grafana Bring Your Own Cloud and Grafana Federal Cloud (FedRAMP High, DoD IL5) for regulated and enterprise deployments; Grafana 13; and Mimir 3.0.

That combination of platform depth and AI investment was reflected in a year of industry recognition:

• Named a Leader in the 2026 Gartner® Magic Quadrant™ for Observability Platforms for the third consecutive year, positioned Furthest in Completeness of Vision for the second year in a row
• Ranked as a Leader and Outperformer in GigaOm’s Cloud Performance Testing Radar Report
• Named Observability Innovator of the Year in The Tech Innovation Cubed Awards
• Won "Best Observability Solution" in the DevOps Dozen awards
• Recognized as Data Observability Solution of the Year in the Data Breakthrough Awards

Join Grafana Labs at ObservabilityCON 2026

Grafana Labs invites practitioners, platform engineers, and observability leaders to ObservabilityCON 2026, the company's flagship observability conference, October 19 to 21 at Pier 27 in San Francisco. Can't make San Francisco? ObservabilityCON on the Road brings one-day events to São Paulo, London, Madrid, and Bengaluru, with more cities to be announced.

Resources

• Register for ObservabilityCON 2026.
• Try Grafana Cloud, including the free tier, today.

Gartner disclaimer

Gartner, Magic Quadrant for Observability Platforms, 13 July 2026, Padraig Byrne, Martin Caren, D.B. Cummings, Neil Young

GARTNER and MAGIC QUADRANT is a trademark of Gartner, Inc. and/or its affiliates. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

About Grafana Labs

Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X.

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