OpenObserve raises USD $10 million for Observability 3.0

OpenObserve has raised USD $10 million in a Series A round and introduced its Observability 3.0 platform.

The funding was led by Nexus Venture Partners and Dell Technologies Capital, both of which backed the company at seed stage and returned for the new round.

OpenObserve sells an open-source observability platform for monitoring logs, metrics and traces across software systems. The latest update adds what it calls an autonomous AI site reliability engineer, or AI SRE, alongside anomaly detection and tools for monitoring large language model workloads.

More than 6,000 organisations use the platform, including many Fortune 100 companies, and its open-source project has attracted more than 18,000 GitHub stars. The new capital will be used to expand commercial operations and support a growing customer base.

Observability software helps engineering teams detect faults, investigate outages and track the behaviour of applications and infrastructure. The market has become crowded with separate tools for infrastructure monitoring, application tracing, log management and, more recently, AI model monitoring.

OpenObserve argues that this fragmented approach is becoming harder to manage as companies generate more telemetry data from AI systems and distributed software environments. In its view, legacy open-source stacks such as Prometheus-Grafana and ELK often force teams to work across several interfaces and make trade-offs over how much data to store and analyse.

Unified platform

Observability 3.0 is designed to bring several of those functions together in one platform. It covers infrastructure, application and LLM observability, and presents telemetry from front-end, back-end, API, network, server and security environments in a single interface.

At the centre of the release is AI SRE, which uses unified telemetry to identify root causes and recommend or take corrective action during incidents. The update also adds anomaly detection to warn teams before incidents occur, along with LLM observability features for prompt monitoring, evaluation tracking and generative AI application performance.

The platform is built on what OpenObserve describes as an S3-native Parquet architecture. It says this helps handle high telemetry volumes while reducing storage costs and avoiding the need for database management.

In a statement announcing the developments, Prabhat Sharma outlined the company's view of the shift in the observability market.

"We simplify the complexity of the AI-native world with a single, high-performance observability platform that transforms raw telemetry into autonomous action," said Prabhat Sharma, Founder and Chief Executive Officer, OpenObserve.

He also linked the new release to changes in how engineering teams operate.

"Observability 3.0 is a new operating model for engineering teams, and the companies that adopt it will ship faster, sleep better, and outpace those still wiring together legacy tools," said Sharma.

Investor backing

The round gives OpenObserve additional backing at a time when infrastructure software investors are placing larger bets on products tied to AI operations and automation. Observability has become a closely watched segment because AI applications tend to increase the volume and complexity of operational data while creating new requirements for monitoring prompts, responses and model behaviour.

Abhishek Sharma, a Partner at Nexus Venture Partners, said the firm's view of the sector had strengthened since its seed investment.

"When we led OpenObserve's seed round, we believed the observability stack was overdue for reinvention," said Abhishek Sharma, Partner, Nexus Venture Partners. "What Prabhat and the OpenObserve team have built since then - in terms of customer traction, architectural differentiation, and a futuristic AI roadmap - has not only validated that belief but positioned the company as a category-defining force in modern observability."

Dell Technologies Capital made a similar case on customer demand, saying companies are struggling to keep up with growing data volumes.

"We talk to enterprise customers every day and they are drowning in data in this AI/agent-first world. They need actionable insights, true, but what they're looking for now are autonomous solutions that measurably lighten workloads," said Deepak Jeevankumar, Managing Director, Dell Technologies Capital. "Prabhat has been focused on that future since day one of OpenObserve. With what's been accomplished so far, our conviction in this team just continues to grow."

Market pressures

Industry analysts have pointed to the same pressures as companies look for fewer tools and more automation in operations. Paul Nashawaty, Principal Analyst and Practise Lead at theCUBE Research, said rising telemetry volumes and fragmented monitoring estates were pushing buyers towards unified platforms.

"Legacy observability stacks weren't built for AI-scale telemetry, and that's creating real friction. Telemetry volumes are growing roughly 30% year over year, yet 75% of organizations still rely on 6 to 15 tools, leading to fragmentation and blind spots," said Nashawaty. "Vendors responding with 'data diets' are solving the wrong problem; engineering teams need more contextual, correlated telemetry, not less, to diagnose issues in AI-driven environments. This is driving a shift to unified observability, where a shared telemetry layer replaces stitched-together tools. Ultimately, it's leading to autonomous operation, AI-driven SRE models such as OpenObserve's where systems surface root cause and act, instead of teams manually triaging incidents."