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OpenObserve Raises $10M in Series A Funding

OpenObserve announced a $10 million Series A financing round led by Nexus Venture Partners and Dell Technologies Capital. 

Both lead investors participated in the company’s seed round and preemptively funded this round, driven by their strong conviction in the company’s momentum and enterprise traction.

OpenObserve offers a single high-performance platform that ingests logs, metrics and traces, as well as real user monitoring (RUM), pipelines, visualization, incident management, anomaly detection and more, while applying embedded AI to understand and act upon these inputs in real time.

OpenObserve’s new suite of AI capabilities includes an AI site reliability engineer (AI-SRE), an autonomous layer that transforms raw telemetry into operational intelligence, without requiring engineering teams to manually sort signal from noise. Also included in that suite are MCP support and LLM observability, making AI monitoring and evals another layer that OpenObserve supports on top of frontend, backend, API, network, servers, security, and more.

“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 CEO of OpenObserve. “This enables companies to move from firefighting to proactive, autonomous operations, Observability 3.0, and build the products that drive their businesses forward.”

The new capital will be used to scale go-to-market actions and to support a growing customer base. The company will build on recent expansions including OpenObserve’s Observability 3.0 vision of predictive analytics and autonomous observability, increased regional footprint with new availability in the U.S. West and the European Union, and added hosting support on Microsoft Azure. The company has also named Shani Shoham chief revenue officer to lead the commercial expansion.

“When we led OpenObserve’s seed round, we believed the observability stack was overdue for reinvention,” said Abhishek Sharma, partner at 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.”

“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 at 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.” 

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OpenObserve Raises $10M in Series A Funding

OpenObserve announced a $10 million Series A financing round led by Nexus Venture Partners and Dell Technologies Capital. 

Both lead investors participated in the company’s seed round and preemptively funded this round, driven by their strong conviction in the company’s momentum and enterprise traction.

OpenObserve offers a single high-performance platform that ingests logs, metrics and traces, as well as real user monitoring (RUM), pipelines, visualization, incident management, anomaly detection and more, while applying embedded AI to understand and act upon these inputs in real time.

OpenObserve’s new suite of AI capabilities includes an AI site reliability engineer (AI-SRE), an autonomous layer that transforms raw telemetry into operational intelligence, without requiring engineering teams to manually sort signal from noise. Also included in that suite are MCP support and LLM observability, making AI monitoring and evals another layer that OpenObserve supports on top of frontend, backend, API, network, servers, security, and more.

“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 CEO of OpenObserve. “This enables companies to move from firefighting to proactive, autonomous operations, Observability 3.0, and build the products that drive their businesses forward.”

The new capital will be used to scale go-to-market actions and to support a growing customer base. The company will build on recent expansions including OpenObserve’s Observability 3.0 vision of predictive analytics and autonomous observability, increased regional footprint with new availability in the U.S. West and the European Union, and added hosting support on Microsoft Azure. The company has also named Shani Shoham chief revenue officer to lead the commercial expansion.

“When we led OpenObserve’s seed round, we believed the observability stack was overdue for reinvention,” said Abhishek Sharma, partner at 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.”

“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 at 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.” 

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Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...