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Cribl Raises $200M in Series C Funding

Cribl raised $200 million in new Series C funding led by Greylock and Redpoint Ventures, joined by new investor IVP, existing investors Sequoia and CRV, and with strategic investment from Citi Ventures and Crowdstrike.

This Series C funding brings Cribl’s total funding to $254 million, coming on the heels of sizable deals with large enterprise customers including FINRA, Rivian, and Cox Automotive.

David Wadhwani, Partner at Greylock, says: “Cribl is enabling customers to realize their long term observability strategies by addressing the single biggest pain point: getting control of the massive surface of data”

Data has become a double-edged sword in the enterprise. Exacerbated by the dramatic growth of remote work, security attacks, and heightened privacy and compliance requirements, companies are now collecting and storing such vast amounts of observability data that a new landscape of tech vendors have emerged to solve the myriad challenges that this “big data” created. But many data vendors address problems by locking customers into their own expensive data stacks — creating a long-term cost and complexity for customers.

Cribl is taking an open approach to the flow of data in the enterprise. In its flagship product, LogStream, Cribl has invented an entirely new, vendor-agnostic way to parse and route any type of event data that flows through corporate IT systems. In doing so, Cribl’s LogStream has not only created an observability pipeline that offers unparalleled flexibility and control across IT systems — it gives companies the freedom to choose their own analytics tools and storage destinations from a diverse range of best-of-breed data solutions without fear of vendor lock-in, complementing tools such as Splunk, Datadog, and Exabeam.

“Enterprises today are caught between the mythical ideal of a single pane of glass for all data insights, and the harsh reality that they have to install agents everywhere they want to observe data,” said Clint Sharp, co-founder and CEO of Cribl. “Cribl, our customers, and investors recognize there’s a better way — to create a unified data pipeline, with the same agents across security and operations, that allows enterprises to maximize the value of their existing investments. This isn’t a ‘better’ or ‘faster’ version of what’s in the market — it’s an entirely new, open architecture for observability.”

“Today’s IT and security teams are under siege – and no one is building software catered to them. Cribl is truly unique as they are the only vendor in the market giving those teams both the power and the choice to manage — and enrich — the onslaught of data in a totally agnostic way,” said Scott Raney, Managing Director at Redpoint Ventures. “We hear again and again that their customers are in awe when they use Cribl, which is not feedback we hear very often in this space...”

The Cribl team has a deep heritage building innovative technology at Splunk, and at Cribl the team has invented technology that is the single strategic control point for all data in their enterprise — offering unparalleled flexibility and control over observability data flowing between every system in the enterprise. Its superior purpose-built technology is 7x more efficient at processing event data while using far fewer resources than alternatives, and has helped it win relationships with new global customers such as Whole Foods and Vodafone.

“Organizations engaged in digital transformation initiatives are now faced with managing highly dynamic, but also very complex, distributed environments. It’s no surprise then that the top goal of these digital transformation initiatives is to drive operational efficiencies,” stated Bob Laliberte Sr Analyst with ESG. “These modern cloud-native environments generate more data than ever before, and organizations need solutions like Cribl LogStream to enable them to regain control and streamline the collection and distribution of the right data to the right tools, in a cost effective manner.”

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Cribl Raises $200M in Series C Funding

Cribl raised $200 million in new Series C funding led by Greylock and Redpoint Ventures, joined by new investor IVP, existing investors Sequoia and CRV, and with strategic investment from Citi Ventures and Crowdstrike.

This Series C funding brings Cribl’s total funding to $254 million, coming on the heels of sizable deals with large enterprise customers including FINRA, Rivian, and Cox Automotive.

David Wadhwani, Partner at Greylock, says: “Cribl is enabling customers to realize their long term observability strategies by addressing the single biggest pain point: getting control of the massive surface of data”

Data has become a double-edged sword in the enterprise. Exacerbated by the dramatic growth of remote work, security attacks, and heightened privacy and compliance requirements, companies are now collecting and storing such vast amounts of observability data that a new landscape of tech vendors have emerged to solve the myriad challenges that this “big data” created. But many data vendors address problems by locking customers into their own expensive data stacks — creating a long-term cost and complexity for customers.

Cribl is taking an open approach to the flow of data in the enterprise. In its flagship product, LogStream, Cribl has invented an entirely new, vendor-agnostic way to parse and route any type of event data that flows through corporate IT systems. In doing so, Cribl’s LogStream has not only created an observability pipeline that offers unparalleled flexibility and control across IT systems — it gives companies the freedom to choose their own analytics tools and storage destinations from a diverse range of best-of-breed data solutions without fear of vendor lock-in, complementing tools such as Splunk, Datadog, and Exabeam.

“Enterprises today are caught between the mythical ideal of a single pane of glass for all data insights, and the harsh reality that they have to install agents everywhere they want to observe data,” said Clint Sharp, co-founder and CEO of Cribl. “Cribl, our customers, and investors recognize there’s a better way — to create a unified data pipeline, with the same agents across security and operations, that allows enterprises to maximize the value of their existing investments. This isn’t a ‘better’ or ‘faster’ version of what’s in the market — it’s an entirely new, open architecture for observability.”

“Today’s IT and security teams are under siege – and no one is building software catered to them. Cribl is truly unique as they are the only vendor in the market giving those teams both the power and the choice to manage — and enrich — the onslaught of data in a totally agnostic way,” said Scott Raney, Managing Director at Redpoint Ventures. “We hear again and again that their customers are in awe when they use Cribl, which is not feedback we hear very often in this space...”

The Cribl team has a deep heritage building innovative technology at Splunk, and at Cribl the team has invented technology that is the single strategic control point for all data in their enterprise — offering unparalleled flexibility and control over observability data flowing between every system in the enterprise. Its superior purpose-built technology is 7x more efficient at processing event data while using far fewer resources than alternatives, and has helped it win relationships with new global customers such as Whole Foods and Vodafone.

“Organizations engaged in digital transformation initiatives are now faced with managing highly dynamic, but also very complex, distributed environments. It’s no surprise then that the top goal of these digital transformation initiatives is to drive operational efficiencies,” stated Bob Laliberte Sr Analyst with ESG. “These modern cloud-native environments generate more data than ever before, and organizations need solutions like Cribl LogStream to enable them to regain control and streamline the collection and distribution of the right data to the right tools, in a cost effective manner.”

The Latest

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...