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Datadog Acquires Timber Technologies

Datadog acquired Timber Technologies, the developers of Vector, a vendor-agnostic, high-performance observability data pipeline.

With Vector, customers can collect, enrich, and transform logs, and other observability data both on-premises and in cloud environments, and can route this data automatically to the destination of their choice.

Observability data like logs, traces and metrics are critical to organizations maintaining the health and availability of their applications. However, enterprises can often have hundreds of legacy and cloud observability technologies deployed across their applications, making it impossible to manage the egress of sensitive data, consolidate monitoring platforms and control costs. With Vector, customers will be able to solve these challenges by gaining full control over how and what data flows out of applications into observability platforms whether they run on-premises or in the cloud.

“Observability has become central to how businesses operate in the modern digital world, yet organizations have little to no control over what data is collected and managed by multiple observability platforms, creating complex compliance issues, vendor lock-in and cost overruns,” said Renaud Boutet, VP, Product, Datadog. “With Datadog’s ‘Without Limits’ model we introduced some choices for customers for how to manage their observability data in the cloud. And, with Vector, we plan to bring this flexibility to on-premises environments while also adding many new features.”

“Our vision for Vector has always been to help customers take back control of their observability data,” said Zach Sherman, CEO, Timber Technologies. “Working with Datadog means we will be able to expand on that vision, to build the ultimate observability pipeline for logs, metrics and traces, and to improve the monitoring experience for millions of engineering teams around the world.”

Under the terms of the acquisition, co-founder and CEO Zach Sherman and co-founder and CTO Ben Johnson will join Datadog within the product and engineering teams respectively to build this integrated vision. The core team from Timber Technologies will become Datadog employees.

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Datadog Acquires Timber Technologies

Datadog acquired Timber Technologies, the developers of Vector, a vendor-agnostic, high-performance observability data pipeline.

With Vector, customers can collect, enrich, and transform logs, and other observability data both on-premises and in cloud environments, and can route this data automatically to the destination of their choice.

Observability data like logs, traces and metrics are critical to organizations maintaining the health and availability of their applications. However, enterprises can often have hundreds of legacy and cloud observability technologies deployed across their applications, making it impossible to manage the egress of sensitive data, consolidate monitoring platforms and control costs. With Vector, customers will be able to solve these challenges by gaining full control over how and what data flows out of applications into observability platforms whether they run on-premises or in the cloud.

“Observability has become central to how businesses operate in the modern digital world, yet organizations have little to no control over what data is collected and managed by multiple observability platforms, creating complex compliance issues, vendor lock-in and cost overruns,” said Renaud Boutet, VP, Product, Datadog. “With Datadog’s ‘Without Limits’ model we introduced some choices for customers for how to manage their observability data in the cloud. And, with Vector, we plan to bring this flexibility to on-premises environments while also adding many new features.”

“Our vision for Vector has always been to help customers take back control of their observability data,” said Zach Sherman, CEO, Timber Technologies. “Working with Datadog means we will be able to expand on that vision, to build the ultimate observability pipeline for logs, metrics and traces, and to improve the monitoring experience for millions of engineering teams around the world.”

Under the terms of the acquisition, co-founder and CEO Zach Sherman and co-founder and CTO Ben Johnson will join Datadog within the product and engineering teams respectively to build this integrated vision. The core team from Timber Technologies will become Datadog employees.

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In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

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 ...