Skip to main content

Dynatrace to Acquire Rookout

Dynatrace has signed a definitive agreement to acquire Rookout, a provider of enterprise-ready and privacy-aware solutions that enable developers to quickly troubleshoot and debug actively running code in Kubernetes-hosted cloud-native applications.

The addition of Rookout to the Dynatrace platform will help developers accelerate innovation and delivery of flawless and secure releases.

Adding Rookout to the Dynatrace platform will provide developers with increased code-level observability into production environments. This will also add interactivity and control to troubleshooting and debugging in production and drastically reduce the need to replicate issues in pre-production environments. The addition of Rookout to the Dynatrace platform will also improve collaboration across development, IT, and security teams by empowering them with a single platform for observability and security analytics and automation.

“Development teams are increasingly expected to incorporate observability and security capabilities into their solutions (shift-left) as well as perform testing, quality, and performance evaluation in production environments (shift-right),” said Bernd Greifeneder, CTO at Dynatrace. “We believe acquiring Rookout will accelerate this process by providing our customers with developer-observability solutions that scale from a developer’s integrated development environment, or IDE, and are designed to enable their organizations to meet enterprise governance requirements. Our experience is that Rookout enables developers to troubleshoot and debug issues in production significantly faster than traditional tools and approaches, dramatically reducing the time they spend on maintenance activities.”

“Our mission is to make debugging easy and fast for developers with state-of-the-art quality and a simple experience,” said Shahar Fogel, CEO at Rookout. “We believe integrating Rookout into the Dynatrace platform and leveraging the AI and automation capabilities Dynatrace is known for will accelerate this mission. This will also create a new standard for how engineers use developer-first, cloud-native observability to improve productivity by enabling them to spend less time on manual activities and more time delivering business value.”

Dynatrace plans to provide a seamless experience for customers by embedding Rookout into its unified observability and security platform.

Closing of the proposed transaction is subject to customary closing conditions and is expected to occur later in the company’s second quarter, which ends on September 30, 2023. The proposed transaction will not have a material impact on Dynatrace’s fiscal year 2024 financials and will be funded from cash on hand.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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.

Dynatrace to Acquire Rookout

Dynatrace has signed a definitive agreement to acquire Rookout, a provider of enterprise-ready and privacy-aware solutions that enable developers to quickly troubleshoot and debug actively running code in Kubernetes-hosted cloud-native applications.

The addition of Rookout to the Dynatrace platform will help developers accelerate innovation and delivery of flawless and secure releases.

Adding Rookout to the Dynatrace platform will provide developers with increased code-level observability into production environments. This will also add interactivity and control to troubleshooting and debugging in production and drastically reduce the need to replicate issues in pre-production environments. The addition of Rookout to the Dynatrace platform will also improve collaboration across development, IT, and security teams by empowering them with a single platform for observability and security analytics and automation.

“Development teams are increasingly expected to incorporate observability and security capabilities into their solutions (shift-left) as well as perform testing, quality, and performance evaluation in production environments (shift-right),” said Bernd Greifeneder, CTO at Dynatrace. “We believe acquiring Rookout will accelerate this process by providing our customers with developer-observability solutions that scale from a developer’s integrated development environment, or IDE, and are designed to enable their organizations to meet enterprise governance requirements. Our experience is that Rookout enables developers to troubleshoot and debug issues in production significantly faster than traditional tools and approaches, dramatically reducing the time they spend on maintenance activities.”

“Our mission is to make debugging easy and fast for developers with state-of-the-art quality and a simple experience,” said Shahar Fogel, CEO at Rookout. “We believe integrating Rookout into the Dynatrace platform and leveraging the AI and automation capabilities Dynatrace is known for will accelerate this mission. This will also create a new standard for how engineers use developer-first, cloud-native observability to improve productivity by enabling them to spend less time on manual activities and more time delivering business value.”

Dynatrace plans to provide a seamless experience for customers by embedding Rookout into its unified observability and security platform.

Closing of the proposed transaction is subject to customary closing conditions and is expected to occur later in the company’s second quarter, which ends on September 30, 2023. The proposed transaction will not have a material impact on Dynatrace’s fiscal year 2024 financials and will be funded from cash on hand.

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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.