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Splunk to Acquire Plumbr and Rigor

Splunk has completed the acquisition of Plumbr, an application performance monitoring (APM) company offering auto-instrumentation, Real User Monitoring and deep application performance insights for enterprise applications.

Splunk also announced that it has signed a definitive agreement to acquire Rigor, a digital experience monitoring (DEM) company offering advanced synthetic monitoring and optimization tools. Rigor’s solutions help customers optimize end-user experiences in digital channels.

With both acquisitions and product integrations, Splunk will significantly expand its APM and DEM capabilities. The combined power of Splunk’s Observability Suite will ultimately give customers a seamless, end-to-end observability experience to help guide them across both cloud and on-premises environments, as well as the software architecture transformations occurring with applications.

“The global acceleration to multicloud and hybrid cloud architectures has created an observability revolution. Development, operations and IT teams everywhere require real-time, full-fidelity and ML-driven solutions that can help them quickly and confidently modernize and build cloud-native applications,” said Tim Tully, CTO, Splunk. “Together, Plumbr and Rigor accelerate Splunk’s vision to deliver a comprehensive Observability Suite with best-in-class DEM and APM for all applications. Splunk is the industry’s leading enterprise-grade Observability Suite providing customers with a complete, full-fidelity view into their data.”

Plumbr offers advanced instrumentation, profiling and Real User Monitoring (RUM) capabilities, which are critical to monitoring Java, PHP, Python and .Net applications. The addition of Plumbr’s technology to Splunk’s Observability Suite gives customers unprecedented monitoring and troubleshooting of existing applications, as well as RUM, database monitoring and code profiling capabilities.

“I am proud of the work Plumbr has accomplished over the past nine years in building a dynamic APM platform,” said Priit Potter, CEO and Co-Founder of Plumbr. “Technical talent is incredibly difficult to find, and Plumbr is beaming with some of the brightest minds in DevOps. We’re looking forward to diving in with the Splunk team and helping the company expand its vision to bring data to everything.”

Rigor delivers a unique DEM platform that combines the power of synthetic monitoring with an intelligent optimization engine to help customers find, fix and prevent web and API performance issues impacting user experiences. Rigor’s solutions can complement Splunk’s newly announced RUM offering as part of the company’s best-in-class Observability Suite.

“The combination of Splunk’s existing observability portfolio with Rigor and Plumbr will help our customers accelerate their digital transformations at the speed demanded by modern business,” added Craig Hyde, CEO of Rigor. “I can’t think of a better cultural and technological partner to join forces with than Splunk, and am looking forward to helping Splunk’s customers leverage Rigor to turn data into doing.”

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Splunk to Acquire Plumbr and Rigor

Splunk has completed the acquisition of Plumbr, an application performance monitoring (APM) company offering auto-instrumentation, Real User Monitoring and deep application performance insights for enterprise applications.

Splunk also announced that it has signed a definitive agreement to acquire Rigor, a digital experience monitoring (DEM) company offering advanced synthetic monitoring and optimization tools. Rigor’s solutions help customers optimize end-user experiences in digital channels.

With both acquisitions and product integrations, Splunk will significantly expand its APM and DEM capabilities. The combined power of Splunk’s Observability Suite will ultimately give customers a seamless, end-to-end observability experience to help guide them across both cloud and on-premises environments, as well as the software architecture transformations occurring with applications.

“The global acceleration to multicloud and hybrid cloud architectures has created an observability revolution. Development, operations and IT teams everywhere require real-time, full-fidelity and ML-driven solutions that can help them quickly and confidently modernize and build cloud-native applications,” said Tim Tully, CTO, Splunk. “Together, Plumbr and Rigor accelerate Splunk’s vision to deliver a comprehensive Observability Suite with best-in-class DEM and APM for all applications. Splunk is the industry’s leading enterprise-grade Observability Suite providing customers with a complete, full-fidelity view into their data.”

Plumbr offers advanced instrumentation, profiling and Real User Monitoring (RUM) capabilities, which are critical to monitoring Java, PHP, Python and .Net applications. The addition of Plumbr’s technology to Splunk’s Observability Suite gives customers unprecedented monitoring and troubleshooting of existing applications, as well as RUM, database monitoring and code profiling capabilities.

“I am proud of the work Plumbr has accomplished over the past nine years in building a dynamic APM platform,” said Priit Potter, CEO and Co-Founder of Plumbr. “Technical talent is incredibly difficult to find, and Plumbr is beaming with some of the brightest minds in DevOps. We’re looking forward to diving in with the Splunk team and helping the company expand its vision to bring data to everything.”

Rigor delivers a unique DEM platform that combines the power of synthetic monitoring with an intelligent optimization engine to help customers find, fix and prevent web and API performance issues impacting user experiences. Rigor’s solutions can complement Splunk’s newly announced RUM offering as part of the company’s best-in-class Observability Suite.

“The combination of Splunk’s existing observability portfolio with Rigor and Plumbr will help our customers accelerate their digital transformations at the speed demanded by modern business,” added Craig Hyde, CEO of Rigor. “I can’t think of a better cultural and technological partner to join forces with than Splunk, and am looking forward to helping Splunk’s customers leverage Rigor to turn data into doing.”

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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 ...