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Undo Releases Live Recorder 5.1

Undo announced the immediate availability of Live Recorder 5.1, an updated version of its flagship product that now offers the ability to record the execution of applications written in Go.

Codenamed Beenleigh, this update brings huge changes to the market by further enabling software engineering teams to accelerate software defect resolution, even for the most complex application architectures.

With the release of Beenleigh, Live Recorder can now record the execution history of applications written in Go and capture software failures in the act - thereby eliminating the guesswork in software defect diagnosis. Software engineers speed up defect diagnosis by loading the recording of the failure in their usual GoLand IDE and Delve debuggers to step through the recording forwards and backwards using Live Recorder’s reverse-debugging capability.

“The Go programming language has seen its market share double in the past two years - with modern SaaS companies like Uber, Google and Twitch taking up Go as their development language of choice for mission-critical applications,” said Undo CTO Greg Law. “However, the software engineering ecosystem for Go has not kept pace. Beenleigh changes this by giving Go developers a new and better way to reproduce, diagnose and resolve defects that they could not do before with traditional methods and tooling.”

Beenleigh also enhances the Multi-Process Correlation of Shared Memory capability with Fast Switch support where multiple recordings can be loaded in the same debugging session and engineers can jump from one process to another without losing their place in the previous recording file. This helps developers to dramatically reduce the time spent on diagnosing defects in complex multi-process programs.

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Undo Releases Live Recorder 5.1

Undo announced the immediate availability of Live Recorder 5.1, an updated version of its flagship product that now offers the ability to record the execution of applications written in Go.

Codenamed Beenleigh, this update brings huge changes to the market by further enabling software engineering teams to accelerate software defect resolution, even for the most complex application architectures.

With the release of Beenleigh, Live Recorder can now record the execution history of applications written in Go and capture software failures in the act - thereby eliminating the guesswork in software defect diagnosis. Software engineers speed up defect diagnosis by loading the recording of the failure in their usual GoLand IDE and Delve debuggers to step through the recording forwards and backwards using Live Recorder’s reverse-debugging capability.

“The Go programming language has seen its market share double in the past two years - with modern SaaS companies like Uber, Google and Twitch taking up Go as their development language of choice for mission-critical applications,” said Undo CTO Greg Law. “However, the software engineering ecosystem for Go has not kept pace. Beenleigh changes this by giving Go developers a new and better way to reproduce, diagnose and resolve defects that they could not do before with traditional methods and tooling.”

Beenleigh also enhances the Multi-Process Correlation of Shared Memory capability with Fast Switch support where multiple recordings can be loaded in the same debugging session and engineers can jump from one process to another without losing their place in the previous recording file. This helps developers to dramatically reduce the time spent on diagnosing defects in complex multi-process programs.

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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 ...

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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 ...