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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Fix flaky tests in your sleep with Chunk by CircleCI

A test fails. You rerun it and it passes. You shrug and move on. This is how most teams deal with flaky tests. The “rerun until green” approach works in the moment, and rerunning from failed tests is a useful way to confirm whether a failure is real. But reruns don’t fix the underlying issue. Over time, they burn CI resources and can hide real instability in your code. On the other hand, fixing flaky tests can mean hours of work.

What Is Business Continuity?

A single outage can stop operations, affect customers, and impact trust. In a world of pandemics, cyberattacks, weather events, and supply chain delays, your team cannot pray that something does not break. Business continuity drives your team to stay ready, recover earlier, and keep downtime lower. In this blog, we’ll explain what business continuity means, how to create a solid business continuity plan, and which approaches help teams keep operational during a disruption event.

Simple Talk Podcast - Coffee Chat with Lee Brownhill

Steve sits down with Lee Brownhill, who by day helps clients optimize their SQL workloads in Azure and AWS at Cloud Rede, but is also a Redgate Ambassador, blogger and aspiring speaker. Lee talks about his interest in giving back to the SQL Server community through writing and speaking, having taken inspiration from others online and in-person at events, and naturally the conversation also touches upon AI, the cloud, and more.

What Is Incident Response Lifecycle?

The Incident Response Lifecycle is a step-by-step process that helps engineering teams detect, respond to, and recover from unexpected system disruptions or outages. It includes a series of six practical stages: Detection, Analysis, Impact Mitigation, Incident Resolution, Service Restoration, and Post-Incident Analysis. By following this lifecycle, teams can minimize downtime, reduce business impact, and continuously strengthen system reliability.

Why your Kubernetes clusters and GPUs should live under one roof

The world remains abuzz with AI hype, but the reality is that most modern applications aren’t purely AI workloads. The average company will have web services, APIs, databases, and background jobs running alongside its machine learning inference or training components. An architecture question everyone faces: should your Kubernetes cluster and GPU compute live in the same data center, or can you split them across providers?

Data Centre Colocation: What UK Businesses Need to Know About Costs

As more UK companies go digital, many are missing critical cost factors when choosing colocation data centres, with location, power bills and regulatory compliance proving far more expensive than many anticipate. With insights from Pulsant, a digital edge infrastructure provider, we take a look at true cost of colocation.

The AI Productivity Paradox-and How We're Solving It

There’s a striking disconnect happening in software development right now. According to the 2025 Stack Overflow Developer Survey, 84% of developers are using or planning to use AI tools in their workflows. Over half of professional developers are using AI daily. The adoption is real, it’s fast, and it’s accelerating.

Resolve's Agents of IT podcast - Ep. 4 - Sean and Ari's Hot Takes

Welcome to Agents of IT, the show where we decode the future of enterprise automation and explore what it really takes to achieve Zero Ticket IT. In this episode, Sean and Ari share unfiltered takes on what’s broken in IT operations and how agentic automation is changing everything. From service desk overload to AI-driven resolution, we’re breaking down how IT can finally escape firefighting mode and focus on innovation.

Building Smarter: How AI is Changing Development

The tech industry is on the cusp of a revolution, driven by the rapid adoption of AI and Gen AI. At Civo Navigate London 2025, Josh Mesout (Chief Innovation Officer at Civo) explored the ways in which enterprises are leveraging these technologies to drive productivity and innovation. The conversation highlighted the challenges of scaling and running AI, including infrastructure bottlenecks and data access issues, but also showcased the potential for AI to transform industries and business models.