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

Test Data Management and SOC 2 Compliance | The Tony and Tonie show Ep43

SOC 2 compliance isn’t just about protecting data in your production systems. Your test data may also be exposing you to risk. Here’s how to get it under control. Using production data outside prod is one of the fastest ways to create compliance risk. Tony and Tonie discuss how a Test Data Management approach gives you the control, automation and traceability that SOC 2 demands, without slowing down development.

DORA Metrics in the AI Era: Why Deployment Isn't Faster

DORA metrics in the AI era reveal a paradox: PR volume is climbing, but deployment frequency is staying flat. In this talk, GitKraken's Director of Product Jeff Schinella breaks down why AI-accelerated code generation is creating a review bottleneck that your DORA metrics can't fully explain on their own. Jeff walks through how PR metrics (cycle time, first response time, code churn, and PR size) serve as the leading indicators behind your DORA data. If your deployment frequency is flat while PR counts go up, the bottleneck isn't your devs. It's your review capacity.

Rightsizing Nightmares: When Your Cloud Cost Tool Degrades Performance

This is what production teams see happening. A vertical pod autoscaler recommendation gets applied automatically. Resource requests come down a notch across a namespace. The cost dashboard registers a small cost savings win. A few minutes later, health checks start failing. Pods enter crash loops.

The cloud optionality blueprint: standardizing the stack to end vendor lock-in

Key takeaway: Real cloud strategy isn't about running the same workload everywhere at once; it’s about the freedom to move when you need to. By standardizing the unified configuration file, Upsun enables true cloud optionality, moving provider migration from a re-architect project to a data move project.

AI writes the code. Who delivers it safely? | Harness Blog

The question for enterprise AI in 2026 is no longer just which model. It’s which harness. An agent harness is the system around the model. It decides what the agent remembers, what context it sees, what tools it can call, what it is allowed to do, and what happens when it is wrong. The model provides intelligence. The harness provides control. This is where the real engineering is happening.

From PR to Production Without Leaving Your Cursor IDE | Harness Blog

TLDR: Today, Harness is introducing the Harness Cursor Plugin, bringing the power of the Harness AI-native software delivery platform directly into Cursor. This integration, along with the Harness Secure AI Coding hook for Cursor, allows developers and AI agents to move from code changes to vulnerability detection, CI/CD execution, security validation, approvals, deployments, and operational insight without leaving the editor. AI has completely changed how we write code.

Four types of incident alerts every team should know

Not every incident alert needs the same kind of response. One incident may need to wake someone up right away. Another may simply need to be picked up when the team starts work in the morning. Without a clear way to tell them apart, every incident feels equally urgent. That usually adds noise and makes incident response decisions harder than they need to be. This is where two questions help: In this guide, we’ll discuss what those questions mean and the four combinations that follow.