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

Code Compare 5.5 R1 Adds Integration Support for Visual Studio 2026

We’re excited to share Code Compare 5.5 R1, the latest update to our code comparison and merge tool. This release adds integration support for Visual Studio 2026, so teams can compare changes and resolve merge conflicts directly within the IDE workflow they already use. With Code Compare 5.5 R1, developers can review differences, apply merges, and handle conflicts in Visual Studio 2026 using the same comparison experience they rely on across projects and repositories.

Your Flaky Tests Are a Data Problem, Not a Test Problem

Your tests are not flaky. Your test data is. That 401 Unauthorized that fails every Monday morning? The OAuth token in your test fixture expired 72 hours ago. The order_id that works in staging but not in CI? It was hardcoded six months ago and the format changed from integer to UUID in January. The timestamp assertion that passes at 2pm and fails at midnight? You are comparing a hardcoded 2026-01-15T14:30:00Z against Date.now(). These are not test infrastructure problems. Retrying them will not help.
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Runtime Validation vs Static Analysis: Why You Need Both

Runtime validation does not replace static analysis. They solve different problems. Static analysis catches structural defects in code before it runs. Runtime validation catches behavioral failures by testing code against real production traffic. Enterprise teams adopting AI coding tools need both layers because AI-generated code introduces a new class of defects that neither layer catches alone. According to CodeRabbit's State of AI vs Human Code Generation report, AI-generated pull requests contain roughly 1.7x more issues than human-written ones. Many of those issues pass static checks cleanly.

AI Coding Agents Have a UX Problem Nobody Wants to Talk About

The pitch was simple: let AI write your code so you can focus on the hard problems. Three years into the AI coding revolution, and developers are focused on hard problems alright, just not the ones anyone expected. Instead of designing systems and solving business logic, engineers in 2026 spend a startling amount of their day managing the AI itself. Should you use Fast Mode or Deep Thinking? Haiku or Opus? Cursor or Claude Code or Windsurf? Should you write a SKILL.md file or a custom system prompt?

Resolve's Agents of IT podcast - S2Ep5 - Ari's Hot Takes #itautomation #claude #aiautomation #ai

In this episode of Agents of IT, Ari Stowe and Ian Coppock unpack the recent Claude outage and what it reveals about our growing dependence on AI at work. From developers suddenly returning to Stack Overflow to the infrastructure challenges behind AI scaling, the conversation explores what happens when AI becomes critical enterprise infrastructure. They also discuss how organizations should prepare for AI outages, why “stampede adoption” is the new reality of AI releases, and what resilient, multi-agent architectures could look like going forward.

MCP vs. CLI for AI-native development

Summary: The CLI vs. MCP question is really a question about where you are in the development loop. CLIs fit the inner loop: fast, local, zero overhead. MCP servers fit the outer loop: external systems, shared infrastructure, structured access. Most teams need both. AI has put a new kind of scrutiny on developer tooling. When a developer works alongside an AI coding assistant, the tools that assistant can reach, and how it reaches them, directly affect the quality and speed of the work.

How to choose a secure private cloud provider for your enterprise

Enterprise private cloud procurement tends to generate impressive security documentation. SOC 2 reports, penetration test summaries, ISO 27001 certificates, detailed descriptions of network segmentation and encryption standards. What it doesn't always generate is clarity on the question that actually matters: does this infrastructure make it possible to operate securely at the level your organization requires, given your specific workloads, your regulatory context, and your threat model?

Developer workflow fragmentation and what's really happening behind the scenes

In the current landscape of enterprise software delivery, a profound paradox has emerged: as the variety of specialized development tools and cloud services increases, the actual velocity of innovation frequently stagnates. For IT leaders, this phenomenon is known as developer workflow fragmentation. It’s a state where parallel, unstandardized processes create a pervasive "operational drag" that consumes the very agility these tools were intended to provide.