5 posts tagged with "DevSecOps"

Picture this. A GitHub Copilot coding agent picks up an issue, creates a branch, writes the implementation across four files, adds tests, and opens a pull request. CI passes. Code scanning reports no alerts. A developer reviews the diff, approves, and merges. The change ships to production through an automated deployment pipeline.

Three weeks later, a penetration test discovers that the agent-generated code introduced a server-side request forgery vulnerability. The code was syntactically clean, the tests covered the happy path, and the reviewer did not catch the flaw because the logic looked reasonable in isolation. Now the team needs to answer a question that their security model was never designed for: who is accountable for code that no human wrote?

The Definition Worked. Until a Fourth Participant Showed Up.​

DevOps has always been defined by a simple, powerful equation: People + Process + Tools. That formula captured something essential about how modern software gets built and delivered. It broke down walls between development and operations. It gave organizations a mental model for diagnosing what was wrong when things moved too slowly, failed too often, or created too much friction.

For over a decade, this three-pillar model served the industry well. And it did so because it rested on an assumption that nobody questioned: every participant in the software delivery lifecycle was human.

That assumption no longer holds.

Your Pipeline Was Built for Humans. That's About to Be a Problem.​

Not so long ago, every commit in your repository came from a human. A developer wrote code, pushed a branch, opened a pull request, and a reviewer approved it. Your CI/CD pipeline was designed around that flow: run tests, check lint, scan for vulnerabilities, deploy if green.

That assumption is breaking.

The Age of AI Agents Has Arrived, Is Your Engineering Culture Ready?​

Agentic software engineering is no longer a future concept. AI coding agents, autonomous pull request generation, self-healing pipelines, and AI-assisted operations are already reshaping how teams design, build, test, and ship software every single day.

And here's the uncomfortable truth most teams aren't ready to hear:

Agents don't magically fix broken engineering practices. They scale them.

Introduction​

Rolling out GitHub Advanced Security (GHAS) across development teams can be a complex task. This blog post provides tips and tricks to help you successfully implement GHAS and integrate it with Microsoft Defender for Cloud, ensuring that your teams are not overwhelmed and can maximize the capabilities of Code Scanning, Secret Scanning, Supply Chain Scanning and Infrastructure as a Code Scanning.