The Convenience Click That Put 2,539 Secrets on Public GitHub

A new Apiiro investigation reveals how Claude Code’s “don’t ask again” command approvals can inadvertently expose sensitive credentials in GitHub repositories. Researchers identified 2,539 distinct secrets across 1,994 repositories, including database passwords, API keys and SSH credentials. The findings highlight a growing security blind spot as AI coding agents quietly turn developer convenience into persistent security policy…

Tom Smith Nov 10, 2026

OpenAI Kept Git and Rebuilt Everything Behind It

OpenAI has rebuilt the Git infrastructure behind its monorepo to handle the explosive growth in activity driven by Codex coding agents. Its new Rust-based backend, Pando, reduces median push latency by approximately 80% while moving nearly a petabyte of Git data daily. The project highlights why DevOps teams must rethink infrastructure designed for human developers as autonomous agents reshape software delivery…

Tom Smith Nov 10, 2026

Blogs

Survey: Need for Speed Tops All Other AI Coding Metrics

A Uplevel survey of 428 engineering and technology leaders reveals a widening gap between AI coding adoption and the ability to measure its business value. While 96% believe AI is improving software development, just 4% have adopted new metrics, and growing code review demands threaten to undermine productivity gains…

Mike Vizard Nov 10, 2026

Claude Code’s “Don’t Ask Again” Feature Creates Major Security Risk

Anthropic’s Claude Code has exposed thousands of passwords, API keys and other sensitive credentials through a feature created to simplify developers’ daily work, according to research from software security firm Apiiro. The researchers identified 2,539 distinct secrets across 1,994 public GitHub repositories, including credentials that could provide access to cloud infrastructure and enterprise applications. The…

James Maguire Nov 9, 2026

Blogs

Ten Great DevOps Job Opportunities

DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted as part of an effort to better serve our audience. Our goal in these challenging economic times is to make it just that much easier for DevOps professionals to advance their careers. Of course, the pool of…

Mike Vizard Nov 9, 2026

Featured Reports

DevOps.com Research

The State of Observability 2026: Bigger Budgets, Higher Stakes and the Rise of the Agent

Observability budgets are climbing fast: a Futurum Group survey of 628 enterprise IT leaders reported by DevOps.com found 36% plan to spend more than $1 million on observability in 2026, with 7% planning to spend more than $5 million. This report draws on Futurum Group research, Enterprise Technology Research (ETR) spending-intention data, practitioner reporting from DevOps.com, Cloud Native Now and PlatformEngineering.com, and executive interviews and webinars from Techstrong TV and Techstrong Learning. Five findings stand out: spending is moving up-market; cost control is the central operational problem; no enterprise has a truly unified platform; AI observability has become a buying priority before agents are widely deployed; and platform engineering is becoming the delivery vehicle for observability.

Techstrong EditorialUpdated November 5, 202616 min read

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DevOps.com Research

The State of AI Coding in DevOps Workflows

Coding using artificial intelligence (AI) tools is no longer an experiment for DevOps teams. It is the new operational reality. Futurum Research, for example, finds that 76.6% of organizations actively use AI in development workflows and another 20.4% are evaluating it. The ETR arm of the Futurum Group, meanwhile, is reporting that 93% of AI coding tool users report measurable productivity gains, which ETR calls the strongest signal of tangible return from investments in AI. This report draws on Futurum Group research, Enterprise Technology Research (ETR) data, practitioner reporting from DevOps.com, Cloud Native Now and PlatformEngineering.com, and executive interviews and webinars from Techstrong TV and Techstrong Learning. Four findings stand out: AI coding adoption has reached critical mass; the bottleneck has moved from writing code to reviewing and verifying it; coding agents are privileged software that widen the supply chain; and platform engineering is becoming the control plane for AI-generated code.

Techstrong EditorialUpdated November 5, 202616 min read

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