GitHub Adds Tools to Manage AI Coding Agents Running in Parallel at Scale

GitHub today made a bevy of updates that collectively promise to make it simpler for DevOps teams to build and maintain workflows using artificial intelligence (AI) agents. Announced at the GitHub Universe conference, Jay Parikh, executive vice president for CoreAI at Microsoft, also provided additional insights into the investments that Microsoft is making to ensure…

Mike Vizard Oct 28, 2026

AWS Delivers AI Service to Discover Vulnerabilities and Generate Patches

Amazon Web Services (AWS) has made generally available a service through which it finds and validates code vulnerabilities and provides a patch that DevSecOps teams can then automatically apply or set up a pull request to implement. Dr. Neha Rungta, director of applied science at AWS, said the AWS Continuum service for code vulnerabilities is…

Mike Vizard Oct 27, 2026

Blogs

Report: Claude Code Exceeds GitHub Copilot for Merging Pull Requests

An analysis of pull requests published today by Jellyfish, a provider of an engineering intelligence platform, finds that Claude Code is the artificial intelligence (AI) coding tool used most often to merge pull requests (31%), followed by GitHub Copilot at 23%. Based on analysis of 100 million pull requests made in September by 276,000 developers…

Mike Vizard Oct 27, 2026

Blogs

Reddit’s r/opensource AI Ban Targets the Wrong Problem

Reddit’s largest open-source community is cracking down on AI-generated projects, prompting criticism over sweeping restrictions that could exclude legitimate developers. As Linux takes a different approach, DevOps teams face a more important question: How can they enforce code quality and accountability without banning the tools developers use?…

Tom Smith Oct 27, 2026

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DevOps.com Research

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

Observability has crossed a threshold. What began as a set of tools for monitoring infrastructure has become a strategic investment that enterprise IT leaders now tie directly to their ability to deploy artificial intelligence (AI) safely. 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. At the same time, telemetry costs are rising faster than many teams can justify, tool sprawl remains stubborn, and AI agents are exposing the limits of the metrics, logs and traces model. 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 October 26, 20269 min read

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