Browse DevOps Blogs (19)

Jacquie Capur joins Matty Stratton to unpack what “meaningful control” over tooling looks like in practice: understanding dependencies, verifying reliability, and keeping a realistic exit path. They connect classic DevOps lessons (config management, Terraform, CI/CD) to today’s fast-moving AI tooling, open models, and data residency constraints.

Hidde de Smet explains why “agent-done” work can still create downstream toil, and how GitHub’s Agentic Engineering System (AES) helps teams make delegation reviewable and observable. The article proposes three practical handoffs—evidence packets, enforced stopping points, and release receipts—to reduce “handoff debt” and keep agent output aligned with team capacity.

Thomas Maurer argues that Azure Local should be evaluated as the infrastructure foundation of Microsoft Sovereign Private Cloud, not just as a hypervisor replacement. He breaks down connected vs disconnected operations, Azure Arc control-plane options, and the platform capabilities (AKS, data services, Foundry Local, GitHub Enterprise Local) that shape sovereignty and resilience.

Jesse Houwing breaks down a nasty PSScriptAnalyzer failure in GitHub Actions where Invoke-ScriptAnalyzer intermittently crashed with a missing Get-Command, then shows how Copilot-assisted investigation, benchmarking, and targeted fixes turned it into a deterministic, faster analyzer with evidence reviewers can rerun.

Hidde de Smet lays out a practical way to judge whether a repo is actually ready for AI coding agents, using GitHub Copilot cloud agent as the concrete example. It focuses on repeatable setup, shared commands, focused tests, CI enforcement, and security boundaries so agent sessions aren’t wasted on missing prerequisites.

Thomas Maurer explains how Adaptive Apps and the open-source Radius control plane help teams engineer, test, and prove application portability across Azure, Azure Local, and other Kubernetes environments by separating app intent from environment-specific implementations.

Matt Stratton talks with Naga Sujitha Vummaneni and Sundeep Bobba about reframing CI/CD pipelines as control systems, using feedback signals, constraints, and bounded automation to keep delivery stable—especially as AI-driven changes increase the pace and volume of deployments.

Jesse Houwing shares a practical checklist for deciding whether a third-party GitHub Action is safe to run in your CI environment, focusing on maintenance signals, dependency hygiene, release integrity, and governance. He also explains why pinning what you run matters, and compares SHA pinning, immutable releases, and action lock files.

Jesse Houwing explains why GitHub Copilot cloud agent sessions can’t be spawned from GitHub Actions using GITHUB_TOKEN, and how GitHub’s accountability model (identity, billing, and auditability) shapes what “agentic workflows” can do today. He then lays out practical orchestration patterns that work, with concrete YAML examples.

Jesse Houwing explains how to stop GitHub Copilot agents from confidently inventing details about fast-moving tools by grounding them in a local clone of the real repository, then forcing answers to be backed by file-and-line citations from the source.

DevClass reviews Kubernetes v1.37 (Garhwal), focusing on production-readiness changes like the Metrics API reaching GA, upcoming removals of kube-dns, IPVS mode in kube-proxy, and cgroup v1, plus new features around autoscaling, watch cache behavior, and stricter YAML conventions via KYAML.

Scott Hanselman walks through diagnosing unexpectedly slow 10GbE file transfers by isolating storage from networking with iperf3, then fixing a Windows NIC bottleneck by increasing receive buffers and disabling Large Send Offload (LSO) V2 for IPv4 on an Intel E610-XT2 adapter.

John Naguib lays out a practical architecture for building self-improving AI agents on Azure, focusing on controlled feedback loops (evaluate, learn, test, approve) rather than uncontrolled self-modification. The guide covers agent runtime, tool calling, RAG, memory/experience stores, evaluation, observability, and governance for production use.

DevClass summarizes how Cursor designed its Origin Git repository service to handle Git at large scale, drawing on Vicent Martí’s write-up about Git’s DAG traversal costs, replica synchronization limits, and an object-storage-backed approach using a write-ahead log plus local NVMe caches.

Scott Hanselman walks through a real-world NAS migration from Synology to a UniFi UNAS Pro 8 using Windows and Robocopy, including how he debugged Windows error 665, handled NTFS Alternate Data Streams, and tuned Robocopy switches to avoid major performance traps.

Hidde de Smet explains Agent Plugins 1.0, a small packaging standard that lets teams ship portable Agent Skills and MCP server definitions once, while keeping Copilot-specific extras in a namespaced folder. The post covers the required file layout, manifest and MCP schemas, and enterprise governance controls for plugin and MCP server policy.

Matt Stratton talks with Doug Pagnutti about “industrial DevOps”: the long-running friction between corporate IT and plant-floor OT in manufacturing, why incentives and ticket-driven workflows create risky workarounds, and how security and data-sharing requirements are forcing the two worlds to converge.

DevClass reports on ChainDrop, a new Shai-Hulud npm worm variant that compromises packages via tarballs and can persist through repository configuration files, enabling credential theft and further propagation. The article explains how the attack spreads through npm, GitHub, and developer tools like VS Code, and outlines practical checks and mitigations.

John Edward outlines practical Azure architecture best practices for enterprise applications, covering the Azure Well-Architected Framework, scalability and high availability patterns, security with Zero Trust, observability, infrastructure as code, CI/CD, cost controls, networking, disaster recovery, and governance.