GitHub Actions for accurate code coverage reporting

GitHub’s recent incident is every engineer’s nightmare: ✅ CI passed ✅ PR approved ✅ Merge successful …and the wrong code still landed in main. On April 23, GitHub confirmed that a merge queue issue affected 2,092 pull requests across 658 repositories, producing incorrect commits and silently reverting code in some cases. Good reminder that “all checks passed” doesn’t always mean “everything is correct”. #GitHub #SoftwareEngineering #DevOps #CodingLife

Even the giants have "off" days: Lessons from GitHub’s Merge Queue regression. GitHub recently confirmed a bug where roughly 2,800 pull requests were merged from the wrong base state, unintentionally reverting previous changes. While 0.07% sounds small, in production, "small" percentages can mean major downtime. Key Takeaways for Teams: 1)Automated Testing is King: GitHub is already expanding test coverage for merge operations. 2)Trust, but Verify: Always keep an eye on your branch history after a merge, especially when using automated queues. 3)Transparency Wins: Kudos to Kyle Daigle and the GitHub team for the quick RCA (Root Cause Analysis) and direct outreach to affected users. Have you ever encountered a "silent revert" in your workflow? How does your team guard against tool-level regressions? #GitHub #DevOps #SoftwareEngineering #CI/CD #TechNews

50 reruns for GitHub Actions workflows feels a bit tight, doesn't it? Makes you really think about why a workflow failed in the first place. Time to get serious about debugging! #DevOps #CI/CD

🚀 Scaling on GitHub: From Script to Enterprise Moving from a solo project to a large-scale enterprise environment isn’t just about more code—it’s about managing complexity. When hundreds of developers contribute, "git push" isn't enough. You need system-level governance. Here are the 10 pillars of GitHub at scale: Structure: Choose between a Monorepo (unified flow) or Polyrepos (team independence). Storage: Use Git LFS to keep your repository slim by offloading large binary files. Gates: Implement Branch Protection—no code hits production without passing CI/CD. Ownership: Define a CODEOWNERS file to automate review assignments to the right experts. Governance: Use Rulesets to apply security guardrails across every repo in your organization. CI/CD: Scale your automation with Matrix Builds to test multiple OS versions simultaneously. Performance: Deploy Self-hosted Runners for faster, more secure automation pipelines. Security: Leverage Dependabot and Secret Scanning to catch vulnerabilities before they’re exploited. Analysis: Use CodeQL to treat your code as data and find deep-seated logic flaws. Roadmaps: Align your team with GitHub Projects (v2) for high-level visibility beyond just code. The goal? Shift from "writing code" to "building systems." 🛠️ #DevOps #DevSecOps #GitHub #SoftwareEngineering #CloudNative #SystemDesign #OpenSource

Let's compare notes! What does your GitOps pipeline look like? I created this end-to-end flow diagram to visualize a canonical GitHub-to-ArgoCD setup, from developer commit to live pods in a Kubernetes cluster. I love how it makes the 'Reconciliation Loop' clear. My question for the community is: Which part of this pipeline has been the biggest challenge for your team? 1. Getting buy-in for GitOps? 2. Setting up the CI pipeline effectively? 3. Managing secrets in GitOps repos? 4. Optimizing the ArgoCD sync performance? Let me know in the comments! Let's learn from each other's experiences. #DevOpsCommunity #KubernetesCommunity #GitOpsChallenge #CloudNative #TechDiscussion"

We cut our deployment time from 47 minutes to 9 minutes using GitHub Actions. Here is what actually moved the needle. Not the flashy stuff. The boring stuff. 1. We stopped running the full test suite on every commit. Using pytest -k with changed-file detection, we ran only relevant tests. Saved ~11 minutes immediately. 2. We parallelised Docker layer caching properly. We were using cache, but pulls were still sequential in our workflow. Fixing that shaved off another 6–7 minutes. 3. We removed a manual approval gate that had been sitting in our pipeline since a production incident in 2022. No one on the team of 5 engineers could explain why it still existed. 4. We built a shared base image for our microservices instead of each service installing the same ~350MB of dependencies separately. The bottleneck in your pipeline is almost never where you think it is. Profile it first. Then fix it. What is the biggest time sink in your current pipeline? #CICD #DevOps #PlatformEngineering #GitHubActions #Docker

GitHub Branch Protection: Advanced Rules for Status Check Dependencies Master advanced branch protection configurations that go beyond basic reviews. Learn to set up dependent status checks, automatic review dismissal, and linear history enforcement for enterprise-grade code quality control. Read the full how-to guide: https://lnkd.in/gB3fSePc #ITTips #Productivity #DevOps #GitHub #TechTips #OpenSource #SoftwareDevelopment #BranchProtection #CodeQuality #GitWorkflow

🚨 Issues with #GitHub today? We’re seeing instability across the platform: ❌ Push & pull delays ❌ Pull Requests not loading ❌ Actions (CI/CD) failing or stuck ❌ Overall slow performance This is not a local issue — it’s affecting multiple environments. 💡 What I did (and what I recommend): I moved to running my own Git server using Gitea Open Source — and honestly, this is something more teams should consider. https://git.xdeye.com/ 👉 Here’s the practical advice: ✔️ Keep a self-hosted Git backup (Gitea / GitLab / bare repo). ✔️ Push your code to multiple remotes (GitHub + your own server). ✔️ Don’t depend fully on GitHub Actions — have manual or server-based deployment ready. ✔️ Keep production deployment independent from third-party outages. ✔️ Automate locally or on your own server where possible. Now my workflow is: Local → self-hosted Git → live servers GitHub is secondary, not critical ⚠️ With the growing use of AI tools and third-party automation inside CI/CD pipelines, complexity and risk are increasing. When one piece fails, everything can break. Better to stay in control. How are you handling redundancy in your Git workflow? #GitHub #DevOps #SelfHosted #Gitea #CI #CD #Security #ITInfrastructure

Good Friday is a day of rest — your deployments deserve one too. While your team takes a well-earned break this holiday weekend, NoShip keeps your codebase safe with automated code freezes. Set up recurring freeze schedules so merges are blocked before anyone even thinks about pushing to prod on a long weekend. Because the only thing that should be rising this Easter weekend is your uptime. #GoodFriday #Easter #DevOps #GitHub #CodeFreeze #SRE #PlatformEngineering #DeploymentSafety #EngineeringLeadership

"I want to code. And I can't code with GitHub anymore." That's Mitchell Hashimoto. GitHub user #1299. The man who built Terraform and Vagrant. After 18 years — he's moving Ghostty off GitHub. And I don't blame him. For a month he kept a journal. Every day GitHub disrupted his work, he marked an X. Almost every day had one. Then April 23: a squash merge bug corrupted 658 repos and 2,092 PRs. That's not downtime. That's data loss. Then April 27: All of GitHub — search, Issues, PRs, Projects — went completely dark. GitHub's CTO apologized. Said they now need 30× capacity. February alone had 37 platform incidents. Here's what nobody's saying: GitHub is bending under the weight of agentic AI. Copilot sessions. Parallel agents. Millions of automated calls per minute. The platform was never designed for this. And it's cracking. When the person who defined modern DevOps infrastructure says GitHub is "no longer for serious work" — that's not a hot take. That's a warning. Where do you go when GitHub goes down? 👇 #GitHub #OpenSource #Ghostty #Developers #DevTools #SoftwareEngineering #Tech #BuildInPublic