GitHub's paradox: using its own tools for backup and recovery

I started by building the infrastructure for my To-Do App using Terraform and Ansible, and then added a full CI/CD pipeline using GitHub Actions and Docker. What it does: First, Terraform creates the server (VPC, Subnets, ElasticIP, Security Groups, etc) and network automatically. Then Ansible sets up the server, Git Runner, installs Docker, and prepares the environment. After that, CI/CD handles the deployment. When I push code to GitHub main branch, GitHub Actions builds the app, creates a Docker image, and pushes it to Docker Hub. After that the server pulls the latest image, stops the old container, and starts the new one automatically. It also keeps only the latest 5 images to save space. Why this is useful: This removes manual work, reduces errors, and makes deployment faster and more reliable. What I learned: This project helped me understand how infrastructure setup and deployment automation work together in real DevOps. Special thanks to my supervisor Sampath D. for the guidance and support. #DevOps #Terraform #Ansible #Docker #GitHubActions #CICD #InfrastructureAsCode #CloudComputing #Automation #SoftwareEngineering #DevOpsJourney #LearningByDoing #TechProject #PortfolioProject #FutureEngineer #AWS #CloudArchitecture #OpenToWork #ITStudent #ContinuousDeployment #antlerfoundry

Hey Techies 👋, DevOps Reality Check When even GitHub becomes unreachable.... Today’s task looked simple push code, trigger my Jenkins pipeline, and continue working on my Docker setup. But instead, I hit this: 👉 fatal: unable to access 'https://github.com/...' 👉 Could not resolve host: github.com At first, it felt like a blocker. But in DevOps, these “small” errors often teach the biggest lessons. After digging deeper, I realized the issue wasn’t with Git or Jenkins it was a DNS/network issue on my remote server (via SSH). How I solved it: - Checked internet connectivity on the remote machine - Verified DNS configuration in /etc/resolv.conf - Restarted network services - Ensured proper nameserver (like 8.8.8.8) was set - Re-tested using ping github.com And finally… connection restored, code pushed, pipeline back on track Key takeaway: 𝐍𝐨 𝐦𝐚𝐭𝐭𝐞𝐫 𝐡𝐨𝐰 𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐲𝐨𝐮𝐫 𝐂𝐈/𝐂𝐃 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐢𝐬, 𝐞𝐯𝐞𝐫𝐲𝐭𝐡𝐢𝐧𝐠 𝐝𝐞𝐩𝐞𝐧𝐝𝐬 𝐨𝐧 𝐭𝐡𝐞 𝐛𝐚𝐬𝐢𝐜𝐬 𝐧𝐞𝐭𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐚𝐧𝐝 𝐜𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐯𝐢𝐭𝐲. This was a reminder that DevOps isn’t just automation… It’s also patience, debugging, and understanding systems from the ground up. Have you ever been stuck because of something as simple as DNS? #DevOps #Jenkins #Docker #GitHub #CICD #Troubleshooting #LearningInPublic #WomenInTech #CloudComputing

Talked to a Director of Platform Engineering at an enterprise logistics company last week. Their GitHub Actions bill was $34K/month. I asked what percentage was test execution. He didn't know. So we looked. 72% of their CI minutes were test runs. Not builds. Not linting. Not deploys. Tests. Running on GitHub-hosted runners at $0.008/minute against infrastructure that looked nothing like production. Here's the rule of thumb I keep seeing validated: If your test step takes longer than your build step, your CI tool is doing someone else's job. GitHub Actions is excellent at orchestrating builds and deployments. But it was never designed to run 2,000 integration tests across 6 microservices with real database connections, service mesh routing, and network policies. At Testkube, this is the pattern we see constantly: teams spending 60-70% of their CI budget on test execution that belongs inside the cluster, not in ephemeral runners. That Director's team moved test execution into Kubernetes. Same tests, same assertions. CI minutes dropped 68%. Tests actually hit real infrastructure. Failures meant something. Stop using your CI as a test lab. It wasn't built for it. #Kubernetes #GitHubActions #DevOps #PlatformEngineering #CICD

GitHub just announced a complete architectural rebuild of Actions—and the reason why matters more than the features themselves. The catalyst? Agentic development. 71 million job executions later, it became clear: the infrastructure wasn't built for how we're working in 2025. AI-powered workflows, GitHub Copilot agents, and autonomous DevOps pipelines demanded a fundamental rethink. Here's what the rebuild enables: → YAML anchors for configuration reuse (finally matching GitLab and Bitbucket) → 10-level reusable workflow nesting with federated credentials → Each workflow now carries its own identity—enabling secure credential scaling without duplicating secrets → Complete removal of the 10GB cache limit The strategic insight here: Reusable workflows with federated credentials allow centralized deployment pipelines where downstream teams consume workflows without managing separate credentials. That's a massive win for enterprise security and governance. But the bigger story is this: Agentic DevOps isn't just changing how we write code. It's forcing us to reimagine our entire infrastructure stack—compute, caching, identity, and orchestration. GitHub is preparing for a world where AI agents run your pipelines. Are your systems ready? More details: https://lnkd.in/gDhG2kJF #AgenticDevOps #GitHubActions #DevOps

Recently came across something genuinely useful for anyone working with containers, Kubernetes, or just trying to get better at debugging in real environments — iximiuz Labs Playgrounds. https://lnkd.in/eHeZg8Ua What I like about it — it’s not another “watch this tutorial” platform. You actually get hands-on labs where things break, and you have to figure them out. It feels much closer to real-life scenarios: Debugging container networking issues Understanding how Linux namespaces really work Troubleshooting Kubernetes behavior without guessing Learning by doing, not by memorizing As someone working in DevOps, this kind of practice is way more valuable than just reading docs or watching videos. It forces you to think the way you would in production. If you're preparing for roles like Platform Engineer / DevOps / SRE — or even certifications — this is definitely worth checking out. Curious if anyone here has already tried it? What was your experience? #DevOps #Kubernetes #Containers #SRE #LearningByDoing #PlatformEngineering

There is a “golden path” to becoming a Kubernetes engineer. But most people never follow it. Instead, they: • Jump between tools • Chase random certifications • Get overwhelmed Here’s the problem 👇 Kubernetes is NOT hard. Lack of direction is. Here’s the golden path I’ve seen work repeatedly 👇 Step 1 → Foundation 🧱 • Linux basics • Containers (Docker) Step 2 → Developer mindset 💻 • CKAD • Application deployment • Configs & debugging Step 3 → DevOps mindset ☸️ • CKA • Cluster management • Networking Step 4 → Specialization 🔐 • CKS • Security + production readiness That’s it. No shortcuts. No hacks. Most people fail because: ❌ They try to learn everything at once ✅ Instead of following a sequence Top engineers do this differently: • Build layer by layer • Focus on real skills • Specialize smartly The result? 👉 Faster growth 👉 Better opportunities 👉 Higher income So ask yourself: Are you following a path… or just exploring randomly? Let’s discuss 👇 💡 Comment “K8S” and I’ll share a complete golden path roadmap + resources. #Kubernetes #CKA #CKAD #CKS #DevOps #CloudComputing #KubernetesEngineer #CloudCareers #DevOpsEngineer #TechCareers #CloudGuru #CareerGrowth #LinuxFoundation #CloudSkills 🚀

A lot of developers rely on GitHub every single day, but the moment you ask them how it truly differs from GitLab, the answers often get blurry. And honestly, I understand why, on la surface they look similar, yet they don’t serve the same vision at all. GitHub has become the place where the world writes code together. Backed by Microsoft and fueled by a massive open-source community, it’s built for speed, simplicity, and collaboration. Actions, Codespaces, Dependabot… everything is designed to help teams move quickly and stay focused on building. GitLab, on the other hand, follows a completely different philosophy. It’s not just a code platform, it’s a full DevSecOps environment. CI/CD is built-in, security tools are native, governance is centralized, and you can even self-host it with the open-source edition. Many companies choose it because they want one platform to manage everything from planning to deployment. So the question isn’t really “which one is better?”. It’s more like “which vision matches the way you work?”. One focuses on velocity and massive adoption. The other focuses on deep integration and full end-to-end control. If you’ve used either platform in your projects, I’d really love to hear your experience. What actually makes a difference in your daily workflow? And what would you pick again if you had to start from scratch? Your insights will definitely help others who are still trying to choose the right tool. #GitHub #GitLab #DevOps #DevSecOps

A lot of developers rely on GitHub every single day, but the moment you ask them how it truly differs from GitLab, the answers often get blurry. And honestly, I understand why, on la surface they look similar, yet they don’t serve the same vision at all. GitHub has become the place where the world writes code together. Backed by Microsoft and fueled by a massive open-source community, it’s built for speed, simplicity, and collaboration. Actions, Codespaces, Dependabot… everything is designed to help teams move quickly and stay focused on building. GitLab, on the other hand, follows a completely different philosophy. It’s not just a code platform, it’s a full DevSecOps environment. CI/CD is built-in, security tools are native, governance is centralized, and you can even self-host it with the open-source edition. Many companies choose it because they want one platform to manage everything from planning to deployment. So the question isn’t really “which one is better?”. It’s more like “which vision matches the way you work?”. One focuses on velocity and massive adoption. The other focuses on deep integration and full end-to-end control. If you’ve used either platform in your projects, I’d really love to hear your experience. What actually makes a difference in your daily workflow? And what would you pick again if you had to start from scratch? Your insights will definitely help others who are still trying to choose the right tool. #GitHub #GitLab #DevOps #DevSecOps

🔐 Secure Your Bitbucket → GitHub Migration Migrating repositories is only the first step. The real challenge comes next: securing project dependencies without breaking CI pipelines. In our latest blog, we break down how to: ✔️ Eliminate hardcoded credentials ✔️ Move to secure SSH-based access ✔️ Keep builds stable after the switch to GitHub Actions 👉 Read the full guide: https://lnkd.in/dUe5B7y5 If you missed Part 1, start here: https://lnkd.in/dd6WxCpZ ✍️ Tyurkiyan Mehmedova, DevOps Engineer, ITGix Ltd #devops #githubactions #bitbucket #cicd #security #platformengineering

How i built a Senior Level Infrastructure Career: The 8 Month Execution Blueprint. Body: Stop getting stuck in the what to learn next trap, The real secret to mastering DevOps and Infrastructure isn't the tools it's the systematic approach to execution. I mapped out my journey from beginner to senior in 8 focused months. If u are ready to build real world skills this is the blueprint 👇 - The 8 Month Execution Plan: • Months 1-2 : Linux Mastery Deep dive into the CLI. Master file systems, permissions, and command efficiency. focus understanding the OS. • Month 3: Automation Learn Bash scripting. Start automating repetitive tasks and setting up your first cron jobs. • Month 4: Networking Core. Solidify TCP/IP , DNS, HTTP and how services communicate across a network. • Month 5: Version Control and CI/CD, Master Git, and build your first automated pipeline using GitHub actions or jenkins. • Months 6-8: Containers & Cloud Dive into Docker fundamentals, then scale up to deploying applications on Kubernetes within a cloud environment ( AWS/Azure basics) • The Real Secret: it's not about memorizing commands it's about developing a powerful problem solving mindset Focus on why u are using a tool not just how to type the command. Senior Tip: Don't wait for perfection. Start messy. get feedback. Iterate fast. That cycle of messy ~ Learn ~ Repeat is the only path to senior level expertise. #DevOps #Linux #CareerGrowth #Tech #Docker #Kubernetes #Infrastructure #TechSkills