Contributing to GitLab's Open-Source Codebase through CodePath x GitLab

🔗 https://lnkd.in/dfAf6idu I just published a new post about building a frontend project with Docker from scratch and truly understanding what’s happening under the hood. Instead of just running commands, this guide walks through the fundamentals from creating your own Dockerfile to understanding how images and containers actually work, helping you build a more solid mental model of Docker. If you want to stop treating Docker like a black box and start using it with confidence in your projects, this is definitely worth checking out. #docker #devops #softwarearchitecture #coding

Software development has many frustrations. But few things are as humbling as code that works perfectly in one place and completely falls apart in another. Different operating system. Wrong library version. A missing dependency nobody mentioned. And the most common advice you will get is "just set up your machine exactly like mine." That is not a solution. This is the problem Docker was built to solve. Instead of shipping just your code, Docker lets you ship your code and the entire environment it needs to run, packed together in one portable package called a container. It does not matter what machine it lands on. It just works. Every single time. No more broken setups. No more environment issues. No more spending two hours debugging before writing a single line of code. #Docker #DevOps #LearningInPublic #Containers #SoftwareEngineering #TechJourney #TechCommunity

Knowledge sharing is at the heart of great engineering. At Orlando Code Camp, Xebia experts Allen Conway and Randy Pagels will share real-world lessons on building modern applications and securing code with AI. From Angular PWAs to GitHub Advanced Security, these sessions go beyond theory into what actually works in production. Join us April 11 in Sanford, FL. #OrlandoCodeCamp #SoftwareEngineering #GitHub #AI #DevOps

Most developers use Docker daily — but how many actually know what's happening under the hood? Here are the 6 core components that make Docker work: 🖼️ Images — Read-only blueprints containing your app code, libraries & dependencies 📦 Containers — Running instances of images. Isolated, lightweight, self-contained ⚙️ Docker Engine — The runtime: daemon + REST API + CLI working together 📄 Dockerfile — A script that tells Docker exactly how to build your image 🗄️ Volumes — Persistent storage that survives container restarts 🔧 Docker Daemon — The background brain managing all Docker objects Understanding these isn't just theory — it makes you better at debugging, optimizing builds, and writing cleaner pipelines. Which one tripped you up the most when you first started? Drop it below 👇 #Docker #DevOps #WebDevelopment #FullStack #100DaysOfCode #MuhammadAzhanBaig #ZState

Docker week was humbling. I built the container. It ran. But something was off, the image wasn't right and I had to go back and figure out why. That back-and-forth taught me more than if it had worked the first time. But here's why Docker even matters: Ever sent your code to someone and they get errors you never saw? Different OS, different versions, different environments, suddenly your code is broken on their machine. Docker fixes that. You package the code AND everything it needs into a container. They run it, it works. Same every time, everywhere. By the end of the week I'd covered: → Writing Dockerfiles and building images → Pushing images to Docker Hub → Anonymous volumes & bind mounts → Multi-stage Dockerfiles → Docker Compose to wire it all together And yes, eventually got a React app running cleanly in a container at localhost. Worth it. Docker is one of those tools that makes you feel stupid before it makes you feel powerful. #Docker #DevOps #Containers #LearningInPublic #CloudComputing

Stop getting stuck with "stale" code in Kubernetes! 🐳 ⛴️ One of the most common "why isn't my code updating?" bugs in K8s comes down to a simple setting: imagePullPolicy: IfNotPresent. If you're using mutable tags (like :latest or :dev), here’s what happens: - You push a new image to the registry. - You restart your Pod. - Kubernetes sees the tag already exists on the node. - It skips the pull and runs your old code. 🤦♂️ Here is the quick fix guide: ✅ Use imagePullPolicy: Always for development. It doesn't actually download the whole image every time—it just checks the registry for a new digest. If nothing changed, it uses the cache. ✅ Use Immutable Digests in Production. Instead of my-app:v1, use my-app@sha256:[hash]. This ensures every single node is running the exact same bits, regardless of the pull policy. ✅ Use Versioned Tags. Avoid :latest. Use unique tags like :v1.0.1 or the Git commit hash. When the tag changes, IfNotPresent works perfectly because the new tag won't be on the node yet. Don't let a cached image trick you into thinking your bug fix didn't work! #Kubernetes #DevOps #CloudNative #Docker #SoftwareEngineering #K8sTips

Nested Contianers - The penultimate scene! In the last post - https://lnkd.in/ewJBedhd - we have seen how Kubedock saved the world, even though by faking Docker APIs and make them available to other processes, So they think "I’m talking to Docker" while they actually talk to Kubedock. Great Idea, i'm still amazed how would someone think of this, but "Yes" we all did nice fake things from mockup services "microcks" all the way to faking kubernetes "KWOK". Before we explore another important option - user namespaces [ https://lnkd.in/egqMy6Mh ] - to run nested containers in OpenShift DevSpaces we have to recall the following : 1 - We - the developers - want an automated unit and integration testing experience inside our devworkspaces. 2 - Unit testing in most frameworks - like quarkus and spring boot - require docker to be available to start test containers. 3 - Again, we don't want to deal with docker socket and how to configure Podman to expose a Docker-compatible socket, I just want my unit testing use cases to run. 4 - Yet, We from time to time would like to run some other containers for experimentation and not only for testing scenarios, so please don't limit me to unit and integration testing scenarios. Because of the above 4 reasons - and some more, we started with Kuedock and we - the development community - might favor this approach over the user namesapce. In the next post we will discuss in details the user namespace option with a quick demo to show how it works. You can get yourseld familiar with the concept of user namespace in DevSpaces documentation https://lnkd.in/e-G3R3aQ Finally, look at the beauty of how Kubedock was integrated into universal developer image UDI in the official dockerfile on redhat catalog: https://lnkd.in/eK2u5-yK #redhat #openshift #devspaces #kubedock #nested #containers

Sveltos v1.8.0 is out. Three new features, handful number of bug fixes, each targeting a specific operational gap. 1. 𝗚𝗶𝘁𝗢𝗽𝘀-𝗳𝗿𝗶𝗲𝗻𝗱𝗹𝘆 𝗸𝘂𝗯𝗲𝗰𝗼𝗻𝗳𝗶𝗴 𝗿𝗲𝗻𝗲𝘄𝗮𝗹 When Sveltos rotated a cluster's kubeconfig, it wrote a new key (`re-kubeconfig`) and updated `SveltosCluster.spec`. GitOps tools like Flux or ArgoCD saw this as live-state drift from the Git source. The fix is a new field: 𝘴𝘱𝘦𝘤:  𝘵𝘰𝘬𝘦𝘯𝘙𝘦𝘲𝘶𝘦𝘴𝘵𝘙𝘦𝘯𝘦𝘸𝘢𝘭𝘖𝘱𝘵𝘪𝘰𝘯:  𝘬𝘶𝘣𝘦𝘤𝘰𝘯𝘧𝘪𝘨𝘒𝘦𝘺𝘕𝘢𝘮𝘦: 𝘬𝘶𝘣𝘦𝘤𝘰𝘯𝘧𝘪𝘨 # 𝘴𝘢𝘮𝘦 Set 𝘬𝘶𝘣𝘦𝘤𝘰𝘯𝘧𝘪𝘨𝘒𝘦𝘺𝘕𝘢𝘮𝘦 to the existing key name and Sveltos overwrites the Secret in-place, skipping the spec update. Live state and Git stay aligned 2. 𝗦𝗸𝗶𝗽 𝗻𝗮𝗺𝗲𝘀𝗽𝗮𝗰𝗲 𝗰𝗿𝗲𝗮𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗿𝗲𝘀𝘁𝗿𝗶𝗰𝘁𝗲𝗱 𝗥𝗕𝗔𝗖 In multi-tenant clusters where Sveltos operates without cluster-wide Namespace permissions, the pre-flight namespace check would fail even when the namespace already existed. 𝘚𝘬𝘪𝘱𝘕𝘢𝘮𝘦𝘴𝘱𝘢𝘤𝘦𝘊𝘳𝘦𝘢𝘵𝘪𝘰𝘯: 𝘵𝘳𝘶𝘦 on 𝘗𝘰𝘭𝘪𝘤𝘺𝘙𝘦𝘧s and 𝘒𝘶𝘴𝘵𝘰𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯𝘙𝘦𝘧𝘴 bypasses that check and deploys directly into pre-provisioned namespaces. 3. 𝗡𝗮𝘁𝗶𝘃𝗲 𝗛𝗲𝗹𝗺 𝘁𝗲𝘀𝘁 𝗲𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 Helm charts ship with test hooks that authors write precisely to validate a deployment. With 𝘳𝘶𝘯𝘛𝘦𝘴𝘵𝘴: 𝘵𝘳𝘶𝘦 in the chart spec, Sveltos runs those hooks automatically after each successful install or upgrade. Failures surface as deployment failures in ClusterSummary status. 𝗕𝘂𝗴 𝗳𝗶𝘅𝗲𝘀 𝘄𝗼𝗿𝘁𝗵 𝗻𝗼𝘁𝗶𝗻𝗴 Modifying Helm patches no longer goes undetected when chart version and values are unchanged. Sveltos now tracks a hash of the patch set. Failure messages on Helm releases are no longer overwritten before persisting. And manually deleting a ClusterSummary while a cluster is mid-update no longer causes a reconciliation deadlock. Full changelog: https://lnkd.in/d65DAXuA #Kubernetes #MultiCluster #GitOps #PlatformEngineering #Sveltos

🚀 Just launched a fully automated CI/CD pipeline for my Appointment Booking System using GitHub Actions! ✅ All tests passing | ✅ Security scanning | ✅ Docker verified | ✅ 0 manual steps Pipeline runs on every push: • Backend builds & tests • Frontend builds & tests   • Code quality checks • Docker image verification Status: 4m 49s total | 100% Success Rate ✅ Tech: React 19 • Node.js • Docker • GitHub Actions Check it out: https://lnkd.in/g7ZfY5-Z #DevOps #CI/CD #FullStack #GitHub #Docker #SoftwareEngineering 🚀

#100DaysOfDevOps - Day Forty - Six Today I continued working on the GitHub Actions version of my CI pipeline. The focus was on moving from the workflow skeleton into actual execution, one stage at a time, while testing and troubleshooting along the way. What I worked on today: ✅ created the .github/workflows/ci.yaml file ✅ pushed it to GitHub and confirmed the workflow was triggered ✅ verified that the checkout stage worked ✅ observed how GitHub Actions provisions a runner automatically ✅ added the backend test stage ✅ set up Python on the runner ✅ installed pip ✅ confirmed the backend test/lint stage ran successfully After that, I moved into the image build stage and started setting up: Docker-related steps GitHub secrets for Docker authentication environment variables for image names and tags That part came with multiple errors, including: wrong field names wrong action version invalid Docker tag formatting mismatched secret references And honestly, I’m glad it happened that way. Because one thing this journey keeps reinforcing is: CI/CD is not learned by only watching clean demos. It is learned by writing, testing, failing, correcting, and understanding why the workflow failed. So even though the image build stage is still being resolved, today still felt like strong progress because the earlier stages are now working, and the workflow is taking shape properly. Big takeaway: The deeper skill is not avoiding errors, it is learning how to read them and move forward with clarity. YouTube Video Link: https://lnkd.in/eDVKJz8d #DevOps #100DaysOfDevOps #GitHubActions #CICD #ContinuousIntegration #Docker #Automation #GitHub #YAML #PlatformEngineering #CloudEngineering #LearningInPublic #TechdotSam