Docker Compose Debugging: YAML Parsing Error Fix

🐳 Day 66: Docker Command Deep Dive Debugging a messy Docker Compose setup today reminded me why I love this command: docker-compose ps -a Ever been in that situation where you're staring at your screen wondering "what containers did this compose file actually create?" This little gem shows you EVERYTHING - running, stopped, crashed containers - the whole family tree of your compose project. 🎯 Use Cases: Beginner: You ran docker-compose up but some services aren't working. Use this to quickly see which containers failed to start or exited unexpectedly. Pro Level 1: During deployment rollbacks, use this to verify which version of containers are actually running vs what you expected to deploy. Pro Level 2: When inheriting legacy projects, this helps you map the actual container landscape against the docker-compose.yml file to spot any orphaned or missing services. 💡 Pro Tip: Remember "ps = Process Status" and the "-a" means "all" (just like regular docker ps -a). Think of it as your compose project's family photo - everyone's included, even the ones that didn't make it! 📸 The beauty is in the details - you'll see container names, status, ports, and commands all in one clean table. Super handy for those "why isn't this working" moments we all have. What's your go-to debugging command for Docker issues? Drop it in the comments! Tomorrow brings another command worth mastering 🚀 #Docker #DevOps #Containers #DockerCompose #TechTips #Developer My YT channel Link: https://lnkd.in/d99x27ve

🐳 🐙 Docker Compose Tip #54: Preview changes with --dry-run See what Compose will do before it does it! ```bash docker compose up -d --dry-run ``` ``` DRY-RUN MODE - Container myapp-db-1 Running DRY-RUN MODE - Container myapp-web-1 Recreating DRY-RUN MODE - Container myapp-web-1 Recreated ``` Works with many commands: • docker compose down --dry-run • docker compose rm --dry-run • docker compose pull --dry-run Perfect for: • Checking what changed after editing compose.yml • Validating override files before applying • Safe exploration in unfamiliar environments Full guide: https://lnkd.in/eEBNQ4Px #Docker #DockerCompose #Debugging #BestPractices #DevOps

Docker Image Optimisation I've been working on optimising the gatus docker image. The current public image is very well optimised. It uses: Multi stage builds Final image built from scratch Minimal Layers The image size is 74MB In terms of changing the dockerfile there isn't much I can change. However, there were a couple of things I was able to do. When building the binary I added the following options to the build command: -trimpath This removes filesystem paths from the binary -ldfalgs="-s" This omits the symbol table from the binary With these two changes, the image size shrunk to 47MB This shows the importance of understanding the application and how it is built. The most impactful change came from the way the binary is built, not the way the dockerfile is structured. #DevOps #Docker #LearningInPublic #optimisation

🐳 Top Docker Commands Every Developer Should Know If you're working with Docker, mastering a few core commands can make your workflow faster, cleaner, and more efficient. Here are some essential Docker commands every developer should know: 🔹 1. Check Docker Version docker --version 🔹 2. Pull an Image from Docker Hub docker pull nginx 🔹 3. List Images docker images 🔹 4. Run a Container docker run -d -p 3000:3000 node-app 🔹 5. List Running Containers docker ps 🔹 6. List All Containers (including stopped) docker ps -a 🔹 7. Stop a Container docker stop <container_id> 🔹 8. Remove a Container docker rm <container_id> 🔹 9. Remove an Image docker rmi <image_id> 🔹 10. View Logs docker logs <container_id> 🔹 11. Execute Command Inside Container docker exec -it <container_id> bash 🔹 12. Build an Image docker build -t my-app . 🔹 13. Docker Compose Up docker-compose up -d 🔹 14. Docker Compose Down docker-compose down 💡 Pro Tip You don’t need to memorize everything — but knowing these commands can cover 80% of real-world Docker use cases. Mastering Docker CLI is a big step toward becoming a DevOps-ready developer 🚀 #Docker #DevOps #Containerization #WebDevelopment #CloudComputing #CICD #SoftwareEngineering #BackendDevelopment #TechSkills #Programming

I learned something new today!! This diagram helped me understand how modern applications actually move from code → production using tools like Jenkins and Docker. Here’s the flow in simple terms: ▪️ 1. Pull Code Jenkins fetches code from GitHub ▪️ 2. Verify Basic checks to ensure everything is correct ▪️ 3. Build Images Docker builds application images ▪️ 4. Push to DockerHub Images are stored in a central registry ▪️ 5. Deploy Containers are started using Docker Compose ▪️ 6. Cleanup Unused images are removed to save space What I realized: CI/CD is not just automation — it’s about making deployments fast, consistent, and reliable. This is where development meets real-world production systems If you're learning backend or full stack, understanding pipelines like this is a game changer. What part of CI/CD do you find most confusing? 🤔 #DevOps #Jenkins #Docker #CICD #BackendDevelopment #FullStack #SoftwareEngineering #CodingJourney

JSON is great for machines. YAML is great for humans. And developers are stuck in the middle. APIs give you JSON. But real systems often expect YAML: • Kubernetes configs • Docker Compose • CI/CD pipelines So you end up doing this: Copy JSON → find converter → fix formatting → debug weird issues. Because converting isn’t just about syntax. It’s about not breaking meaning. YAML does things differently: • indentation defines structure • some values auto-convert (yes, on, null) • multiline strings behave differently One small mistake — and your config breaks. Silently. So we added a JSON → YAML converter to JSONGate. Paste JSON → get clean, structured YAML: • preserves hierarchy • handles tricky values safely • ready for real-world configs And like everything in JSONGate: No uploads. No backend. Nothing leaves your browser. 👉 https://lnkd.in/dZ3b6bSe Because data conversion isn’t just formatting. It’s trusting that nothing breaks. Curious — have you ever had a YAML config fail because of something “invisible”? #BuildInPublic #JSONGate #DevTools #WebDevelopment #DevOps #Kubernetes #Programming #SoftwareEngineering #DeveloperExperience #IndieHacker

Most Docker tutorials stop at docker run. That’s exactly where production problems begin. I learned this the hard way. A base image CVE sitting in production, not caught by the pipeline, flagged hours later in an audit. The image had been running fine. The vulnerability hadn’t. I just didn’t know. That experience changed how I think about container delivery. It’s not enough to build an image that works. It needs to be minimal, verified, signed, and scanned, before it ever touches a registry. So I built a reference project that codifies exactly that. Here’s what I changed after that audit: Distroless final image. No shell, no package manager, ~4MB. The base image CVE that got us? No longer possible. There’s almost nothing left to exploit. Trivy scans every image before push. The pipeline fails on HIGH/CRITICAL, not a Slack notification you’ll read tomorrow. Not advisory. A hard stop. SBOM generated at build time. Image signed with cosign keyless signing. No private key to manage, signature tied to the GitHub Actions OIDC identity. You can prove exactly what was built and who built it. The CI/CD pipeline does two different things depending on context: On PRs: source scan, build amd64 locally, scan the loaded image. No registry push. No packages: write on untrusted code. On main/tags: multi-arch build, push, scan the exact digest (not the tag, tags are mutable), sign. One deliberate trade-off I documented: Release runs two builds, validation and publish. Slower. But the permission separation is clean, and clean pipelines don’t surprise you at 2am. Every decision has an ADR. Every operational scenario has a runbook entry. Because the person debugging this might be me. → https://lnkd.in/dUMiQCta If you’re building container delivery pipelines, what does your image scanning gate look like? Before push, after push, or both? #Docker #DevOps #CICD #PlatformEngineering #Security #Kubernetes

🚨 Broken GitLab pipelines are a silent productivity killer, engineers context-switch, logs get skimmed, and the same failures resurface week after week. After sitting with this problem long enough, I put together a structured skill template that teaches Claude Code how to diagnose and repair CI/CD failures intelligently: - Keyword-scored symptom matching - Tag-based reference loading - Scaffold scripting - Hook-enforced guardrails All designed so the agent's context stays lean no matter how large your failure database grows. This architecture is deliberately compatible with a self-healing agent loop, where Claude doesn't wait to be asked, it just fixes the pipeline. Something called Remedy is on the horizon, and it should make the "waiting for CI" part of your workflow feel very different. 👀 https://lnkd.in/dKWvbgqz

Docker seems easy… until your container refuses to start. And suddenly, you’re stuck googling errors you don’t even understand. Every beginner goes through this. The problem isn’t Docker. It’s not knowing the right commands at the right time. Here are the must-know Docker CLI commands you’ll use daily: 🔹 Setup & Info • docker --version → Check installation • docker info → System details 🔹 Images • docker pull <image> → Download image • docker images → List images • docker rmi <image> → Remove image 🔹 Containers • docker run <image> → Run container • docker ps → Running containers • docker ps -a → All containers • docker stop <id> → Stop container • docker start <id> → Restart container • docker rm <id> → Delete container 🔹 Debugging (Most Important) • docker logs <id> → Check errors • docker exec -it <id> bash → Enter container • docker inspect <id> → Deep details 👉 You don’t need 100 commands. You need the right 10–15 that actually solve problems. That’s how real devs work. Save this before your next “container not working” moment. Comment DOCKER and I’ll share a printable cheat sheet. Follow for Part 2 (advanced Docker that most beginners skip). #docker #devops #backenddevelopment #softwareengineering #programming #cloudcomputing #developers

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