How to use Argo CD Agent with OpenShift GitOps

Tired of wondering what actually gets deployed in software development? 💡 It's the Artifacts! We break down the critical role of these essential, immutable, and versioned outputs that power Continuous Delivery (CI/CD) from code to production. Artifacts are the unsung heroes of modern deployment. Learn why they are so fundamental to DevOps in this short video! 👇 ➡️ Watch now: https://lnkd.in/gyDZ2NbQ #DevOps #CI_CD #Artifacts #SoftwareEngineering #ContinuousDelivery

🚀 Just wrapped up an exciting DevOps architecture project! I recently designed and implemented a complete GitOps-based CI/CD pipeline for a client — from developer workflow automation to observability and security — all visualized in this architecture diagram 👇 🧩 Key highlights: GitHub Actions for CI — automating build and image publishing to ACR Argo CD for GitOps-based continuous deployment Prometheus + Grafana + Loki + Fluent Bit for observability Cert-Manager + Let’s Encrypt for automated TLS management RBAC & GitOps access control for secure and auditable operations Slack integration for real-time pipeline and deployment updates The result: faster deployments, stronger visibility, and more reliable releases — all with minimal manual intervention. Building this kind of ecosystem that ties together CI/CD, monitoring, and security is always rewarding — it turns DevOps from a process into a culture of confidence. 🔧💙 #DevOps #GitOps #ArgoCD #Kubernetes #CI_CD #Observability #InfrastructureAsCode #Automation

🚨 Life-Saving Kubernetes Commands Every DevOps Engineer Must Know! Bookmark this for the future. 1. Context & Namespace Discipline (InfraThrone Rule #1) kubectl config get-contexts kubectl config use-context <elite-cluster> kubectl config set-context --current --namespace=InfraThrone 2. Node & Cluster Health kubectl get nodes -o wide kubectl top nodes kubectl top pods -n infrathrone kubectl get events -n infrathrone --sort-by=.lastTimestamp | tail -n 50 3. Pod Crash / Restart Chaos kubectl describe pod <elite-pod> -n infrathrone kubectl logs <elite-pod> -c <container> --previous kubectl exec -it <elite-pod> -c <container> -- bash 4. Service & Networking Sanity kubectl get svc -n infrathrone -o wide kubectl describe svc <elite-svc> -n infrathrone kubectl get endpoints <elite-svc> -n infrathrone kubectl exec -it <elite-pod> -n infrathrone -- curl -v <elite-svc>:<port> 5. The Elite Recovery Edge kubectl get --raw='/readyz?verbose' kubectl drain <node> --ignore-daemonsets kubectl cordon <node> Takeaway: These aren’t just commands. They’re war-room survival skills. Use them until they become muscle memory. 📌 Want the full Kubernetes troubleshooting guide with 50+ real commands and scenarios? Comment “send” and repost this. I’ll DM you the full playbook. #DevOps #Kubernetes #SRE #Troubleshooting #InfraThrone #RCADrills

🚨 Life-Saving Kubernetes Commands Every DevOps Engineer Must Know! Bookmark this for the future. 1. Context & Namespace Discipline (InfraThrone Rule #1) kubectl config get-contexts kubectl config use-context <elite-cluster> kubectl config set-context --current --namespace=InfraThrone 2. Node & Cluster Health kubectl get nodes -o wide kubectl top nodes kubectl top pods -n infrathrone kubectl get events -n infrathrone --sort-by=.lastTimestamp | tail -n 50 3. Pod Crash / Restart Chaos kubectl describe pod <elite-pod> -n infrathrone kubectl logs <elite-pod> -c <container> --previous kubectl exec -it <elite-pod> -c <container> -- bash 4. Service & Networking Sanity kubectl get svc -n infrathrone -o wide kubectl describe svc <elite-svc> -n infrathrone kubectl get endpoints <elite-svc> -n infrathrone kubectl exec -it <elite-pod> -n infrathrone -- curl -v <elite-svc>:<port> 5. The Elite Recovery Edge kubectl get --raw='/readyz?verbose' kubectl drain <node> --ignore-daemonsets kubectl cordon <node> Takeaway: These aren’t just commands. They’re war-room survival skills. Use them until they become muscle memory. 📌 Want the full Kubernetes troubleshooting guide with 50+ real commands and scenarios? Comment “send” and repost this. I’ll DM you the full playbook. #DevOps #Kubernetes #SRE #Troubleshooting #InfraThrone #RCADrills

Containers are the backbone of modern infrastructure, and if you’re still only using Docker, it’s time to level up. I’ve put together comprehensive notes on Podman a daemonless, rootless container engine that is becoming a favorite for enterprise DevOps and secure production workloads. 👨💻 This guide covers everything from installation to running containers, creating pods, building images, integrating Podman with Kubernetes, and even using it inside CI/CD pipelines. I’ve also included security best practices, podman-compose examples, and hands-on exercises so you can practice and build a portfolio-ready project. Whether you’re preparing for a DevOps/SRE interview or looking to improve your container workflow, mastering Podman will give you an edge. These notes are designed to be job-oriented and practical helping you become the engineer that teams trust to ship secure, production-grade containers. Get your hands on it, experiment with rootless containers, and export your pods straight to Kubernetes this is how modern DevOps is done. #DevOps #Containers #Kubernetes #CloudEngineering

🚀 Demystifying Kubernetes Architecture 🐳☸️ Kubernetes (K8s) powers modern container orchestration, and this diagram is a simple breakdown of how it all works: ✨ 𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐏𝐥𝐚𝐧𝐞 – The brain of the cluster, making scheduling and scaling decisions. 🖥️ 𝐖𝐨𝐫𝐤𝐞𝐫 𝐍𝐨𝐝𝐞𝐬 – Physical or virtual machines that actually run workloads. 📦 𝐏𝐨𝐝𝐬 – The smallest deployable units, each containing one or more containers. 🔄 𝐊𝐮𝐛𝐞𝐥𝐞𝐭 & 𝐊𝐮𝐛𝐞-𝐩𝐫𝐨𝐱𝐲 – Ensure communication between nodes and handle network traffic. 🐳 𝐃𝐨𝐜𝐤𝐞𝐫 (or another container engine) – Runs on each worker node to host containers 👉 In short: 🔹 Control Plane = 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐌𝐚𝐤𝐞𝐫 🔹 Worker Nodes = 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧 𝐏𝐨𝐰𝐞𝐫 🔹 Pods = 𝐘𝐨𝐮𝐫 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐢𝐧 𝐀𝐜𝐭𝐢𝐨𝐧 Kubernetes may look complex at first glance, but breaking it down makes it much more approachable! 💡 💬 Have you worked with Kubernetes yet? What’s been your biggest learning curve with it? #Kubernetes #CloudComputing #DevOps #Containers #Microservices

🚨 Life-Saving Docker Commands Every DevOps Engineer Must Know Bookmark this before your next production outage. 1. Image & Container Discipline docker images   docker ps -a   docker rm -f <container_id>   docker rmi <image_id> 2. Debugging a Broken Container docker logs -f <container_id>   docker exec -it <container_id> /bin/bash   docker inspect <container_id>   docker diff <container_id> 3. Networking Chaos docker network ls   docker network inspect <network_name>   docker run -it --net=<network_name> busybox ping <service> 4. Volume & Storage Sanity docker volume ls   docker volume inspect <volume>   docker system df   docker system prune -a 5. The Elite Recovery Edge docker commit <container_id> <image_name>   docker save <image> > backup.tar   docker load < backup.tar>   docker update --restart=always <container_id> Takeaway: Docker isn’t just about running docker run. In production chaos, these commands are the difference between panic and control. 📌 Want the full Docker troubleshooting playbook with 50+ real-world RCA drills? ⭕️ Repost this and I’ll DM you the guide. #DevOps #Docker #SRE #Troubleshooting #InfraThrone #Containers

Today, I explored the core concepts of Kubernetes (K8s)! Understanding the Kubernetes Architecture helped me see how the Master Node and Worker Nodes work together to manage containerized applications efficiently. 🧩 The Master Node handles cluster control — scheduling, API management, and maintaining the desired state. ⚙️ The Worker Nodes run the actual application pods through kubelet and k-proxy, ensuring everything stays connected and running. This deep dive gave me a clearer view of how Kubernetes automates deployment, scaling, and management — truly the backbone of modern DevOps! Big shoutout to Shubham Londhe — I followed one of his 📺 video, which helped me complete this component! TrainWithShubham #Kubernetes #DevOps #CloudComputing #Containers #K8s #TechInnovation #CloudNative #K8sCommunity #TechTrends #Automation

🐳 Understanding Docker Architecture Ever wondered what makes Docker such a powerful tool for developers and DevOps engineers? Here’s a breakdown of the key components that make containerization possible 👇 🔹 Docker Engine – The core that builds and runs containers. 🔹 Docker Daemon – Manages Docker objects like images, containers, and networks. 🔹 Docker Client – The interface developers use to communicate with the daemon. 🔹 Docker Images – Blueprints containing everything needed to run your application. 🔹 Docker Containers – Lightweight, isolated, and portable runtime environments. 🔹 Docker Registry (e.g., Docker Hub) – A repository to store and share images. 💡 In short: Docker’s architecture provides consistency, scalability, and efficiency across environments — from development to production. #Docker #DevOps #Containers #CloudComputing #Microservices #SoftwareEngineering #DockerArchitecture #CICD #CloudNative #TechInsights

What if your perfectly rendered Helm chart still breaks in production? I spent a morning debugging a CI pipeline that failed during a Helm deployment, even though `helm template .` generated flawless YAML. My role was to automate pre-deployment validation, and I assumed that if the template rendered, it was valid. The application was a standard Go microservice, using Helm v3.10 to deploy to an EKS cluster running Kubernetes v1.27. The root cause was a subtle but critical difference in Helm commands. `helm template` is a pure client-side action; it renders manifests but has no awareness of the target cluster's state or capabilities. Our chart referenced an Ingress API version that our new EKS cluster didn't support. `helm install --dry-run`, on the other hand, actually communicates with the Kubernetes API server to validate the rendered manifests against the cluster's available API versions. The failure was instant once we used the right command. Here's the actionable fix for reliable Helm CI: 1. Use `helm lint` for static analysis and best practice checks. 2. Use `helm template` to quickly inspect the generated YAML for correctness. 3. Use `helm install <release> . --dry-run` as the final gate. This is the only command that truly validates the chart against a live cluster's API. 💡 This experience was a lesson in the difference between static rendering and server-side validation. Never assume a client-side check is a substitute for a true pre-flight check against the target environment. How do you approach Helm chart validation in your pipelines before a real deployment? #Helm #Kubernetes #DevOps #PlatformEngineering #CI #LearningInPublic