ROHAN T.’s Post

🚗 “K8s upgrade completed” 😎 Meanwhile… 78 pods are unresponsive If you’ve worked with Kubernetes, you know this feeling. Upgrading clusters sounds simple: ✔ Plan ✔ Execute ✔ Celebrate Reality: ❌ Pods stuck in Pending ❌ CrashLoopBackOff surprises ❌ Services not reachable 💡 Lesson learned: A successful upgrade isn’t just about completion — it’s about stability. 👉 Always: - Check node compatibility - Validate workloads post-upgrade - Monitor logs & events - Have a rollback plan Because in DevOps… “Done” doesn’t mean “Working.” #Kubernetes #DevOps #SRE #CloudComputing #PlatformEngineering #FrontendMedia

Building a practical DevOps pipeline on AWS that keeps things simple, reliable, and scalable. From code commit to deployment, the flow is straightforward — developers push code to repositories, triggering automated pipelines using CodePipeline and CodeBuild. Artifacts are stored in ECR, and deployments are managed seamlessly on EKS using GitOps with FluxCD. What I like about this setup is the clear separation between application code and infrastructure, along with automated, consistent deployments into Kubernetes. It reduces manual effort and helps maintain stability across environments. This kind of architecture is what truly brings DevOps and SRE practices together — automation, reliability, and faster delivery without compromising control. #AWS #DevOps #SRE #Kubernetes #EKS #GitOps #FluxCD #CI_CD #CloudArchitecture

🚀 Kubernetes – Replication Controller Explained In Kubernetes, a Replication Controller plays a crucial role in managing the pod lifecycle by ensuring that the desired number of pod replicas are always running. It automatically maintains the specified number of pods, scaling them up or down whenever required. Instead of manually creating pods repeatedly, using a Replication Controller is considered a best practice for maintaining system reliability and availability. Through this concept, we also understand key configurations like defining replicas, container details (Tomcat), and exposing applications via specific ports. As shown in the diagram on page 3, multiple pod replicas are managed efficiently under a single controller, ensuring high availability and consistency. 💡 A fundamental concept for anyone learning Kubernetes, DevOps, and container orchestration. #Kubernetes #DevOps #Containers #CloudComputing #AshokIT

🚀 Dockerfile Optimization: Why It Matters A common mistake I see in many projects is using inefficient Dockerfiles that lead to massive image sizes. 📉 Example: ❌ Traditional approach → 1.4 GB image ✅ Optimized approach → 180 MB image 🔍 What makes the difference? Using lightweight base images like Alpine Implementing multi-stage builds Installing only required dependencies Running containers as non-root users Adding health checks for reliability 💡 Impact: Faster CI/CD pipelines Reduced storage costs Improved security posture Faster deployments in Kubernetes 👉 As DevOps engineers, optimization is not optional — it's essential. #DevOps #Docker #Kubernetes #CloudComputing #SoftwareEngineering #CI_CD #AWS #Containers #BestPractices

Docker vs Kubernetes: Understanding the Difference In modern cloud-native environments, Docker and Kubernetes are often used together—but they solve different problems. Docker focuses on containerization: • Packages application code along with dependencies • Uses Dockerfiles to build portable images • Ensures consistency across development, testing, and production • Runs containers directly on a host system Kubernetes focuses on orchestration: • Manages containerized applications at scale • Handles scheduling, scaling, and self-healing of workloads • Provides service discovery and load balancing • Ensures high availability across clusters Key takeaway: Docker helps you create and run containers. Kubernetes helps you manage and scale them in production. Together, they form the foundation of resilient, scalable, and cloud-native systems. #DevOps #Kubernetes #Docker #CloudComputing #SRE #PlatformEngineering #Microservices #CloudNative #CICD #InfrastructureAsCode

𝐑𝐞𝐝 𝐇𝐚𝐭 𝐎𝐩𝐞𝐧𝐒𝐡𝐢𝐟𝐭 𝐛𝐲 𝐑𝐞𝐝 𝐇𝐚𝐭 changed how I look at 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬. - Kubernetes is just the engine - OpenShift is the complete factory 𝑾𝒉𝒚 𝒊𝒕 𝒎𝒂𝒕𝒕𝒆𝒓𝒔: - No more DIY complexity - Built-in CI/CD, security & scaling - Self-healing with Operators - True DevOps alignment 𝑹𝒆𝒂𝒍𝒊𝒕𝒚 𝒄𝒉𝒆𝒄𝒌: 75% of enterprises struggle with Kubernetes complexity 𝑭𝒊𝒏𝒂𝒍 𝑻𝒉𝒐𝒖𝒈𝒉𝒕: - Don’t just run containers… - Run a platform that runs everything for you. #Kubernetes #OpenShift #DevOps #CloudNative #PlatformEngineering

🚀 Kubernetes End‑to‑End Project | AWS EKS | GitOps | DevSecOps Successfully completed a Kubernetes End‑to‑End implementation as part of advanced Kubernetes training, covering the complete lifecycle from infrastructure provisioning to production deployment. 🔹 Highlights: - Provisioned AWS EKS using Terraform (Infrastructure as Code) - Built a GitOps model using Argo CD with multi‑environment support (dev, qa, staging, prod) - Implemented CI/CD with GitHub Actions including Docker build, Trivy security scan, SonarQube analysis, and DockerHub image publishing - Enforced production safety with manual approval via Argo CD - Integrated Slack notifications for deployment and pipeline visibility - Followed modern DevSecOps & Cloud Native best practices This project helped me strengthen my hands‑on understanding of Kubernetes, EKS, GitOps, CI/CD, and security‑first deployments. #Kubernetes #EKS #DevOps #GitOps #ArgoCD #Terraform #GitHubActions #CloudNative #DevSecOps

🚀 Hands-On Guide to Kubernetes CRDs (with a Practical Example) If you're working with Kubernetes and feel limited by built-in resources like Pods or Deployments, this is a must-read 👇 🔗 https://lnkd.in/dpYY4dYX 💡 Key takeaway Kubernetes Custom Resource Definitions (CRDs) let you extend the Kubernetes API by creating your own resource types, making your infrastructure truly custom, automated, and scalable. 📌 What you’ll learn ● What CRDs are and why they matter ● How to define your own custom resources ● A practical, real-world example ● Best practices for production use ⚙️ CRDs are the foundation behind powerful tools like Operators, enabling Kubernetes to manage complex systems beyond its default capabilities. If you're diving into platform engineering, DevOps, or cloud-native architecture, this is a concept you can't skip. #Kubernetes #DevOps #CloudNative #PlatformEngineering #Containers #K8s

Most people learn DevOps in bits. Few actually see how it all connects in a real-world workflow. From writing code to deploying a full microservices application with CI/CD, this is what building like a professional actually looks like. Clean pipelines, automated deployments, scalable infrastructure, and real monitoring. If you are serious about moving beyond theory and building skills that actually matter, this is the level to aim for. #DevOps #CloudEngineering #TechSkills #CI_CD #Elev8trix

Company with 3 microservices: "We need Kubernetes!" No. You need a working product. Kubernetes solves orchestration at scale. If you're not at scale, it's just complexity overhead. → Managing clusters → Learning operators → Debugging networking → Configuring storage All before shipping a single feature. Sometimes the best DevOps decision is choosing boring, proven technology over shiny new infrastructure. Solve business problems first. Infrastructure problems second. #DevOps #Kubernetes #AliveDevOps #Infrastructure #CloudNative #TechStrategy