APPUiO’s Post

We just published a new blog post on our GitOps journey - and how it led us to building our own operator: Espejote. From Ansible playbooks to a jungle of operators, bash reconcilers and plenty of lessons learned along the way - this is the story of how we ended up building something that finally fits our needs. Espejote combines GitOps principles with in-cluster state, powered by Jsonnet and native server-side apply. Built for flexibility, reliability and real-world operations at scale. If you're working with Kubernetes, GitOps or platform engineering, this might resonate 🙂 👉 Read the full story: https://lnkd.in/d29EEvtT #Kubernetes #GitOps #PlatformEngineering #DevOps #CloudNative #OpenSource

Stop overcomplicating GitOps workflows with ArgoCD and Flux for Kubernetes. I've reviewed hundreds of implementations. The best ones? Dead simple. The pattern: - Start with the boring solution - Measure actual bottlenecks - Only then add complexity Premature optimization is real, and it kills projects. What's the simplest solution you've shipped that just worked? #DevOps #CloudComputing #Kubernetes

Kubernetes scheduling feels “magical”… until it breaks 😅 Why did your Pod not get scheduled? Why is it stuck in Pending? What’s the real difference between NoSchedule vs NoExecute? The following hands-on video breaks it all down—without any confusion: → NodeSelector vs NodeAffinity (when to use what) → Taints & Tolerations (NoSchedule vs NoExecute, clearly explained) → How DaemonSets run on every node automatically → Operators like Equal vs Exists (simple + practical) → Real cluster demos so you can see scheduling in action No theory overload. Just practical understanding you can actually use. If Kubernetes scheduling has ever confused you, this will make things click 👇 🎥 https://lnkd.in/evXTDwAx #Kubernetes #DevOps #CloudNative #K8s #Containers #TechLearning

🚀 Day 15/30 – Docker + CI/CD Integration Today, I successfully integrated Docker with CI/CD using GitHub Actions 🐳⚙️ 🔹 Created a Dockerfile to containerize my application 🔹 Integrated Docker build into CI pipeline 🔹 Triggered automated Docker image build on code push 🔹 Explored how CI/CD works with containerization in real-time 💻 Initially, I faced errors like a missing Dockerfile, but I was able to debug and resolve them successfully. This helped me understand the importance of correct configuration and file structure in DevOps workflows. 💡 Key Takeaway: Combining Docker with CI/CD enables automated, consistent, and reliable application builds and deployments 🚀 📸 Attached: Successful Docker build via GitHub Actions 👉 Learning and improving step by step! #DevOps #Docker #CICD #GitHubActions #AWS #Automation #LearningInPublic #Day15

🚀 Day 10/50 — Namespaces As your Kubernetes cluster grows, managing resources becomes complex. That’s where Namespaces help. 👉 What are Namespaces? Namespaces divide a cluster into multiple virtual environments. 💡 Why it matters? • Organize resources efficiently • Separate environments (dev, test, prod) • Avoid conflicts between applications ⚙️ Example: You can have the same app name in different namespaces without conflict. 🧠 Simple Understanding: Namespace = Virtual partition inside a cluster 🔥 Key Takeaway: “Namespaces help you organize and isolate resources in Kubernetes.” 📌 Follow my journey as I learn Kubernetes step by step. #Kubernetes #DevOps #LearningInPublic

If you want to learn Kubernetes, do not start by memorizing commands. Start by understanding the building blocks. Kubernetes begins with containers, because Kubernetes manages containers. Then comes YAML, which is the language used to describe what you want Kubernetes to create. Think of YAML like giving Kubernetes a blueprint. You are not building the house by hand, you are handing the builder exact instructions. A simple learning path: Learn containers and Docker Understand Pods Learn Deployments Understand Services Learn ConfigMaps and Secrets Study Ingress Then move to Volumes, Namespaces, and Helm Learn in that order, and Kubernetes starts making sense instead of feeling like chaos. #Kubernetes #YAML #DevOps #CloudNative #Containers #TechLearning

Docker and Kubernetes are often mentioned together — but they solve different problems.   𝗗𝗼𝗰𝗸𝗲𝗿 Packages your application and everything it needs into a container. Think of it as a box that runs the same way everywhere — your laptop, staging, production.   𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 Manages those containers at scale. When you have 10, 50, or 500 containers — Kubernetes decides where they run, restarts them when they crash, and balances traffic between them.   Simple analogy: → Docker = shipping container (packages the cargo) → Kubernetes = the port (manages where every container goes)   You can use Docker without Kubernetes. You can't use Kubernetes without containers.   Start with Docker. Understand containers first. Then Kubernetes makes much more sense.   #Docker #Kubernetes #DevOps #CloudEngineering #ContainerOrchestration

While learning Kubernetes, I tried removing requests from my Deployment. I expected the scheduler to “guess” where to place my Pods. But something unexpected happened. When I checked the running Pod: kubectl get pod -o jsonpath='{.spec.containers[0].resources}' Requests were still there. Kubernetes had automatically set: requests = limits That’s when it clicked: Requests - define the minimum resources needed for scheduling. Limits - define the maximum resources a container can use. If you set limits but not requests, Kubernetes assumes both should be the same. So instead of guessing, it treats your Pod as fully guaranteed. To actually see “guesswork” scheduling… you need to remove both: requests and limits. #Kubernetes #DevOps #CloudNative #Containers #BackendDevelopment   #SoftwareEngineering #DistributedSystems #LearningInPublic #BuildInPublic

K8s + the ecosystem = Unstoppable. Here’s a quick cheat sheet on how external tools plug in to give Kubernetes new superpowers. What's your go-to K8s combo? 👇 #Kubernetes #CloudNative #DevOps

This week I went deeper into Docker and Kubernetes 🚀 I moved beyond just running containers and started understanding how things actually work under the hood — from building efficient Docker images to managing deployments, services, and scaling in Kubernetes. Some key takeaways: *Writing cleaner, optimized Dockerfiles *Understanding container networking and volumes *Working with Kubernetes deployments, pods, and services *Getting hands-on with scaling and basic orchestration Still a lot to explore, but this felt like a solid step forward in my cloud-native journey. #Docker #Kubernetes #DevOps #Learning #CloudComputing