Kubernetes (K8s) is one of the most in-demand technologies in DevOps today. At first glance, it looks like just YAML files and kubectl commands. But if you try to learn Kubernetes only that way, it will feel confusing and overwhelming.
👉 The secret is this: To truly understand Kubernetes, you need strong foundations in Application Engineering, System Engineering, and Microservices Architecture.
In this article, I’ll break down why these three areas are important, and how they connect to Kubernetes in real life.
🔹 1. Application Engineering
Applications define what Kubernetes actually runs. If you don’t understand how apps work, you won’t know how to design your Kubernetes objects.
Key Points:
Stateless apps (like frontends) are easy to scale → use Deployments.
Stateful apps (like databases) need stable storage → use StatefulSets + PVCs.
Config & Secrets → represent environment variables, API keys, configs that apps need.
Probes (liveness/readiness) → monitor if the app is healthy or needs a restart.
👉 Example:
If you deploy a simple web app, you can scale it to 10 replicas easily using a Deployment. But if you deploy PostgreSQL, you need a StatefulSet with persistent storage.
🔹 2. System Engineering (Linux, Networking, OS)
Kubernetes runs on Linux nodes. Pods are basically Linux processes wrapped in containers. If you don’t know system engineering basics, Kubernetes will feel like magic.
Key Points:
Processes, namespaces, cgroups = how containers isolate workloads.
Networking basics (IP, DNS, load balancing) = how Pods and Services communicate.
Storage (volumes, filesystems, mounts) = how StatefulSets and PVCs work.
Resource management (CPU, memory) = how requests & limits control scheduling.
👉 Example:
When you expose a Pod using a Service, Kubernetes assigns a stable virtual IP. Without knowing DNS or load balancing, this looks mysterious.
🔹 3. Microservices Architecture
Kubernetes was designed to run microservices at scale. If you don’t understand microservices, it’s hard to see why Kubernetes exists.
Key Points:
Microservices = small, independent services that talk via APIs.
Service Discovery → Kubernetes Services make sure pods can find each other.
Scaling → Deployments + Horizontal Pod Autoscaler (HPA).
Traffic routing → Ingress or Service Mesh (Istio/Linkerd).
👉 Example:
Your frontend Pod doesn’t hardcode backend IPs. It connects to the backend via a Service name (like backend.default.svc.cluster.local).
🔹 4. How to Learn Kubernetes the Right Way
Instead of trying to master everything at once, learn in layers:
Linux & Networking basics → processes, ports, DNS, IP.
Docker & Containers → build and run a simple app.
Microservices Basics → stateless vs stateful, scaling, APIs.
Kubernetes Core → Pods → Deployments → Services → Ingress.
Advanced K8s → StatefulSets, Pod Disruption Budgets (PDB), RBAC, Operators.
🔹 5. Practical Learning Path
Don’t just read—practice step by step:
Deploy Nginx in a Pod.
Expose it with a Service.
Scale it with a Deployment.
Add a database using StatefulSet + PVC.
Run kubectl drain node1 → see why PDBs are important.
Add an Ingress → connect frontend and backend.
👉 Each Kubernetes object = a solution to a real-world engineering problem.
✅ Conclusion
Kubernetes is not about memorizing YAML. It’s about connecting the dots between:
Applications (what you run),
Systems (where it runs), and
Microservices (how they talk to each other).
📌 Learn them together, layer by layer. Once you do, Kubernetes will stop being a mystery and start making sense
Top comments (1)
Wonderful Article ... Very Helpful...