CKA — Workloads & Scaling
Chapter Overview
Welcome to Chapter 7 — Workloads & Scaling of the CKA exam preparation series.
This chapter maps to the Workloads & Scheduling domain, which accounts for 15% of the CKA exam. As a cluster administrator, you need to know how to deploy applications, update them safely, roll back when things go wrong, manage configuration data, scale workloads, and set resource boundaries.
We’ll cover Deployments, rolling updates & rollbacks, ConfigMaps & Secrets, scaling with HPA, and resource management — everything you need to confidently handle workload-related questions on exam day.
What You’ll Learn
| # | Topic | What’s Covered |
|---|---|---|
| 1 | Deployments | Creating Deployments, strategies (RollingUpdate vs Recreate), ReplicaSets |
| 2 | Rolling Updates & Rollbacks | rollout status/history/undo, maxSurge, maxUnavailable |
| 3 | ConfigMaps & Secrets | Creating, consuming as env vars & volumes, immutable configs |
| 4 | Scaling & HPA | Manual scaling, HorizontalPodAutoscaler, Metrics Server |
| 5 | Resource Limits | Requests vs limits, QoS classes, LimitRange, ResourceQuota |
| 6 | Hands-On Lab | Deploy, scale, update, rollback — full practice scenario |
CKA Exam Relevance
The Workloads & Scheduling domain tests your ability to:
- Create and manage Deployments
- Perform rolling updates and rollbacks
- Configure applications using ConfigMaps and Secrets
- Scale workloads manually and automatically
- Set resource requests, limits, and quotas
Expect imperative commands under time pressure. Know both kubectl create and YAML manifests — the exam rewards speed.
Prerequisites
Before starting this chapter, make sure you’re comfortable with:
- Pods — You should understand Pod specs and lifecycle
- Labels & Selectors — Deployments use label selectors to manage Pods
- Namespaces — Resource quotas and limit ranges are namespace-scoped
- kubectl basics —
create,apply,get,describe,delete - A working kubeadm cluster or minikube to practice
Ready to dive in? Let’s start with the building block of workload management.
