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CKA
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CKA · Workloads & Scheduling
Taints and Tolerations
A worker node has been tainted with dedicated=gpu:NoSchedule and labeled gpu=true. A Deployment called web-app already exists in namespace cka-taints. It should not run on the tainted node.
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The task
A worker node has been tainted with dedicated=gpu:NoSchedule and labeled gpu=true.
A Deployment called web-app already exists in namespace cka-taints. It should not run on the tainted node.
Task: Create a pod named gpu-pod in namespace cka-taints that:
- Uses image
nginx:1.25 - Has a toleration for the taint
dedicated=gpu:NoSchedule - Has a nodeSelector that targets nodes with label
gpu=true - Is in a Running state
What this tests
Run and schedule workloads — deployments, autoscaling, taints and tolerations, affinity, and resource limits. On the CKA exam, Workloads & Scheduling tasks are graded purely on what you build in the cluster — not multiple choice — so the only way to get faster is to do them on a real cluster against a clock.
Practice it for real
prepium.sh drops you into your own isolated Kubernetes cluster in the browser — no install, no credit card. You solve the task in a real terminal, hit validate, and a programmatic checker scores exactly what you got right and wrong (with partial credit). The canonical solution unlocks after you attempt it, so you learn the fast, exam-ready way to do it.