Learn Computer Stuff
Home / Credentials / Certified Kubernetes Administrator (CKA)
Credential

Certified Kubernetes Administrator (CKA)

Issued by CNCF. Below is what it costs, how long it lasts, and what it actually signals — with the date we checked.


Certified Kubernetes Administrator (CKA)

Free to learn · paid certificate Recognized

The honest cost
Cost$445
ValidityNot stated on the certification page. CNCF does not print a validity period there, so we record it as unknown rather than repeat a figure from elsewhere.
RenewalNot stated on the certification page.
AssessmentPerformance-based, hands-on exam in a live environment (not multiple choice)
ProctoredYes
Verify viaunknown
Cost per active yearUnknowncannot be computed — CNCF publishes the $445 fee but not a validity period

The standard Kubernetes credential, and AI infrastructure runs largely on Kubernetes.

Read this before you buy

The $445 fee includes one free retake, which is unusual and worth weighing against cheaper exams that charge again on a resit. HONEST GAP: CNCF does not print a validity period on this page, so we cannot tell you the cost per active year. Check before you budget. It is listed because a performance-based exam is a stronger signal than a quiz.

· Official page

How we know

Price of $445 including one free retake read from CNCF's own CKA page via headless Chrome on 2026-07-28, where it appears twice — in the cost panel and in the exam description. The same page states no validity period, so validity and renewal remain recorded as unknown rather than guessed. A plain fetch of the page shows no price.

· https://www.cncf.io/training/certification/cka/

Free preparation

Free resources first. Everything below is free to use; the exam itself is the paid part.

Kubernetes Basics — the official tutorial

Free to learn · no certificate

Kubernetes is the substrate most AI infrastructure sits on. The project's own interactive tutorial is free and open; no certificate.

vLLM documentation — serving at scale

Free to learn · no certificate

Inference serving, batching and memory behaviour. Use the /en/stable/ path — /en/latest/ serves developer-preview docs and says so on the page.

Ray documentation

Free to learn · no certificate

Distributed execution for training and serving, free and open source. Anyscale (Ray's company) separately runs a paid-status-unknown Ray Accreditation Test — the docs themselves cost nothing.

CNCF Platforms White Paper

Free to learn · no certificate

The reference statement of what a platform is and what makes one succeed or fail, from CNCF's App Delivery technical advisory group. Free and open; substantial rather than a summary.

Backstage — what it is and how it works

Free to learn · no certificate

The open-source developer portal originally from Spotify, now a CNCF project. Free and open source; docs shown for stable v1.53.0.

Kubeflow — introduction

Free to learn · no certificate

The ML toolkit for Kubernetes — pipelines, notebooks and serving as a platform rather than as one-off scripts. Free and open source.

Docker — Get started

Free to learn · no certificate

Containers are the unit everything else assumes. Docker's own guide is free; note Docker Desktop has paid licensing for larger companies while the engine and docs are free.

GitHub Actions — quickstart

Free to learn · no certificate

CI/CD you can practise on a free account today. Free tier has generous minutes for public repositories; private repos consume a quota.

HashiCorp — Terraform tutorials

Free to learn · no certificate

Infrastructure as code, from the vendor. Free to read and follow; the cloud resources you create in them can cost money, so mind the teardown step.

Kubernetes — concepts

Free to learn · no certificate

The substrate nearly every internal platform is built on now. Free and thorough; read concepts before tutorials or you will cargo-cult.

Kubernetes — tutorials

Free to learn · no certificate

Hands-on once the concepts land. Free.

GitHub Actions — quickstart

Free to learn · no certificate

A platform is mostly the paths your builds take. Start by owning one properly.

Used by these roles

  • AI Infrastructure Engineer — You run the clusters models train and serve on — GPUs, schedulers, networking and the things that fail at 3am.
  • AI Platform Engineer — You build the internal platform other teams use to ship AI — so they do not each reinvent serving, tracking and deployment.
  • DevOps Engineer — You make shipping software boring — automated, repeatable, and safe to undo.
  • Platform Engineer — You build the paved road other engineers ship on, so they stop reinventing the same pipeline.