This lab is currently in Beta, content may be updated as we refine the material
LABINTERMEDIATE

ConfigMaps, Secrets & StatefulSets Lab

Set up a real ConfigMap and Secret for the TaskFlow backend, deploy PostgreSQL as a StatefulSet with persistent storage, and compare your manifests against the production originals.

115 minutes
ConfigMaps, Secrets & StatefulSets Lab - Platform Engineering Hands-On Lab Icon
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Lab Overview

🛠 Lab from the Platform Engineering Bootcamp. Used in Week 8. Bootcamp landing page: https://academy.tekanaid.com/bootcamps/platform-engineering-bootcamp Parent course(s):

  • Week 8: Kubernetes Fundamentals (slug: kubernetes-fundamentals)

🟡 Beta bootcamp lab. Hands-on instructions, check scripts, and solve scripts are in place.

Continues directly from last week's k8s-deployments-services-scaling lab: the real TaskFlow FastAPI backend, cloned fresh and built from its own Dockerfile, starts this lab with a hardcoded `WORKERS` value on the Pod template. You'll externalize that, and the rest of the app's real settings from `backend/.env.example`, into a ConfigMap, then move `DATABASE_URL` and `SECRET_KEY` into a Secret. You'll deploy PostgreSQL as a StatefulSet with a PersistentVolumeClaim, the same real infrastructure the TaskFlow repo ships ahead of the database code that will use it in a later bootcamp week, and deploy Redis as an ordinary Deployment to see the contrast between stateful and stateless workloads firsthand.

You'll test configuration reloads and data persistence across pod restarts using real, verifiable checks (live environment variables and database queries, not a fictional health endpoint), and finish by revealing the real production ConfigMap, Secret, and StatefulSet manifests from the canonical TaskFlow repo to compare against what you built.

What You'll Learn

Create Kubernetes ConfigMaps and Secrets to externalize a real application's configuration from its container image

Deploy PostgreSQL as a StatefulSet with a PersistentVolumeClaim and verify data survives pod restarts

Inject ConfigMaps and Secrets into a Deployment as environment variables

Distinguish between stateful and stateless workloads and choose the appropriate Kubernetes controller

Compare handwritten Kubernetes manifests against real production originals in the same repo

Prerequisites

Completion of the Deployments, Services & Scaling Lab (k8s-deployments-services-scaling)

Basic familiarity with kubectl, Deployments, Services, and YAML manifests

Technologies Covered

kubernetesconfigmapssecretsstatefulsetspersistent-storage

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