Running Containers with Kubernetes
Learn how Kubernetes keeps modern web applications alive, scaled, and reachable. Shift from managing single servers to declaring your desired state and letting the cluster automate healing, routing, and updates.
Like Duolingo, but for Running Containers with Kubernetes. Tomo turns the whole topic into a game you play five minutes a day, until it actually sticks.
A short one: 12 levels across 2 sections, about 24 minutes end to end, roughly 5 days at five minutes a day. It moves through Keeping Containers Alive and Scaled and Routing Traffic and Fixing Failures. It starts from scratch.
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Key ideas in Running Containers with Kubernetes
- In Kubernetes, you specify the desired state rather than issuing step-by-step start commands
- A continuous background control loop monitors the cluster and acts whenever reality does not match the desired spec
- A Pod is the smallest unit Kubernetes deploys, wrapping one or more containers
- Containers in the same Pod share an IP address, communicate over localhost, and can share mounted storage
- Declarative YAML manifests describe what the cluster should look like in a text file
- Storing manifests in version control lets you track configuration changes and redeploy identical environments on demand
- Kubernetes treats Pods as disposable workers that can be terminated and replaced at any time
- Any data stored only inside an ephemeral Pod is lost when it restarts or moves
- Because new replacement Pods get new internal IP addresses, apps must not depend on fixed Pod identities
- The Kubernetes scheduler automatically evaluates worker nodes and places Pods where CPU and memory are available
- Nodes without enough spare capacity are skipped until resources free up
- If a node becomes unavailable, the cluster places replacement Pods onto healthy nodes that have sufficient headroom
- A Deployment constantly compares the desired number of Pods against what is actually running
- If a node crashes, Kubernetes automatically recreates the missing Pods on another available node
- Deployments use label selectors (key-value tags) to group and manage their Pods
- Because Pods are frequently created and destroyed with generated names, rigid name lists cannot track them
You've tried the other tabs
Thirty open tabs. Four facts you actually kept.
You watched. You nodded. By Sunday it was gone.
One answer, then back to scrolling.
Eight weeks. You meant to finish. You didn't.
Tomo gives Running Containers with Kubernetes the Duolingo treatment: levels, streaks, and quick quizzes that test what you just learned. That game loop is what the tabs above never had, so it's the one you actually finish.
Here's what playing it feels like
A real question from this course. Take your best guess.
How do you usually tell Kubernetes to run your app?
Get it right to open this lesson and 11 more in the app.
Where Running Containers with Kubernetes takes you
- 1
Keeping Containers Alive and Scaled
- Running Apps as Declarative Workloads
- Scaling and Self-Healing with Deployments
- 2
Routing Traffic and Fixing Failures
- Directing Traffic with Services
- Finding and Fixing Common Breakages
2 sections · 4 units · 12 levels. Built to play, not to enroll.
Tomo is in ChatGPT
Tomo is also a ChatGPT plugin: the same playable courses, built and played inside your chat.
Add Tomo to ChatGPT- What to ask
- “Make me a Tomo course on black holes.” “Turn this chat into a Tomo course.”
- What you get
- Quick questions with instant feedback, hearts and stars, ready to play in about a minute.
- Where it goes
- No sign-up to start. Connect your Tomo account and your streak carries on in the app.
You pick the voice
Running Containers with Kubernetes is taught in the Bestie style: your friend who just gets it. Want a different feel? In the app you can spin up the same topic in any of Tomo's teaching styles. Same facts, totally different vibe.
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Start Running Containers with Kubernetes today.
Download Tomo, search Running Containers with Kubernetes, and play your first lesson in under a minute.