Inside The AI Stack

Practice

Labs

Reading about a failure and diagnosing one are different skills. Labs drop you into an incident with the same partial, noisy information you would have in production, and ask you to work it out before showing you the answer.

How a lab works

Six stages, in the order a real investigation goes — not the order a tutorial would put them in.

  1. 01

    Scenario

    You are handed a failure and the context an engineer would actually have. Nothing is pre-diagnosed.

  2. 02

    Signals

    Realistic command output, logs, and service state. Some of it is relevant. Some of it is not.

  3. 03

    Investigate

    You decide what to run next. The lab tells you what each command would have returned.

  4. 04

    Hypotheses

    Rank what could produce these signals, and identify which check eliminates the most possibilities.

  5. 05

    Root cause

    The explanation, including why the obvious first guess was wrong.

  6. 06

    Fix and validate

    Remediation, the validation that proves it worked, and the rollback if it did not.

Labs

Available labs

Introductory labs are free. Advanced labs are part of Pro.

Lab: CrashLoopBackOff

A service crash-looping after a routine config change, with logs that show a normal startup and no error anywhere. Work out what is killing it.

intermediate· 25 minKubernetes

Lab: Nova NoValidHost

Instances stopped building on a cloud with visible free capacity. Work the evidence, form hypotheses, and find why the scheduler has no candidates.

expert· 35 minOpenStackNova

Lab: Destructive Plan Review

A routine-looking Terraform pull request. Find the changes that would destroy data before you approve it, and work out which one is not what it appears to be.

intermediate· 20 minTerraformAWS

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