Start with a small, bounded service
Use a fictional internal application with a simple API and a small database or permitted sample dataset. Define the expected users, the allowed budget and what the service should do. Keep experiments in an authorized sandbox. Avoid production accounts and confidential data.
The example can use AWS, Azure or Google Cloud. Choose one environment you can explain before adding multiple clouds. Record what is deliberately simplified and what a real organization would still need to review.
Make the architecture a decision record
Show the request path, network boundaries, identity, application components, data stores and monitoring. For each important choice, explain an alternative and why you did not use it. A small diagram with clear boundaries is better than a large collection of service logos.
Use the AWS Well-Architected Framework as one structured reference for discussing operational, security, reliability, performance, cost and sustainability concerns. It does not make your project an officially approved architecture.
Prove that a second person can repeat the work
Keep infrastructure definitions in version control. Document prerequisites, environment variables and the deployment sequence. Use a pipeline with meaningful checks and show a successful run alongside a failed check that prevented a bad change.
Explain how permissions are limited and how secrets reach the application without being committed. Separate a development example from the controls required in an organization. A README should let a reviewer understand the process without exposing your credentials.
Investigate one failure and one recovery
In the sandbox, create a controlled failure such as a bad application version or an unavailable dependency. Capture the symptoms, logs and metrics. Explain how you narrowed the cause, what you changed, and how you confirmed recovery. If you demonstrate rollback, document which state or data the rollback cannot restore.
For Kubernetes, distinguish readiness from liveness and startup checks. A readiness failure affects whether a Pod receives Service traffic; liveness and startup failures can trigger container restarts under their configured behavior. Consult the official Kubernetes probe documentation before configuring a lab.
Close the loop on cost and cleanup
Record the resources you created, the cost assumptions and how you will remove the environment. Include a cleanup command or documented sequence and verify that resources were removed. Cost estimates vary with region, usage and provider pricing; do not present a lab estimate as a guaranteed production budget.
Your evidence pack can contain the diagram, infrastructure definitions, pipeline results, incident timeline, runbook, cleanup notes and limitations. Explain what you personally implemented and where you used templates or AI assistance.
Choose learning around the gap you found
If networking and identity remain unclear, start with Cloud Engineer training. If you can deploy manually but cannot make delivery repeatable, compare the DevOps Engineer path. Review the Cloud and DevOps catalog for other specializations.
Ask enrollment support about prerequisites, lab accounts, expected practice time, instructor availability and project feedback. This public guide describes an educational example; the confirmed course syllabus defines enrolled assignments.
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