Python Scripting for Infrastructure Automation Questions

Applied Python skills for building reusable, production grade automation for infrastructure and operations. Topics include designing modular automation code and libraries, using relevant third party libraries for systems administration and remote management, invoking and controlling subprocesses, interacting with application programming interfaces and cloud platform endpoints, robust error handling and structured logging, automated testing of scripts and modules, packaging and distributing tools for reuse, secure credential management, integration with configuration management and orchestration tooling, and designing multi step workflows and idempotent operations. Candidates should demonstrate experience with writing maintainable automation, reasoning about failure modes, and selecting appropriate abstractions and libraries for operational tasks.

MediumTechnical

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You are on-call: a nightly release fails mid-deploy due to a broken automation script, causing partial rollout. Walk through detection (what alerts/logs you consult), triage (isolate affected services), immediate remediation steps (rollback strategy, apply fixes or abort), communication to stakeholders, and long-term remediation to prevent recurrence (tests, gating, better rollbacks). Be concrete about commands or checks you'd run and who you'd notify.

MediumTechnical

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You are responsible for automation that provisions cloud resources. Sometimes runs abort and leave orphaned resources (e.g., unattached volumes, load balancers). How would you design tracking, reconciliation and cleanup mechanisms in Python automation to detect orphaned resources and safely delete them without impacting live services? Include tagging, owner tracking, grace periods, dry-run, and how to prove safety before deletion.

EasyTechnical

0 practiced

Explain structured logging and why it matters for automation scripts used by SREs. Provide a concise Python example using the standard 'logging' module that emits JSON logs with the fields: timestamp, level, message, module, trace_id, and duration_ms. Explain how to attach contextual information (like trace_id) to all log records and how structured logs integrate with log aggregators for search and alerting.

EasyTechnical

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Implement a simple Python CLI using argparse that supports global flags '--dry-run' and '--verbose' and a subcommand 'deploy' which accepts a '--target' parameter. Define how '--dry-run' should behave (no external changes, list planned actions) and provide example output for a dry-run deploy. Also explain how to unit test the dry-run behavior in CI.

EasyTechnical

0 practiced

You need to run a Python automation action across 500 hosts concurrently. Compare an approach building a custom runner using concurrent.futures + paramiko versus using an off-the-shelf orchestration tool like Ansible. Discuss scalability, inventory management, secrets distribution, retry behavior, idempotency, and how you would implement batching and failure isolation with the custom runner.

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