Automation and Scripting Questions

Covers practical and architectural skills for writing production safe automation and operational scripts as well as building reusable automation systems. Topics include designing idempotent automation, safe retries, robust error handling, structured logging and observability, argument parsing and command line interface design, configuration management, and secure credential handling. Emphasis on testing and validation of scripts and automation code, packaging, documentation, deployment, and maintainability so automation can be operated by other team members. Includes integration with schedulers such as cron and systemd timers, continuous integration and continuous delivery pipelines, orchestration and configuration management systems, and common operational patterns such as log processing, backups, polling, multi step orchestration, provisioning, configuration changes, and routine maintenance. Also assesses language selection and trade offs among Python, Go, Bash and other tooling, concurrency and performance considerations, and at senior levels the design and architecture of reusable automation frameworks and strategies for scaling automation to reduce toil.

MediumTechnical

79 practiced

Given a nightly database backup job that archives snapshots to object storage, design a monitoring and alerting plan. Include which metrics to emit (success/failure, duration, throughput, snapshot size), alert thresholds, paged vs non-paged alerts, a runbook for recovery, and how to test alerting to avoid false positives.

MediumSystem Design

91 practiced

Design a rollback strategy for automated deployments that uses canary releases and feature flags. Define detection thresholds that trigger automated rollback, automated rollback steps, verification checks after rollback, and how to coordinate rollback if a database migration is part of the release.

EasyTechnical

77 practiced

Explain structured logging for automation scripts: list the key fields you would include (timestamp, level, component, job_id, correlation_id, message, metadata), explain why JSON logs are preferred in distributed environments, and describe how structured logs make alerting and debugging easier for SREs.

HardTechnical

94 practiced

Design an automated canary analysis system that compares key metrics between canary and baseline cohorts, runs appropriate statistical tests (e.g., non-parametric or t-test depending on distribution), accounts for false positives across multiple metrics, and integrates with orchestration to promote or rollback. Define minimum sample sizes, confidence thresholds, and mitigation for noisy signals.

MediumTechnical

87 practiced

Implement a Python 3 script named 'fetch_verify.py' (standard library only) that: 1) ensures the destination directory exists; 2) downloads a file from a provided URL into that directory only if a file with the same SHA-256 checksum does not already exist; 3) verifies the downloaded file's SHA-256; 4) supports --retries N with exponential backoff and --dry-run. Code must be idempotent and avoid partial-file states.

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