Start by clarifying requirements and scale (number of repos, jobs/day, concurrency, deployment targets), then propose a high-level architecture covering triggers, pipeline execution, build agents, artifact storage, secret management, retries, observability, and scaling. Walk through the end-to-end flow of a code change, diving into each component and discussing trade-offs (e.g., self-hosted vs. managed agents, push vs. pull triggers).
Pro tip: Emphasize idempotency and isolation in pipeline steps and build agents to ensure reliable retries and secure multi-tenancy; also discuss how you'd handle secrets rotation and auditability without slowing down developers.
Ask about the number of repositories, expected concurrent jobs, deployment frequency, and target environments. Establish non-functional requirements like build time SLAs, security, and cost constraints.
Define how jobs are triggered (webhooks, polling, manual) and the pipeline execution model (DAG-based, stages, parallel steps). Explain how pipelines are defined (e.g., YAML in repo) and versioned.
Choose between self-hosted and managed build agents, discuss autoscaling, isolation (containers/VMs), and caching. Describe artifact storage (e.g., S3, Artifactory) with versioning, retention, and promotion across environments.
Detail secure secret injection (e.g., Vault, KMS), retry policies with idempotency, and observability (logs, metrics, traces, alerts) for pipeline health and debugging.
Discuss scaling strategies for agents, queueing, and storage; trade-offs between consistency and availability, cost vs. performance, and how to handle failures and backpressure.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.