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Production Deployments and Operations Questions

Covers the end to end practices and trade offs involved in releasing, running, and operating software in production environments. Topics include deployment strategies such as blue green deployment, canary releases, and rolling updates, and how each approach affects reliability, rollback complexity, recovery time, and release velocity. Includes feature flagging and release gating to separate deployment from feature exposure. Addresses continuous integration and continuous deployment pipeline design, automated testing and validation in pipelines, artifact management, environment promotion, and release automation. Covers infrastructure as code and environment provisioning, containerization fundamentals including container images and runtimes, container registries, and orchestration fundamentals such as scheduling, health checks, autoscaling, service discovery, and the role of Kubernetes for scheduling and orchestration. Discusses database migration patterns for large data sets, strategies for online schema changes, and safe rollback techniques. Explores monitoring and observability including metrics, logs, and traces, distributed tracing and error tracking, performance monitoring, instrumentation strategies, and how to design systems for effective troubleshooting. Includes alerting strategy and runbook design, on call and incident response processes, postmortem practice, and how to set meaningful service level objectives and service level indicators to balance reliability and velocity. Covers scalability and high availability patterns, multi region deployment trade offs, cost versus reliability considerations, operational complexity versus operational velocity trade offs, security and compliance concerns in production, and debugging and troubleshooting practices for distributed systems with partial information. Candidates should be able to justify trade offs, explain when a simple deployment model is preferable to a more complex architecture, and give concrete examples of operational choices and their impact.

MediumSystem Design
44 practiced
Design a CI/CD pipeline for a polyglot microservices platform (Java, Go, Python) that supports trunk-based development, fast merges, artifact immutability, and progressive delivery. Include stages for build, unit and integration tests, security scanning, canary deployment, manual approvals, artifact promotion between dev/staging/prod, and rollback controls. Explain how the pipeline prevents 'works-on-my-machine' issues.
MediumSystem Design
55 practiced
Design an automated canary release process for a microservices-based e-commerce platform with 500k daily users and significant revenue sensitivity. Your design should include traffic routing method, metrics to observe (both system and business), automated rollback criteria (statistical approach or thresholds), and how to coordinate dependent services and database migrations during the canary window.
MediumTechnical
43 practiced
Explain key Kubernetes scheduling concepts: node affinity/anti-affinity, taints and tolerations, pod priority and preemption, resource requests and limits, and how scheduling decisions affect reliability. Provide examples of policy combinations to ensure high availability for critical services.
EasyTechnical
48 practiced
Explain feature flagging and release gating. For an organization with many microservices, describe types of flags (release, ops, experiment), the lifecycle for flags (creation, targeting, kill-switch, cleanup), and common pitfalls such as flag debt and configuration drift. Give criteria your team should use to decide when to remove a flag.
EasyTechnical
45 practiced
Explain the GitOps approach to deployments and how it changes the control plane for an SRE team. Describe core components (git repo as source-of-truth, controllers that reconcile cluster state), the benefits for auditability and rollbacks, and limitations or operational risks when using GitOps at scale.

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