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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.

HardTechnical
0 practiced
As a Solutions Architect, design an on-call and alerting program that includes SLO-driven alerts, alert thresholds, routing/escalation policies, runbook formats for common incidents, and postmortem practice. Explain how to balance noise reduction with rapid detection and how to measure alert fatigue improvements.
MediumTechnical
0 practiced
Propose controls to integrate security and compliance checks into CI/CD: secret scanning, image and dependency scanning, policy-as-code gates, least-privilege build runners, SBOM generation, and audit logging. Explain how to fail fast on violations yet allow emergency overrides with traceable approvals.
HardTechnical
0 practiced
Create a cost-optimized capacity plan for an online retailer expecting unpredictable traffic spikes (e.g., Black Friday). Consider reserved instances, spot/on-demand tradeoffs, autoscaling, pre-warming caches, ephemeral services, and capacity testing strategies. Provide cost vs risk tradeoffs and an operational runbook for surge handling.
MediumTechnical
0 practiced
Write a Dockerfile (or describe one) for a Go web application using multi-stage builds that produces a minimal final image, runs as a non-root user, and embeds build metadata (version and build time) into the binary. Explain choices that improve security and rebuild performance.
HardSystem Design
0 practiced
Design an observability strategy for a distributed microservices platform to enable SLO monitoring, root-cause analysis, and anomaly detection while controlling telemetry costs. Specify tracing sampling, metric cardinality policies, log retention tiers, and how traces propagate context across services.

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