Personal account of hands on experience using public cloud providers and the concrete results delivered. Candidates should describe specific services and patterns they used for compute, storage, networking, managed databases, serverless and eventing, and explain their role in architecture decisions, deployments, automation and infrastructure as code practices, continuous integration and continuous delivery pipelines, container orchestration, scaling and performance tuning, monitoring and incident response, and cost management. Interviewees should quantify outcomes when possible with metrics such as latency reduction, cost savings, availability improvements or deployment frequency and note any formal training or certifications. This topic evaluates depth of practical experience, ownership, and the ability to operate and improve cloud systems in production.
HardTechnical
0 practiced
Design a monitoring and alerting strategy to minimize alert fatigue across a platform of dozens of services. Cover how you select which metrics to alert on, techniques to reduce noise (aggregation, debounce, anomaly detection), alert prioritization and routing, escalation workflows, synthetic monitoring, and continuous improvement of alert quality.
HardTechnical
0 practiced
A Java-based API service shows periodic p99 latency spikes suspected to be caused by garbage collection pauses. As the SRE, describe how you would confirm GC as the root cause, which JVM flags or GC algorithms you would evaluate, how to estimate safe heap sizes, and what operational mitigations such as sharding, thread pool tuning, or circuit breakers you might deploy to reduce tail latency.
MediumTechnical
0 practiced
Using Terraform HCL, design a reusable module that provisions an autoscaling group behind an application load balancer. The module should accept parameters for instance type, desired/min/max capacity, health check path, and tags. Show example inputs and explain where remote state is stored and how locking is handled in CI.
EasyTechnical
0 practiced
Describe the managed database services you have operated in the cloud such as RDS, Cloud SQL, DynamoDB, or Spanner. For each, explain tradeoffs you considered around availability modes, read replicas, scaling approaches, consistency, operational overhead, and common failure modes. Give one example where your database choice materially affected reliability or cost.
MediumSystem Design
0 practiced
Design a CI/CD pipeline for a microservices platform deployed to managed Kubernetes that supports automated canary rollouts, database migrations, infrastructure as code changes, and safe rollbacks. Describe the tooling choices, gating criteria, environment promotion strategy, and how SLOs and automated testing are integrated into the pipeline.
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