A concise but comprehensive presentation of a candidate's core technical competencies, tool familiarity, and practical proficiency. Topics to cover include programming languages and skill levels, frameworks and libraries, development tools and debuggers, relational and non relational databases, cloud platforms, containerization and orchestration, continuous integration and continuous deployment practices, business intelligence and analytics tools, data analysis libraries and machine learning toolkits, embedded systems and microcontroller experience, and any domain specific tooling. Candidates should communicate both breadth and depth: identify primary strengths, describe representative tasks they can perform independently, and call out areas of emerging competence. Provide brief concrete examples of projects or analyses where specific tools and technologies were applied and quantify outcomes or impact when possible, while avoiding long project storytelling. Prepare a two to three minute verbal summary that links skills and tools to concrete outcomes, and be ready for follow up probes about technical decisions, trade offs, and how tools were used to deliver results.
HardSystem Design
32 practiced
Design a secure automated pipeline to build, sign (using cosign or similar), generate SBOMs, scan for vulnerabilities, and publish container images across multiple cloud registries. Include ephemeral build agents with least privilege, key management and rotation, SBOM generation and storage, and runtime signing verification. Describe defenses against compromised CI credentials.
HardTechnical
26 practiced
A Java service in production shows steadily increasing heap usage over weeks and occasional OOMs. Describe a systematic root cause analysis plan using heap dumps, jmap/jstack, GC logs, async-profiler/flamegraphs, and how to identify retained object paths and suspicious classes. Describe short-term mitigations while fixing root cause and long-term practices to prevent recurrence.
MediumTechnical
27 practiced
Your microservice's DEBUG logs flood the logging system during peak hours, causing cost spikes and noise. Propose a comprehensive mitigation strategy: dynamic log-level control, sampling strategies, structured log filtering, buffered logging, tiered storage, and CI/CD changes to reduce verbosity. Explain trade-offs for observability versus cost.
EasyTechnical
30 practiced
For a microservice you own, list the structured log fields you would include to support debugging and postmortems (for example timestamp, request_id, trace_id, user_id, severity, service_name, message). Which logging frameworks have you used (Log4j, python logging, Bunyan) and how do you configure log rotation and retention to control costs?
MediumTechnical
46 practiced
You need to add a new column and a computed index to a live PostgreSQL database without downtime. Provide a migration plan describing steps, tooling options (pg_repack, Liquibase, online schema change techniques), backward compatibility patterns (dual writes, feature flags), and a rollback strategy. Explain how you would validate the schema change before switching the application to the new behavior.
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