I started with the client side, checking network latency, DNS resolution, browser rendering.
Start by clarifying the scope and impact of the slowness, then systematically narrow down the root cause using a top-down approach across the client, network, and server layers. Propose both immediate mitigations and long-term fixes, emphasizing monitoring and prevention.
Pro tip: Demonstrate a data-driven mindset by mentioning specific metrics (e.g., p95 latency, error rates) and tools (e.g., CloudWatch, X-Ray) to validate hypotheses before jumping to solutions. This shows you prioritize evidence over assumptions.
Ask clarifying questions to understand the extent of the issue: Is it affecting all users or a subset? Is it specific to certain pages or regions? When did it start? This helps define the problem and prioritize investigation.
Check monitoring dashboards (e.g., latency, error rates, throughput) and logs to identify anomalies. Use tools like CloudWatch, X-Ray, or APM solutions to pinpoint where the slowdown occurs (client, network, server, database).
Based on data, hypothesize potential causes (e.g., increased traffic, database bottleneck, third-party service degradation) and test them systematically, isolating variables to confirm or eliminate each.
Apply immediate mitigations (e.g., scaling resources, caching, rolling back recent changes) to restore performance, then address the root cause with a permanent solution (e.g., code optimization, infrastructure changes).
After the fix, monitor key metrics to ensure resolution, conduct a post-mortem to identify gaps, and implement preventive measures (e.g., better alerting, capacity planning, chaos testing).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.