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Performance Engineering and Performance Testing

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Description

Performance Engineering Interview Questions and Answers basic to Advanced, Real-time Scenario-Based and Coding Based

Performance Engineering  

  • Foundations: Focus on load testing, basic benchmarking, understanding latency vs throughput, and using tools like JMeter or Gatling for repeatable tests.
  • Profiling and diagnostics: Learn CPU/memory profiling, flame graphs, thread dumps, and root‑cause analysis for hotspots.
  • Application and database tuning: Optimize query plans, connection pooling, caching strategies, and ORM behavior to reduce tail latency.
  • Performance automation: Integrate performance tests into CI pipelines, create performance gates, and automate regression detection.
  • Distributed systems concerns: Study consistency, backpressure, circuit breakers, retries, and idempotency to manage cross‑service performance.
  • Observability for performance: Instrument metrics, traces, and logs; define SLIs for latency and error budgets to drive decisions.
  • Capacity planning and scaling: Model demand, perform capacity tests, and design autoscaling and sharding strategies.
  • Chaos and resilience testing: Inject failures and resource constraints to validate graceful degradation and recovery.
  • Performance at scale (10+ years): Lead architecture reviews, design multi‑tenant and geo‑distributed systems, and set enterprise performance standards.
  • Cost‑performance tradeoffs: Quantify cost vs latency/availability, optimize resource allocation, and recommend right‑sizing.
  • Leadership and process: Establish performance SLAs, run blameless postmortems, mentor engineers on performance culture.
  • Advanced research topics