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Performance Engineering: JMeter, k6 and System Diagnosis

From measurement fundamentals to an independent performance investigation: JMeter and k6, JVM and garbage collection, CPU, databases, pools and queues, Prometheus, Grafana, logs, tracing and profiling. Beginner explanations, diagrams, local laboratories, quizzes and an evidence-based capstone.

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From measurement fundamentals to an independent performance investigation: JMeter and k6, JVM and garbage collection, CPU, databases, pools and queues, Prometheus, Grafana, logs, tracing and profiling. Beginner explanations, diagrams, local laboratories, quizzes and an evidence-based capstone.

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Leçon 1What Performance Testing measures

Theory and practice

  • ArticlesWhat Performance Testing measures
Leçon 2Workload models

Theory and practice

  • ArticlesWorkload models
Leçon 3Your first k6 test

Theory and practice

  • ArticlesYour first k6 test
  • Contrôle des connaissancesCheck your understanding
Leçon 4Experiment types and recovery

Theory and practice

  • ArticlesExperiment types and recovery
Leçon 5Diagnosis and hypothesis testing

Theory and practice

  • ArticlesDiagnosis and hypothesis testing
Leçon 6Comparison and the capstone

Theory and practice

  • ArticlesComparison and the capstone
  • Contrôle des connaissancesCheck your understanding
Leçon 7JMeter: from the first launch to a correct journey

Theory and practice

  • ArticlesJMeter without mystery: installation and test anatomy
  • ArticlesHTTP in JMeter: address, body, headers and timing
  • ArticlesThreads, ramp-up and loops: what work are we scheduling?
  • ArticlesDebugging a business journey: login to an order retry
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 8JMeter: data, correlation, assertions and user pacing

Theory and practice

  • ArticlesCSV and data ownership: independent users
  • ArticlesCorrelation: tokens, cookies and dependent requests
  • ArticlesAssertions and Groovy: verify meaning without unnecessary cost
  • ArticlesThink time, pacing and timers: defining behavior
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 9JMeter: CLI, results and generator reliability

Theory and practice

  • ArticlesFrom GUI to CLI: reproducible runs and JTL
  • ArticlesReading a JMeter report: from tables to a defensible conclusion
  • ArticlesWhen the load generator is the bottleneck
  • ArticlesJMeter plugins and distributed runs: installation, examples and limits
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 10k6: scenario code, lifecycle and criteria

Theory and practice

  • Articlesk6 as a program: init, setup, VU and teardown
  • ArticlesAn HTTP journey in k6: correlation and business validation
  • ArticlesSharedArray, VU and iteration: who owns the data?
  • ArticlesChecks, custom metrics and thresholds: when a test actually fails
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 11k6: workload models, VU capacity and the browser

Theory and practice

  • ArticlesExecutors: choose a model for the experiment question
  • ArticlesDropped iterations: why a fast test can miss its objective
  • ArticlesTags, groups and per-operation criteria
  • Articlesk6 browser, extensions and CI: setup and complete examples
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 12How the system works: requests, CPU, networking and containers

Theory and practice

  • ArticlesThe request path and latency budget
  • ArticlesProcesses, threads, CPU and event loops without confusion
  • ArticlesNetworking: DNS, TCP, TLS, KeepAlive and measurement boundaries
  • ArticlesOS and container resources: quotas, RSS, disk and queues
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 13JVM and garbage collection: memory, mechanisms and tradeoffs

Theory and practice

  • ArticlesWhat is a garbage collector? Objects, references and live memory
  • ArticlesHow GC finds and reclaims memory: generations, pauses and barriers
  • ArticlesG1, Serial, Parallel and ZGC: choosing an experiment
  • ArticlesTuning heap, CPU and pauses: change a cause, not a flag collection
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 14Memory diagnosis: GC logs, JFR, leaks and other runtimes

Theory and practice

  • ArticlesReading GC logs and post-collection trends
  • Articlesjcmd, JFR and thread dumps: match the tool to the question
  • ArticlesRetention and leaks: establishing that data lives too long
  • ArticlesGC in Node.js and Python: what transfers and what does not
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 15Prometheus and Grafana: from measurement to a readable dashboard

Theory and practice

  • ArticlesObservability architecture: metrics, logs, traces and profiles
  • ArticlesCounters, gauges and histograms: modeling a metric correctly
  • ArticlesPromQL: rates, aggregation, p95 and the correct denominator
  • ArticlesGrafana: a dashboard that supports investigation
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 16Logs, traces, profiles and telemetry reliability

Theory and practice

  • ArticlesStructured logs, Loki and LogQL
  • ArticlesOpenTelemetry and Tempo: reading a trace beyond a long bar
  • ArticlesProfiles and cross-signal analysis: testing an explanation
  • ArticlesTelemetry gaps, alerts and observability cost
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 17Bottleneck diagnosis: from symptoms to mechanism

Theory and practice

  • ArticlesCPU and locks: why threads stop making progress
  • ArticlesSQL: plans, indexes, statistics and locks
  • ArticlesConnection pools, queues and backpressure
  • ArticlesCaches, I/O and dependencies: bottlenecks beyond CPU
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 18Overload, capacity and recovery

Theory and practice

  • ArticlesLoad, stress, spike, endurance and data volume
  • ArticlesTimeouts, deadlines, retries and idempotency
  • ArticlesCapacity, scaling and resource headroom
  • ArticlesRecovery, degradation and experiment boundaries
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 19Statistics, SLOs and evidence-based decisions

Theory and practice

  • ArticlesPercentiles, histograms and sample adequacy
  • ArticlesWarm-up, repeatability and fair A–B comparison
  • ArticlesSLIs, SLOs, error budgets and release criteria
  • ArticlesExperiment reports and CI checks
  • Contrôle des connaissancesApplied checkpoint: test your conclusions
Leçon 20Capstone: an independent performance investigation

Theory and practice

  • ArticlesDesigning the capstone investigation
  • ArticlesInvestigating an initially unknown slowdown
  • ArticlesA change, repeated comparison and recovery verification
  • ArticlesTechnical defense, portfolio and competence criteria
  • Contrôle des connaissancesApplied checkpoint: test your conclusions