Pratik QA kursu

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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Ders 1What Performance Testing measures

Theory and practice

MakaleWhat Performance Testing measures

Ders 2Workload models

Theory and practice

MakaleWorkload models

Ders 3Your first k6 test

Theory and practice

MakaleYour first k6 test
Bilgi kontrolüCheck your understanding

Ders 4Experiment types and recovery

Theory and practice

MakaleExperiment types and recovery

Ders 5Diagnosis and hypothesis testing

Theory and practice

MakaleDiagnosis and hypothesis testing

Ders 6Comparison and the capstone

Theory and practice

MakaleComparison and the capstone
Bilgi kontrolüCheck your understanding

Ders 7JMeter: from the first launch to a correct journey

Theory and practice

MakaleJMeter without mystery: installation and test anatomy
MakaleHTTP in JMeter: address, body, headers and timing
MakaleThreads, ramp-up and loops: what work are we scheduling?
MakaleDebugging a business journey: login to an order retry
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 8JMeter: data, correlation, assertions and user pacing

Theory and practice

MakaleCSV and data ownership: independent users
MakaleCorrelation: tokens, cookies and dependent requests
MakaleAssertions and Groovy: verify meaning without unnecessary cost
MakaleThink time, pacing and timers: defining behavior
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 9JMeter: CLI, results and generator reliability

Theory and practice

MakaleFrom GUI to CLI: reproducible runs and JTL
MakaleReading a JMeter report: from tables to a defensible conclusion
MakaleWhen the load generator is the bottleneck
MakaleJMeter plugins and distributed runs: installation, examples and limits
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 10k6: scenario code, lifecycle and criteria

Theory and practice

Makalek6 as a program: init, setup, VU and teardown
MakaleAn HTTP journey in k6: correlation and business validation
MakaleSharedArray, VU and iteration: who owns the data?
MakaleChecks, custom metrics and thresholds: when a test actually fails
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 11k6: workload models, VU capacity and the browser

Theory and practice

MakaleExecutors: choose a model for the experiment question
MakaleDropped iterations: why a fast test can miss its objective
MakaleTags, groups and per-operation criteria
Makalek6 browser, extensions and CI: setup and complete examples
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 12How the system works: requests, CPU, networking and containers

Theory and practice

MakaleThe request path and latency budget
MakaleProcesses, threads, CPU and event loops without confusion
MakaleNetworking: DNS, TCP, TLS, KeepAlive and measurement boundaries
MakaleOS and container resources: quotas, RSS, disk and queues
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 13JVM and garbage collection: memory, mechanisms and tradeoffs

Theory and practice

MakaleWhat is a garbage collector? Objects, references and live memory
MakaleHow GC finds and reclaims memory: generations, pauses and barriers
MakaleG1, Serial, Parallel and ZGC: choosing an experiment
MakaleTuning heap, CPU and pauses: change a cause, not a flag collection
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 14Memory diagnosis: GC logs, JFR, leaks and other runtimes

Theory and practice

MakaleReading GC logs and post-collection trends
Makalejcmd, JFR and thread dumps: match the tool to the question
MakaleRetention and leaks: establishing that data lives too long
MakaleGC in Node.js and Python: what transfers and what does not
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 15Prometheus and Grafana: from measurement to a readable dashboard

Theory and practice

MakaleObservability architecture: metrics, logs, traces and profiles
MakaleCounters, gauges and histograms: modeling a metric correctly
MakalePromQL: rates, aggregation, p95 and the correct denominator
MakaleGrafana: a dashboard that supports investigation
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 16Logs, traces, profiles and telemetry reliability

Theory and practice

MakaleStructured logs, Loki and LogQL
MakaleOpenTelemetry and Tempo: reading a trace beyond a long bar
MakaleProfiles and cross-signal analysis: testing an explanation
MakaleTelemetry gaps, alerts and observability cost
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 17Bottleneck diagnosis: from symptoms to mechanism

Theory and practice

MakaleCPU and locks: why threads stop making progress
MakaleSQL: plans, indexes, statistics and locks
MakaleConnection pools, queues and backpressure
MakaleCaches, I/O and dependencies: bottlenecks beyond CPU
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 18Overload, capacity and recovery

Theory and practice

MakaleLoad, stress, spike, endurance and data volume
MakaleTimeouts, deadlines, retries and idempotency
MakaleCapacity, scaling and resource headroom
MakaleRecovery, degradation and experiment boundaries
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 19Statistics, SLOs and evidence-based decisions

Theory and practice

MakalePercentiles, histograms and sample adequacy
MakaleWarm-up, repeatability and fair A–B comparison
MakaleSLIs, SLOs, error budgets and release criteria
MakaleExperiment reports and CI checks
Bilgi kontrolüApplied checkpoint: test your conclusions

Ders 20Capstone: an independent performance investigation

Theory and practice

MakaleDesigning the capstone investigation
MakaleInvestigating an initially unknown slowdown
MakaleA change, repeated comparison and recovery verification
MakaleTechnical defense, portfolio and competence criteria
Bilgi kontrolüApplied checkpoint: test your conclusions