01 What is Performance Testing?
Why correctness and performance are two different, both-necessary questions, and where dedicated performance testing fits relative to the QA-level performance checks earlier paths already taught.
02 Performance Metrics and SLAs
Latency, throughput, error rate, and resource utilization as the core performance metrics, and how a meaningful SLA threshold is set versus an arbitrary round number.
03 Performance Testing Strategy
Deciding what actually deserves dedicated performance testing, in what order test types should run, and what a performance test strategy needs to capture before execution begins.
04 Performance Testing Types
Load, stress, spike, soak, and volume testing — five variations on how load is shaped over time, each answering a distinct question no other type answers as well.
05 Performance Test Environment
Why a performance test run against a scaled-down or misconfigured environment produces numbers that don't transfer to production, and what 'close enough to production' actually requires.
06 Test Data for Performance
Realistic data volume and shape for a dedicated performance test, building directly on Database Testing's own small-test-data lesson rather than re-teaching it.
07 Performance Testing Tools
The concepts every performance testing tool has to implement, and how JMeter (this path's primary worked example, not the canonical tool) implements each one.
08 Executing the Five Test Types
Practical configuration guidance for each performance test type — how ramp-up, duration, and load target differ deliberately across load, stress, spike, soak, and volume tests.
09 Bottleneck Analysis and Monitoring
Reading monitoring data during a test run to identify which specific resource is actually the constraint, not just that response time degraded.
10 Result Analysis and Reporting
Turning a raw, correlated performance finding into a defensible result — communicated appropriately to both an engineering audience and a non-technical stakeholder.
11 Capacity Planning
Using a confirmed performance ceiling and real growth trends to forecast when current infrastructure will no longer meet demand, and what a credible capacity recommendation includes.
12 Performance Defect Investigation
A systematic, repeatable trace from 'the system feels slow' to a specific, reproducible root cause — tying this path's entire toolkit together into one investigation process.
13 Applying Performance Testing: AtlasBank Validation
Combining strategy, test design, execution, and analysis from Sections 1-4 against a realistic, integrated AtlasBank loan-application feature under load.
14 Applying Performance Testing: AtlasShop Validation
Applying this path's full toolkit against AtlasShop's bursty, sale-driven checkout traffic — a deliberate contrast to AtlasBank's steady banking load shape.
15 Common Mistakes in Performance Testing
Six performance-testing mistake patterns spanning readiness assumptions, metrics, strategy, test-type configuration, environment realism, and incomplete reporting — each traced back to a real defect earlier in this path.
16 Performance Testing Interview Scenarios
Multi-part interview scenarios requiring synthesis across this path's full toolkit, distinct from the single recall-style questions each individual module already covers.
17 Capstone: End-to-End Performance Verification
The complete performance-testing lifecycle applied to AtlasBank's International Money Transfer feature — evaluating the operational cost, under production-scale load, of the already-correct implementation four prior certified paths verified.
Section 1 — Review
A recap of Performance Testing Foundations — correctness vs. performance, core metrics and SLAs, and risk-based test strategy — plus a Knowledge Check.
Section 1 — Solutions
Answers and reasoning for Section 1's Knowledge Check — applying correctness-vs-performance, percentile metrics, and risk-based strategy to five realistic scenarios.
Section 2 — Review
A recap of Designing a Performance Test — the five test types, environment parity, and realistic test data — plus a Knowledge Check.
Section 2 — Solutions
Answers and reasoning for Section 2's Knowledge Check — applying test-type selection, environment parity, and realistic test data to five realistic scenarios.
Section 3 — Review
A recap of Executing Performance Tests — concept-first tool literacy, per-type test configuration, and bottleneck correlation — plus a Knowledge Check.
Section 3 — Solutions
Answers and reasoning for Section 3's Knowledge Check — applying tool neutrality, per-type configuration, and bottleneck correlation to five realistic scenarios.
Section 4 — Review
A recap of Analysis and Operations — dual-audience reporting, capacity forecasting, and systematic defect investigation — plus a Knowledge Check.
Section 4 — Solutions
Answers and reasoning for Section 4's Knowledge Check — applying dual-audience reporting, capacity forecasting, and systematic defect investigation to five realistic scenarios.