Backend roadmap
The Performance Testing Roadmap
Performance testing goes wrong when it starts with a tool instead of a question. This roadmap starts with the question — what workload, what threshold, what evidence — and then builds the Locust project and dashboards that answer it.
The roadmap, stage by stage
Stage 1 — Workload modelling
Define realistic user journeys and their weights before writing a single script. A load test that does not resemble production traffic proves nothing.
- Journey identification
- Weighting and think time
- Target thresholds agreed up front
Stage 2 — Locust in code
Write load tests as Python so they live in version control, get reviewed, and scale out the same way your services do.
Stage 3 — Observability
Numbers without context are noise. Export metrics to Prometheus and build Grafana dashboards showing latency percentiles, error rate and throughput together.
- p50 / p95 / p99 latency
- Error rate
- Throughput and saturation
Stage 4 — Modern targets
APIs are no longer the only load-bearing surface. LLM endpoints have latency and cost characteristics that deserve the same treatment.
Skills you'll gain
- Workload modelling
- Locust scripting
- Prometheus metrics
- Grafana dashboards
- API performance analysis
Why it matters for your career
Performance engineers are consistently scarce, and the skill pairs naturally with API ownership and SRE-adjacent work.
Recommended learning path
Performance & API Testing at Scale
Own performance and API quality end-to-end: Locust load tests, REST Assured suites, and AI agents that write API tests for you.
3 courses · ~11 hours · Intermediate → Advanced
View the full path →Recommended courses
Performance
Scalable Performance Testing with Locust and Python
Design, execute, and monitor performance tests with Locust, Prometheus, and Grafana
2 hours · All Levels
Selenium / Java
Enterprise QA Automation with Java, Selenium & APIs
Scalable web and API automation with TestNG, Selenium, REST Assured and AI
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AI Agents
AI Agent: Automated QA Test Case Generator and Executor
Build an AI agent for API test automation using Python, JIRA-API & GenAI
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FAQ
Locust or JMeter?
Locust when you want code-first tests in Python and easy horizontal scaling; JMeter when your organisation is already invested in it.
What should I report?
Latency percentiles, error rate and throughput against an agreed threshold — never averages alone.
Can I run load tests in CI?
Yes, as a scaled-down smoke load per build, with full runs on a schedule.
Not sure where you fit on this roadmap?
Take the quiz for a personalised path, or ask Tia — she'll build a plan around your experience.