Enhance Software Performance Testing Using Artificial Intelligence
summary
Proposes concrete AI tasks for performance work: generate test plans, synthesize large unique datasets, and generate Gatling or JMeter scripts from an API spec; prototypes take a JMeter results CSV and use Google Gemini 1.0 to turn JMeter CSV into a test report with averages, medians and 99th percentiles plus query-level recommendations. Mentions integration with Prometheus/Grafana and Splunk for live monitoring, and using ML for server-utilization forecasting and anomaly detection; warns prototypes produce hallucinations and need human review.
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chapters (10)
- 0:00Introduction
- 1:26AI and ML basics
- 4:57Software performance testing
- 7:02Performance testing types
- 12:43From testing to engineering
- 16:37Performance testing workflow
- 27:30AI use cases in testing
- 33:12AI testing tools and limits
- 37:02AI testing challenges
- 40:53Final reflections
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