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// case study
Proptech

End-to-End QA Infrastructure — Built from Zero

Built the entire testing infrastructure from scratch as sole QA engineer for a high-traffic property platform.

Skyloov Property Portal

500+Endpoints Covered
1,000Concurrent Users Tested
120KListings at Stake

The Problem

Skyloov was shipping high-risk releases with no test coverage and no performance data, across a platform handling 120K+ property listings. Bugs were reaching production users regularly. There was no definition of what "good performance" looked like, and no way to catch regressions between releases. I was hired as the only QA engineer in a ~12-person engineering team to change this — from day one.

Testing Pipeline Architecture

FUNCTIONAL REGRESSION Dev Commit GitHub push Jenkins Trigger CI pipeline start Newman Run 500+ endpoints tested Test Report Pass/Fail per endpoint Release Gate Block or approve deploy PERFORMANCE TESTING Gatling Script 1,000 virtual users Load Execution 200+ API endpoints Metrics Collected p95 latency · TPS · Errors Grafana Real-time dashboards Baseline Report Per-release benchmarks Also validated: ElasticSearch search relevance · Kafka async workflows · AI chatbot flows

Built two parallel testing tracks that ran every release cycle. Functional track: Postman collections covering 500+ backend endpoints, executed automatically via Newman in Jenkins CI. Performance track: Gatling simulating 1,000 concurrent users across 200+ APIs with p95 latency, TPS, and error rate metrics exported to Grafana dashboards. For the first time, the team had a performance baseline they could compare against after every deployment.

Business Impact

  • 500+ endpoint regression suite running on every deployment — regressions caught before reaching 120K+ property listings users
  • Platform launched successfully across 3 apps (web, iOS, Android) with established pass/fail gates at every release
  • First-ever performance baselines defined: p95 latency, max throughput, error rate thresholds enforced per release
  • AI-powered property search chatbot fully validated across search, support, and lead generation flows before launch
  • ElasticSearch relevance and Kafka async event processing validated under real workload conditions
Stack: PostmanNewmanGatlingGrafana JenkinsElasticSearchKafkaPostgreSQL MongoDBDockerCharles Proxy