High Quality Code

High Velocity Business

Keploy turns real production traffic into regression tests, blocks flaky code from reaching main, and surfaces actionable quality metrics on every pull request — so defects are caught before they ship.

Synthetic tests (whether hand-written or AI-generated) reflect assumptions about how code should behave. Production traffic tests capture how code actually behaves under real user load — including edge cases, unusual payloads, and dependency failure modes that synthetic approaches miss. Keploy converts this traffic into regression tests that validate the code paths users actually exercise, not theoretical ones.

Static analysis catches syntax issues, type errors, and known vulnerability patterns, but cannot detect runtime behavior problems. Keploy captures actual response correctness, latency regressions, dependency interaction failures, data serialization bugs, and race conditions from real traffic — the class of defects responsible for most production incidents that static analysis tools fundamentally cannot detect.

Keploy runs replayed traffic tests on every pull request and fails the CI check if new code paths lack test coverage or if existing tests regress. Unlike traditional coverage tools that only measure line coverage, Keploy validates actual API behavior against recorded baselines, catching semantic regressions (correct line coverage but wrong output) that code coverage percentages miss entirely.

Instrumentation-based tools (JaCoCo, Istanbul, coverage.py) inject bytecode or runtime hooks that add 5-30% execution overhead and can alter timing-sensitive behavior. Keploy's eBPF probes run in the Linux kernel's networking stack with sub-microsecond overhead, capturing traffic without touching the application runtime. This means production recordings are safe to run continuously without performance impact.

Yes. Native actions exist for GitHub and Jenkins. A single CLI step runs the tests and fails the job if new regressions or coverage regressions are detected.

Absolutely. Because Keploy operates at the network layer, it supports monoliths and microservices alike — no framework rewrites required. This makes it uniquely suited for adding quality gates to legacy systems that were never designed for testability.

Most escaped defects (bugs that reach production) occur in code paths that lack test coverage or have tests that validate structure but not semantics. Keploy's traffic-based tests validate actual API responses against production baselines, catching behavioral regressions that pass traditional assertions. Teams typically see a 30-50% reduction in escaped defects within two sprints of adopting Keploy as a CI gate.