keploy/keploy
Keploy
Keploy is an automated testing platform that leverages kernel-level traffic interception to generate and maintain regression test suites for microservices. By capturing live network traffic and system calls via eBPF, the platform automatically creates deterministic test cases and mocks external dependencies without requiring manual code instrumentation. This approach allows developers to validate application behavior and API contracts by replaying production-like traffic in isolated environments.
The platform distinguishes itself through its use of machine learning to perform test maintenance, including self-healing for brittle tests and the dynamic masking of volatile data like timestamps. It provides comprehensive service virtualization, automatically generating mocks for databases, message queues, and third-party APIs to ensure that tests remain consistent and reproducible across different development and staging environments.
Beyond core regression testing, the system integrates directly into CI/CD pipelines to enforce quality gates, blocking deployments that exhibit schema drift, performance regressions, or coverage gaps. It also includes observability tools that surface actionable insights, such as API reliability metrics and schema coverage analysis, to help teams identify and prioritize potential issues within their distributed systems.
Features
- Regression Test Replayers - Replays captured traffic against application code to verify runtime behavior and identify regressions by comparing responses against recorded baselines.
- eBPF-Powered Replayers - A platform that uses eBPF to capture live network traffic and automatically generate deterministic regression tests and dependency mocks.
- Automated Test Execution - Captures live API traffic to generate and replay deterministic test suites that validate application behavior without manual instrumentation.
- Contract Validators - Verifying communication integrity between services by validating API request and response structures against recorded interaction patterns and schemas.
- Service Virtualization - A solution that records and replays external dependency interactions to isolate microservices for testing without requiring live infrastructure.
- eBPF Interceptors - Captures network and system calls at the kernel level to record application behavior without manual code instrumentation.
- Kernel-Level Traffic Interceptors - Intercepts live network requests at the kernel level to record application behavior without requiring code changes or manual instrumentation.
- Drift Detectors - A system that validates API schemas and detects drift by comparing live traffic against established contract definitions and specifications.
- Dependency Mocking - Records interactions with external services and databases to generate isolated mocks that simulate production behavior.
- CI/CD Pipeline Integrations - Executes generated test suites within automated deployment workflows to detect regressions and enforce quality gates.
- Quality Gates - Blocks code merges based on automated metrics including code coverage, schema drift, and performance regressions.
- Drift Detection - Identifies breaking changes and mismatches by comparing live network traffic against established contract definitions.
- Traffic-Replay Sandboxes - Replays captured production traffic against virtualized dependencies to validate application behavior in isolated environments.
- Deterministic Simulation Environments - Freezes system time and mocks external dependencies to ensure test execution remains consistent across different environments.
- Test Isolation - Ensures consistent test execution by isolating environments and handling dynamic data fields to prevent flaky results.
- Deterministic Value Injection - Freezes system time and masks volatile data during test replays to ensure consistent validation results.
- Automated Mock Generation - Automatically creates mocks for downstream services and databases by observing real traffic patterns during the recording process.
- Self-Healing Test Suites - Uses artificial intelligence to suggest fixes for brittle tests, detect edge cases, and perform self-healing on generated test suites.
- Schema Coverage Analysis - Identifies which parts of an API schema are exercised by existing tests and highlights gaps in test coverage.
- API Clients and Debuggers - AI-powered testing platform for recording traffic and mocking.
- API Testing - Platform that auto-generates unit tests and dependency mocks.
- API Testing Tools - An API testing tool that generates test cases from traffic.
- Frameworks de test - Auto-generates tests and mocks from real traffic using eBPF.
- Continuous Integration Validators - A tool that integrates into CI/CD pipelines to replay captured production traffic and validate application behavior against code changes.
- Test Code Generators - Analyzes code changes in pull requests to automatically create focused test cases that cover happy paths, error paths, and edge cases.
- Test Recording Tools - Records user interactions and API traffic through a browser extension to convert natural navigation into executable integration tests.
- Service Isolation Utilities - Records and replays external dependency interactions during testing to ensure service behavior is verified independently of databases, caches, or third-party APIs.
- UI Self-Healing Tools - Detects changes in UI selectors and updates test definitions using machine learning to reduce the maintenance burden for end-to-end testing suites.
- Schema Validation - Enforces contract expectations and field-level validation against specifications to ensure consistent request and response structures.
- Statistical Masking Utilities - Uses statistical analysis to identify and mask non-deterministic fields like timestamps to prevent flaky test results.
- Test Suites - Creates validated test suites and multi-step API flows from existing specifications to ensure consistent testing coverage.
- Data Masking - Redacts secrets and personal data at capture time before writing to disk to ensure sensitive values never persist in test fixtures or logs.
- Traffic-Based Synthesizers - Analyzes production API interactions to synthesize accurate and realistic data sets for integration testing.
- Test Data Management - Identifies and masks dynamic values like timestamps or sensitive information during test generation to ensure reliable results.
- Message Queue Mocks - Records and replays interactions with message brokers during test execution to isolate application logic from external messaging infrastructure dependencies.
- Autonomous Exploratory Agents - Deploys intelligent agents that use visual reasoning to navigate application interfaces and identify defects without requiring manual test scripts.
- Web Traffic Simulators - Replays captured traffic at higher concurrency levels to measure system performance using actual request sequences and real-world payload distributions.
- Traffic Decryption - Captures TLS-encrypted network data by hooking into library functions to ensure visibility into secure communication channels during the recording process.
- API Monitoring - Surfaces actionable insights from test runs to identify flaky endpoints and performance bottlenecks within distributed systems.
- AI-Powered Bug Prioritization - Analyzes API behavior patterns to identify potential errors and assigns confidence scores to help teams focus on critical issues.
