What Functionize Can’t Test, Keploy Cancatch what breaks
Auto-Generated API Tests from Traffic vs AI-Powered Autonomous Testing
Keploy auto-generates API tests from real production traffic using eBPF with zero code changes. Functionize is an AI-powered testing platform that uses machine learning and NLP to create, execute, and maintain functional tests for web and API with minimal manual intervention. Keploy captures real behavior; Functionize applies ML models to predict and stabilize test outcomes.
eBPF · zero code changesHow Keploy turns real traffic into a test suite
One pipeline, running the moment your app receives a request. No SDKs, no sidecars, no test scripts — just kernel-level capture that becomes deterministic regression coverage.
- 01Real API trafficLive requests + responses from your running app
- 02eBPF captureKernel-level recording — zero code changes
- 03NormalizeTime-freeze + field noise removed automatically
- 04Generate testsDeterministic test cases from actual behavior
- 05Generate mocksEvery downstream dependency stubbed for you
- 06Replay in CIRuns locally, in CI, or in-cluster on Kubernetes
- 07Regression detectionDiffs flagged before they reach production
See how the capture-replay engine works under the hood.
Trusted by engineering teams at scale
Why teams switch from Functionize
Keploy eliminates manual test authoring by generating tests automatically from real traffic — no scripts, no stubs, no infrastructure setup.
Want automatic test generation from real traffic without ML training periods
Need automatic mock generation for databases and downstream services
Prefer deterministic test replay over ML-predicted test behavior
The numbers behind the switch
Industry data on how much manual testing costs teams — and what Keploy delivers from the first recording session.
Writing tests, configuring mocks, debugging flakiness — not building features that ship.
A routine rename or interface change silently invalidates more than half your suite.
Keploy generates tests from every request your API actually handles — no guessing.
Traffic capture reaches edge cases, error paths, and concurrent requests no dev would write.
Pain stats sourced from developer productivity surveys. Coverage stats from Keploy production recording sessions across 50+ engineering teams.
Every number here comes from teams running Keploy in CI.
Zero code. Real tests. Automatically.
Keploy's eBPF agent intercepts every API call at the kernel level and turns live traffic into test cases with dependency mocks — no SDK, no sidecars, no annotations.
Incoming API Requests
Keploy Agentrecording · analyzing · generatingEvery API call your app makes gets captured, replayed as a test, and its dependencies auto-mocked — continuously, from real traffic.
How they compare, dimension by dimension
A logical breakdown across the dimensions that matter. Click any row for real-world KPI impact across industries.
Auto-generates from captured production traffic via eBPF
ML-powered test creation from NLP steps or recorded interactions
Zero code changes needed to instrument or capture
No code required — NLP and visual recording interfaces
Auto-generates mocks for all downstream dependencies
No built-in mock generation for service dependencies
Built-in time-freezing and field normalization
ML models learn to handle dynamic content patterns
Native CLI integration with any CI pipeline
API-based CI integration for triggering test runs
Language-agnostic — captures at network level
Language-agnostic — ML tests work with any web or API
KeployClick any dimension to see real-world KPI impact across industries.
Dive into how each capability actually works.
Your tests miss more than you think
Manual tests cover paths developers remember to write — usually just the happy path. Keploy captures every pattern production traffic actually generates.
Coverage grid shows 8 common endpoints × 10 production scenario types. Manual tests cover only what developers remember to write. Keploy captures every pattern your API actually serves in production.
Keploy is open source — read the code that captures this coverage.
The infrastructure you're maintaining
Traditional testing stacks require a shadow infrastructure to exist alongside your real app. Keploy eliminates all of it — tests and mocks come from actual traffic, not from services you run and maintain.
How they work differently
Architectural differences that affect workflow, cost, and velocity.
KeployeBPF-basedKeploy uses eBPF to record real API calls and responses from your running application, then replays them as regression tests. It auto-generates mocks for downstream dependencies and handles non-deterministic data automatically. No ML training or NLP step writing required.
Functionize uses machine learning models trained on application behavior to create and maintain tests. Teams write tests in natural language or record browser interactions. The ML engine analyzes changes and self-heals tests when the application evolves. For API testing, it provides ML-assisted request building and response validation.
When to use each tool
Specific scenarios where each tool delivers the most value.
Keploy is the better fit when…
- Want automatic test generation from real traffic without ML training periods
- Need automatic mock generation for databases and downstream services
- Prefer deterministic test replay over ML-predicted test behavior
- Want open-source, self-hosted tooling without cloud platform dependency
- Need tests that start working immediately, not after ML model training
Functionize is the better fit when…
- Want ML-powered autonomous test creation and maintenance
- Need visual and functional web testing alongside API testing
- Prefer natural language test authoring with AI interpretation
- Want predictive analytics on test failures and application quality
- Are willing to invest in ML training time for long-term maintenance savings
Compare the full workflow for your own stack.
The workflow you're escaping
Same starting point, same finish line. One path is short because Keploy does the tedious middle for you — the other is where teams lose days every sprint.
Without Keploy (Functionize / manual)
Every dependency is your problem, and every code change ripples back through the test suite you hand-built.
With Keploy
Record once from real traffic, replay anywhere. Tests and mocks are generated and stay in sync automatically.
Cut the maintenance middle out of your test suite.
The test maintenance trap
With Functionize, every feature commit generates a hidden tax — a follow-up "fix tests" commit. The commit history tells the whole story.
Deterministic replays, no flaky tests — see how.
Switch from Functionize in minutes
Choose the path that fits your workflow. Both are up and running the same day.
Install, record real API traffic, then replay it as regression tests — zero code changes, zero framework dependencies.
# 1. Installcurl --silent -O https://keploy.io/install.sh && source install.sh# 2. Record your traffickeploy record -c "your-start-command"# 3. Replay as testskeploy test -c "your-start-command" --delay 10Paste your cURLs, drop in an OpenAPI spec or Postman collection, and click Generate. Keploy builds your test suite in seconds.
Real-world scenarios
How Keploy handles the challenges your team actually faces.
Your team ships 50 PRs/week and needs regression coverage
Keploy captures traffic and generates regression tests that run in CI immediately. No ML training period. Coverage is available from day one.
Functionize's ML models improve over time but need a training period. Once trained, autonomous maintenance reduces flaky tests. Initial setup takes longer but pays off for stable test suites.
You're migrating from monolith to microservices
Keploy records monolith traffic, generates dependency mocks, and verifies microservice equivalence automatically. No ML models to retrain during migration.
Functionize can test new microservice APIs, but ML models trained on monolith behavior may need retraining for new service architectures. The transition period adds overhead.
Join the teams shipping with confidence on Keploy.
What you write vs what Keploy writes
The same test coverage — one approach takes hours of setup and ongoing maintenance, the other takes five minutes and zero boilerplate.
Every new endpoint needs a new file. Every refactor breaks tests. Every non-deterministic value (timestamps, IDs) needs custom handling.
Keploy captures the real request, response, and all dependency calls. Non-deterministic fields are auto-detected and excluded from assertions.
Frequently asked questions
Common questions about choosing between Keploy and Functionize.
Still have questions? The docs and community can help.
Looking for a Functionize alternative?
Engineering teams evaluating Functionize alternatives often compare it with Keploy for API testing and regression coverage. Keploy captures real production traffic via eBPF and auto-generates tests with dependency mocks — requiring zero code changes. The key differences come down to how tests are generated (traffic-based vs manual), how dependencies are mocked (automatic vs configured), and what infrastructure changes are needed (none vs SDK/sidecar/containers).
Ready to stop writing tests manually?
Keploy captures your real API traffic and turns it into a regression suite automatically. Zero code changes. Full coverage from day one.