🤖 Announcing SmartTests: AI powered Contract Testing. Read our CTO's Blog Post here!

Find Every Regression in your Pull Requests

SmartTests validates PRs in a live Kubernetes sandbox, using AI to detect both functional API regressions and non-functional issues like performance drops or memory leaks.
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Catch Regressions before merging code

A Pull Request can introduce functional bugs, performance issues, or memory leaks. Our solution helps you find them by automating deep validation on every code change.
Native Kubernetes Testing
Validate PRs in real K8s environments with actual dependencies, not brittle mocks. Get a true signal of how your code will behave in production.
AI-Powered Risk Analysis
Our AI "diffs" not just API responses but also performance metrics (CPU, memory, I/O) to spot functional and non-functional regressions.
Developer-First Workflow
Test Results are posted as a "relevance score" comment directly in your PR to empower reviewers.

Simple Developer Workflow

Four simple steps to get a risk score for every PR
1
Write Simple Tests
Define API calls in simple starlark language
You only define the API invocations in SmartTests and don't need explicit assertions.
2
Automate in CI/CD
Check every Pull Request for regressions
Seamlessly integrate with your existing CI pipeline to automatically validate each pull request. Tests run in isolated Kubernetes sandboxes, providing realistic environments.
3
Compare Service Versions
See exactly how changes affect your functional and non-functional behavior
SmartTests run against baseline and PR versions, capturing real API requests and responses. This approach detects actual behavior changes that static analysis might miss.
4
Get AI-Powered Insights
Focus on meaningful changes, not false alarms
Our AI model spots meaningful behavioural changes, filtering out false positives to help developers focus only on changes that indicate a regression.
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Powered by AI

Our AI model provides holistic risk analysis. It performs a deep semantic diff on API responses to find functional and non-functional regressions.

Frequently Asked Questions

Is this a contract testing tool like Pact?

No. SmartTests is not a direct alternative to consumer-driven contract testing tools like Pact. SmartTests is a provider-focused validation tool that gives you a "risk score" for your PR by analyzing its runtime behavior, rather than coordinating contracts between consumer/provider teams.

How does the AI system in SmartTests work?

The AI system performs two main functions: First, it analyzes API responses from both versions to identify structural, data type, and content differences. The models determine which differences actually impact compatibility rather than flagging every change.

Second, it reduces test flakiness by learning from historical test runs, distinguishing between expected variations (timestamps, random IDs) and genuine breaking changes. The system adapts to your specific APIs over time, improving its accuracy with continued use.

What kinds of contract breakages can SmartTests detect?

SmartTests detects:
- Schema changes: Removed fields, changed data types, altered object structures
- Behavioral changes: Different response codes, new error conditions, altered validation rules

Because SmartTests observes runtime behavior rather than just validating static schemas, it can identify subtle issues that traditional approaches miss.

How can SmartTests be integrated with my CI/CD pipeline?

Integration requires two components:
1) The Signadot CLI integrated into your pipeline to create sandboxes for each PR
2) Smart Test triggers configured to automatically run tests against those sandboxes

How long does it take to set up SmartTests?

Most teams have their first SmartTests running in under an hour:
1) Install the Signadot operator on your Kubernetes cluster (10-15 minutes)
2) Write your first test in Starlark to call your API endpoints (5-10 minutes)
3) Configure triggers to run the test on your sandboxes (5 minutes)
4) Integrate sandbox creation with your CI/CD pipeline (15-30 minutes)

Since SmartTests runs against your existing staging/pre-production environment, you avoid the typically time-consuming process of setting up separate test environments or managing test data.

What is the maintenance overhead of SmartTests when APIs change?

SmartTests minimizes maintenance when APIs evolve:
- When you make compatible API changes (adding fields, extending functionality in backward-compatible ways), SmartTests automatically recognizes these as non-breaking and doesn't require test updates.
- For intentional breaking changes, you typically only need to update the test code that calls the changed endpoints - not assertions or expectations, since those are handled by the AI comparison system.