APIClarity

Reconstruct OpenAPI Specifications from real-time workload traffic seamlessly.

Microservices API challenges

• Not all applications have an OpenAPI specification available
• How can we get this for legacy or external applications?
• Detect whether microservices still use deprecated APIs (a.k.a. Zombie APIs)
• Detect whether microservices use undocumented APIs (a.k.a. Shadow APIs)
• Generate OpenAPI specifications without code instrumentation or modifying existing workloads (seamless documentation)

Solution

• Capture all API traffic in an existing environment using multiple traffic sources
• Construct an OpenAPI specification by observing API traffic or upload a reference OpenAPI spec
• Review, modify and approve automatically generated OpenAPI specs
• Alert on any differences between the approved API specification and the API calls observed at runtime; detects shadow & zombie APIs
• UI dashboard to audit and monitor the findings

High level architecture

Getting started

Supported traffic source integrations

APIClarity supports integrating with the following traffic sources. Install APIClarity and follow the instructions per required integration.

• Istio Service Mesh

  • Make sure that Istio 1.10+ is installed and running in your cluster. See the Official installation instructions for more information.

• Tap via a DaemonSet

  • Integration instructions

• Kong API Gateway

  • Integration instructions

• Tyk API Gateway

  • Integration instructions

The integrations (plugins) for the supported traffic sources above are located in the plugins directory within the codebase and implement the plugins API to export the API events to APIClarity. To enable and configure the supported traffic sources, please check the trafficSource: section in Helm values. Contributions of integrations with additional traffic sources are more than welcome!

Install APIClarity in a K8s cluster using Helm:

1. Add Helm repo

   helm repo add apiclarity https://apiclarity.github.io/apiclarity

2. Save APIClarity default chart values

   helm show values apiclarity/apiclarity > values.yaml

3. Update values.yaml with the required traffic source values

4. Deploy APIClarity with Helm for the selected traffic source

   helm install --values values.yaml --create-namespace apiclarity apiclarity/apiclarity -n apiclarity

5. Port forward to APIClarity UI:

   kubectl port-forward -n apiclarity svc/apiclarity-apiclarity 9999:8080

6. Open APIClarity UI in the browser: http://localhost:9999/

7. Generate some traffic in the traced applications and check the APIClarity UI :)

Configurations

The file values.yaml is used to deploy and configure APIClarity on your cluster via Helm. This ConfigMap is used to define the list of headers to ignore when reconstructing the spec.

Testing with a demo application

A good demo application to try APIClarity with is the Sock Shop Demo.

To deploy the Sock Shop Demo, follow these steps:

1. Create the sock-shop namespace and enable Istio injection:

   kubectl create namespace sock-shop
   kubectl label namespaces sock-shop istio-injection=enabled

2. Deploy the Sock Shop Demo to your cluster:

   kubectl apply -f https://raw.githubusercontent.com/microservices-demo/microservices-demo/master/deploy/kubernetes/complete-demo.yaml

3. Deploy APIClarity in the sock-shop namespace (e.g. Istio service-mesh traffic source):

   helm install --set 'trafficSource.envoyWasm.enabled=true' --set 'trafficSource.envoyWasm.namespaces={sock-shop}' --create-namespace apiclarity apiclarity/apiclarity -n apiclarity

4. Find the NodePort to access the Sock Shop Demo App

   $ kubectl describe svc front-end -n sock-shop
   [...]
   NodePort:                 <unset>  30001/TCP
   [...]

   Use this port together with your node IP to access the demo webshop and run some transactions to generate data to review on the APIClarity dashboard.

Building

Building from source:

Build and push the image to your repo:

DOCKER_IMAGE=<your docker registry>/apiclarity/apiclarity DOCKER_TAG=<your tag> make push-docker

Update values.yaml accordingly.

Running locally with demo data

1. Build UI & backend locally as described above:

   make ui && make backend

2. Copy the built site:

   cp -r ./ui/build ./site

3. Run backend and frontend locally using demo data:

   DATABASE_DRIVER=LOCAL FAKE_TRACES=true FAKE_TRACES_PATH=./backend/pkg/test/trace_files \
   ENABLE_DB_INFO_LOGS=true ./backend/bin/backend run

4. Open APIClarity UI in the browser: http://localhost:8080/

Contributing

Pull requests and bug reports are welcome.

For larger changes please create an Issue in GitHub first to discuss your proposed changes and possible implications.

License

Apache License, Version 2.0