How to Build Your Own KrakenD

Create faster interactions with automatic API Composition and aggregation of multiple data sources into a single response

Automatic output encoding and translation (XML, JSON, RSS, noop)

Create an API consumption layer that provides aggregated views of several services and returns only the needed data

Add validation rules to continue with the request or to return the response

Modify the data you return to the end-user, or the payload you send to your services. Filter fields, enrich responses, convert from SOAP, JSON or XML automatically

Write your own Go plugins and side-load them with KrakenD to extend the functionality

With the OpenAPI exporter, you can automatically generate rich documentation websites. Have an OpenAPI? Then, create your API gateway using the OpenAPI specs

Generate Graphviz images displaying your configuration logic

Speed up development with a specific container with hot-reload functionality

Automatic validation as you type, showing documentation while hovering an attribute, explanation of errors, and autocompletion of properties

Check security and best practices recommendations of your configuration before going live

End-User validation and gateway to service validation: JWT, Client credentials, Oauth2, OpenID, API-Keys, Basic Auth, mTLS

OWASP recommendations that add a frame-breaking strategy

Cross-origin resource sharing

Enables the Cross-site scripting (XSS) filter in the user's browser

Authenticate users with API keys in headers or query strings

Service-to-service authentication using AWS SigV4 service accounts

Authentication of requests based on .htpasswd files

OAuth 2.0 Client Credentials Grant to automatically request access tokens before reaching the backend's protected resources

Service-to-service authentication using Google Cloud service accounts

Receives all the traffic from routes and methods that do not resolve to any of the other existing endpoints in the configuration

Route requests to one or multiple backends based on request headers or custom policy expressions

Allow the end-user to follow redirects set by services instead of the gateway resolving them

Header and query string processing to assemble the final upstream URL

JSON Web Token processing to assemble the final upstream URL

Granular token usage monitoring and enforcement to keep your AI expenses transparent and within budget

Ability to connect endpoints to AI providers and models

Enforce compliance, security, and operational guardrails inline with AI traffic

From isolated authorization flows to data masking and exfiltration prevention

Use Google's Gemini AI without writing custom integration code

Extends the flexible config adding $ref, nested directories, multiple settings file formats, conflict handling, debugging and more

Declare the configuration using templates and environment-specific values

Write the configuration in JSON, YAML, TOML, HCL and more

Store backend responses in memory to reduce the number of calls a user sends to the origin, reducing the network traffic and alleviating your services' pressure

Set automatically cache headers for CDN or intermediate caching