Service Composition

This is an advanced example and not necessarily intended to be a "getting started" example.

This example is meant to resemble a somewhat realistic application from a control flow and serialization perspective while demonstrating how ServiceTalk’s API variations enable users to choose their preferred programming model.

Note this example also contains "backend" services which simulate databases and keep the example self contained. These backend services do show more usage of ServiceTalk APIs but are not the focus of the example.

How to run the example?

This example has two distinct bootstrap locations:

  • GatewayServer is a main class and starts only the gateway server with all the endpoints. This server is started on port 8080.

  • BackendsStarter is a main class that starts the other services, viz., Recommendation, Metadata, User and Rating service.


In order to demonstrate a complex service composition usecase, we take the following abstract example:

Gateway Service

A service that composes multiple downstream service results into an externally consumable result.


The result is a complex object FullRecommendation as follows:

public final class FullRecommendation {
    private Metadata entity;
    private User recommendedBy;
    private Rating overallRating;
    // Getters and setters removed for brevity

Each component of this data is fetched from different backends as described below.

Recommendation Backend

A backend service that provides recommendation (entities) for a particular user. Each recommended entity contains:

  • Recommended entity ID.

  • User ID who recommended this entity to this user.

This backend provides a two endpoints:

  1. Streaming: An push based endpoint which keeps pushing new recommendations when available. To simulate real life scenarios, we push a recommendation periodically.

  2. Aggregated: An aggregated endpoint that sends all currently available recommendations as a list of entities.

Since a recommendation returned by this backend is not externally consumable (only contains IDs), this incomplete information is materialized using the following backends:

Metadata Backend

A backend service that provides details about the entity given an entityId.

User Backend

A backend service that provides details about a user given a userId.

Rating Backend

A backend service that provides ratings of an entity given an entityId.


The objective is to demonstrate what will be the different ways in which these service calls can be composed to provide the final materialized result.

Gateway Endpoints

In this example we provide three different endpoints on the gateway server to also demonstrate how different programming paradigms can co-exist in a single HTTP server.

Asynchronous streaming

This is an endpoint that streams FullRecommendation JSON. This is a simulation of a push based API that streams data back to the user as and when it is available. It queries the streaming recommendation endpoint of the recommendation backend described above. This endpoint is implemented as a fully asynchronous HttpService and can be queried using the following URI:


Asynchronous aggregated

This is an endpoint that creates a single JSON array containing one or more FullRecommendations. Although the result is a single JSON array, the elements of the array are still fetched from the other services asynchronously.

This endpoint can be queried using the following endpoint:



This is an endpoint that uses blocking Http client and server APIs to sequentially query all other services for each recommendation.

This endpoint can be queried using the following endpoint:


Error Handling

This example also demonstrates checking the response status, and handling unexpected status codes. Making a request with with the simulateError query parameter will trigger a 500 Internal Server Error response from the appropriate backend service for the following values: - recommendation-service - metadata-service - user-service - rating-service



The Gateway services implement a "fallback" for the Rating service only, which can be seen as -1 ratings in the response.