Feature Service


When developing new application features, it is often advantageous to provide a programmatic mechanism that allows us to control their visibility to the user. This approach is often referred to as a feature toggle or feature flag. The feature toggle mechanism enables us to:

  • Minimize the number of feature branches required.
  • Release versions of the application that disables unfinished features.
  • Release features to a specific set of users for analysis and testing.

In the FeatureService, we will build, the service provides a single endpoint that can be queried based on the application client type and the user account id to deliver a customized collection of feature toggle values.


Before you get started, you will need the following:
  • Java
  • Maven
  • Docker
  • Docker-Compose
Refer to the Development Toolbox article if you do not have these installed locally.

Building the Feature Service

Feature Service Hexagonal diagram

The FeatureService provides an application client with a feature set. In this implementation, the feature set is composed of a collection of key-value pairs, each representing an individual feature's visibility. The feature set returned to the application client is determined by the application client type, feature set name, and the current application client's user account id. By providing the combination of application client type, feature set name, and account id, the service can control visibility based on the type of application client (e.g., browser, mobile, IoT) as well as the individual user. The FeatureService provides a basic implementation that stores each feature set as a properties file in its local classpath. The service uses the feature set name and the application client type to locate the file and returns its contents as a JSON encoded object. Currently, the service implementation does not provide user-level customization, so the account id value is ignored.

The source

Maven pom.xml


Service Configuration



Not much different in this bootstrap file except for the spring.application.name



Feature Controller


The FeatureController provides the REST endpoint for our service implementation. Is exposes a single endpoint method /lookup. This method interprets the FeatureSetRequest model, and returns a custom array of feature key:value pairs.

Feature Set Request model


Feature Service


The FeatureService defines a single interface method: getFeatureSet.

Classpath Feature Service Impl


The ClasspathFeatureServiceImpl implements the FeatureService to provide a simple, classpath-based feature-set resource lookup. By concatenating the featureSetName and the clientApplicationType, we create the path to the local classpath properties file containing the custom feature set. The service implementation then loads the contents of the properties file and returns it to the caller.

Docker Compose

We continue the process of extending our Docker-Compose file. Here we include our FeatureService


Feature Service In Action

We can copy the Docker-Compose file above to your local machine and run it from the command prompt:

 docker-compose -f ./dc-12-feature.yml up -d

Exercising the Swagger Interface

Once all the services have started, navigate to the following url: http://localhost:3550/swagger-ui.html and you should arrive at the Feature Service REST API page.

Swagger-UI Feature service methods

The Swagger interface contains a single endpoint method /lookup

If we expand the /lookup method and click the Try it out button, we are presented with the method form.

Swagger-UI Feature service lookup form DEFAULT

We provide it with our desired values (in this case we are requesting the DEFAULT featureSetName and applicationClientType) and a valid Authorization token and click Execute.

Swagger-UI Feature service lookup response DEFAULT In the DEFAULT feature set, we get a single response: "enable.video.chat":"false" .

Here we call the service with the featureSet to VIDEO: Swagger-UI Feature service lookup form VIDEO

we get:

Swagger-UI Feature service lookup response VIDEO

Metrics and Monitoring

The Telemetry Service generates the following service-level metrics:
  • telemetry.query.id.total
  • telemetry.query.account.total
  • telemetry.event.created.total
  • telemetry.delete.total
These four metrics allow us to monitor profile creation, updates and deletes that are being made by the service.

To visualize this data, we will import the TelemetryDashboard.json file from the ThinkMicroservices Github Dashboards repository. The dashboard should appear as:

Grafana Telemetry Dashboard


Coming Up

In our next article, we will build a Peer-Signaling Service that will provide our application with the ability to support browser-to-browser voice, video, and data communications.