Quickstart for Agent
This topic describes how to quickly get started with Optimizely Agent using Docker or as a Node microservice.
This brief quickstart describes how to run Agent, using two examples:
-
To get started using Docker, see Running locally via Docker.
-
To get started using example Node microservices, see the following video link.
Running locally via Node
Resource | Description |
---|---|
Implementing feature flags across microservices with Optimizely Agent | 4-minute video on implementing Optimizely Agent with example microservices |
Running locally via Docker
Follow these steps to deploy Optimizely Agent locally via Docker and access some of the common API endpoints.
If Docker is not installed then you can download it on Docker's official site.
First, pull the Docker image with:
docker pull optimizely/agent
Then start the service in the foreground with the following command:
docker run -p 8080:8080 --env OPTIMIZELY_LOG_PRETTY=true optimizely/agent
Note that we are enabling "pretty" logs which provide colorized and human-readable formatting.
The default log output format is structured JSON.
Evaluating REST APIs
The rest of the getting started guide will demonstrate the APIs' capabilities. For brevity, we have chosen to illustrate the API usage with Python.
Note
The APIs are also defined via OpenAPI (Swagger) and can be found on localhost
<http://localhost:8080/openapi.yaml>
or online in our API reference documentation.
Start an http session
Each request made into Optimizely Agent is in the context of an Optimizely SDK Key. SDK Keys map API requests to a specific Optimizely Project and Environment. We can set up a global request header by using the requests.Session
object.
import requests
s = requests.Session()
s.headers.update({'X-Optimizely-SDK-Key': '<<YOUR-SDK-KEY>>'})
To get your SDK key, navigate to the project settings of your Optimizely account.
Future examples will assume this session is being maintained.
Get current environment configuration
The /config
endpoint returns a manifest of the current working environment.
resp = s.get('http://localhost:8080/v1/config')
env = resp.json()
for key in env['featuresMap']:
print(key)
Activate Feature
The /activate?featureKey={key}
endpoint activates the feature for a given user. In Optimizely, activation is in the context of a given user to make the relative bucketing decision. In this case we'll provide a userId
via the request body. The userId
will be used to determine how the feature will be evaluated. Features can either be part of a Feature Test in which variations of feature variables are being measured against one another or a feature rollout, which progressively make the feature available to the selected audience.
From an API standpoint the presence of a Feature Test or Rollout is abstracted away from the response and only the resulting variation or enabled feature is returned.
python
params = { "featureKey": "my-feature" }
payload = { "userId": "test-user" }
resp = s.post(url = 'http://localhost:8080/v1/activate', params=params, json=payload)
print(resp.json())
The activate API is a POST to signal to the caller that there are side-effects. Namely, activation results in a "decision" event sent to Optimizely analytics for the purpose of analyzing Feature Test results. A "decision" will NOT be sent if the feature is simply part of a rollout.
Updated 12 months ago