Python SDK Bulk Event Dispatcher

This is a reference implementation of a bulk event dispatcher for the Optimizely Full Stack Python SDK. The dispatcher defines how events are sent to Optimizely for analytics tracking. Read more in the event dispatcher documentation.

By default, the dispatcher is synchronous and dispatches on a per event basis via separate HTTP calls to Optimizely’s logging endpoint. This implementation batches events and sends in bulk by leveraging a producer/consumer model.

The producer is responsible for writing events to AWS SQS so they can be maintained in a queue. The consumer then runs on AWS Lambda at a set interval to flush the queue. This process aggregates the events and makes a single request to Optimizely.

Architecture

Getting Started

To get started, you will need to setup the consumer and producer using event_dispatcher.py and lambda_function.py, as well as configure the AWS environment and create a Optimizely Python project. If this is your first Optimizely project, check out the getting started guide.

Producer

SQS

1. In AWS, create a new queue called event-queue. Use a standard queue.
2. Configure the settings as needed. I recommend a visibility timeout of 1 min & receive message wait time of 20 secs.

Python SDK

1. This dispatcher should be added to the Python SDK and passed in as follows:

from .event_dispatcher_bulk import EventDispatcher as event_dispatcher

// Create an Optimizely client with the default event dispatcher
optimizely_client = optimizely.Optimizely(datafile,
                                          event_dispatcher=event_dispatcher)

2. Provide the Python SDK with your AWS credentials. Ideally, use environment variables: AWS_KEY & AWS_SECRET. Note: I’ve set the region to us-west-2.

3. The SDK's EventBuilder must use the class EventBuilderV3, which builds events in bulk format. To do this, change the class in optimizely.py here to self.event_builder = event_builder.EventBuilderV3(self.config)

4. Rebuild & install the SDK. Instructions in the Python SDK readme.

Consumer

Lambda

1. In lamdba_function.py provide your Optimizely account_id & project_id. This can be found in your datafile.
2. Create a new lambda function via the blank function template.
3. Add CloudWatch Events as the configured trigger.
4. Create a new rule with a scheduled expression depending on your desired frequency. Ie. rate(1 minute) to flush the queue every minute. Syntax
5. Give the function a name, description and runtime Python 2.7
6. Provide a AWS role policy that provides full access to SQS
7. Upload the function (lambda_function.py) as well as the necessary dependencies via a .ZIP file.
8. Under advanced settings, set the timeout to 1 minute. Depending on the workload, you might need to increase this.
9. Create the function!

Performance

This bulk dispatcher provides many performance and cost saving benefits.

• In the same AWS region, calls to SQS are sub millisecond, whereas hitting Optimizely's endpoint directly is ~60 milliseconds.
• If the Optimizely endpoint is down, events will be safely stored in SQS up to 4 days.
• AWS charges per HTTP call to the outside world. Millions of events can get costly and sending in bulk greatly reduces this.

Next steps

A few thoughts on improvements:

• In event_dispatcher.py, use an async library to write to SQS to improve performance
• Keep the connection to SQS open. Ideally, this should be done when the Optimizely client is initialized and should be persisted.
• Re-try logic: Handle for cases where SQS or Optimizely could be down