Dev guideAPI Reference
Dev guideAPI ReferenceUser GuideGitHubNuGetDev CommunitySubmit a ticketLog In
GitHubNuGetDev CommunitySubmit a ticket

Event batching for the Go SDK

How the Optimizely Feature Experimentation Go SDK uses the event processor to batch impressions and conversion events into a single payload before sending it to Optimizely.

The Optimizely Feature Experimentation Go SDK batches decision and conversion events into a single payload before sending it to Optimizely. This is achieved through an SDK component called the event processor.

Event batching has the advantage of reducing the number of outbound requests to Optimizely Feature Experimentation depending on how you define, configure, and use the event processor. It means less network traffic for the same number of Impression and conversion events tracked.

In the Go SDK, QueueingEventProcessor provides implementation of the EventProcessor interface and batches events. You can control batching based on two parameters:

  • Batch size – Defines the number of events that are batched together before sending to Optimizely Feature Experimentation.
  • Flush interval – Defines the amount of time after which any batched events should be sent to Optimizely Feature Experimentation.

An event consisting of the batched payload is sent as soon as the batch size reaches the specified limit or flush interval reaches the specified time limit. Batchcessor options are described in more detail below.



Event batching works with both out-of-the-box and custom event dispatchers.

The event batching process does not remove any personally identifiable information (PII) from events. Ensure that you are not sending any unnecessary PII to Optimizely.

Basic example

import optly "" // for v2: ""

// the default client will have a BatchEventProcessor with the default options
optlyClient, err := optly.Client("SDK_KEY_HERE")

By default, batch size is 10 and flush interval is 30 seconds.

Advanced Example

To customize the event processor, you can use the client factory methods.

import (
  "" // for v2: ""
  ""  // for v2: ""
  ""  // for v2: ""

optimizelyFactory := &client.OptimizelyFactory{
		SDKKey: "SDK_KEY",	

// You can configure the batch size and flush interval
eventProcessor := event.NewBatchEventProcessor(
  event.WithFlushInterval(30 * time.Second),
optlyClient, err := optimizelyFactory.Client(



The maximum payload size is 3.5 MB. Optimizely rejects requests with a 400 response code, Bad Request Error, if the batch payload exceeds this limit.

The size limitation is because of the Optimizely Events API, which Feature Experimentation uses to send data to Optimizely.

The most common cause of a large payload size is a high batch size. If your payloads exceed the size limit, try configuring a smaller batch size.


BatchEventProcessor is an implementation of EventProcessor where events are batched. The class maintains a single consumer thread that pulls events off of an in-memory queue and buffers them for either a configured batch size or a maximum duration before the resulting LogEvent is sent to the EventDispatcher and NotificationCenter.

The following properties can be used to customize the BatchEventProcessor configuration.

PropertyDefault valueDescription
event.EventDispatcherNewQueueEventDispatcherUsed to dispatch event payload to Optimizely Feature Experimentation.
event.BatchSize10The maximum number of events to batch before dispatching. Once this number is reached, all queued events are flushed and sent to Optimizely Feature Experimentation.
event.FlushInterval30000 (30 Seconds)Milliseconds to wait before batching and dispatching events.
event.QNewInMemoryQueueBlockingCollection that queues individual events to be batched and dispatched by the executor.
event.MaxQueueSize1000The maximum number of events that can be queued.

For more information, see Initialize the Go SDK.

Side Effects

The table lists other Optimizely Feature Experimentation functionality that may be triggered by using this method.

LogEventWhenever the event processor produces a batch of events, a LogEvent object will be created using the event factory.

It contains batch of conversion and decision events.

This object will be dispatched using the provided event dispatcher and also it will be sent to the notification subscribers
Notification ListenersFlush invokes the LOGEVENT notification listener if this listener is subscribed to.

Register and Unregister a LogEvent listener

The example code below shows how to add and remove a LogEvent notification listener.

import (

  "" // for v2: ""
  ""  // for v2: ""

// Callback for log event notification
callback := func(notification event.LogEvent) {

  // URL to dispatch log event to
  // Batched event

optimizelyFactory := &client.OptimizelyFactory{
  SDKKey: "SDK_KEY",
optimizelyClient, err := optimizelyFactory.Client()
if err != nil {
	// handle error

// Add callback for logEvent notification
id, err := optimizelyClient.EventProcessor.(*event.BatchEventProcessor).OnEventDispatch(callback)
if err != nil {
	// handle error
// Remove callback for logEvent notification
err = optimizelyClient.EventProcessor.(*event.BatchEventProcessor).RemoveOnEventDispatch(id)


LogEvent object gets created using factory. It represents the batch of decision and conversion events we send to the Optimizely Feature Experimentation backend.

Required (non null)
StringURL to dispatch log event to.
event.BatchContains all the information regarding every event which is batched. Including list of visitors which contains UserEvent.

Close Optimizely Feature Experimentation on application exit

If you enable event batching, you must call the Close method (optimizelyClient.Close()) before exiting. This ensures that queued events are flushed as soon as possible to avoid data loss.


Because the Optimizely Feature Experimentation client maintains a buffer of queued events, you must call Close() on the Optimizely Feature Experimentation instance before shutting down your application or whenever dereferencing the instance.

Close()Stops all executor threads and flushes the event queue. This method will also stop any scheduledExecutorService that is running for the data-file manager.