Amazon EventBridge is a serverless event bus that routes events between AWS services, SaaS applications, and your own code. In AI pipelines it acts as the connective tissue between loosely coupled steps - decoupling event producers (S3 uploads, API calls, scheduled jobs) from event consumers (Lambda functions, Step Functions workflows, SQS queues).

Official documentation: https://aws.amazon.com/eventbridge/ Pricing: https://aws.amazon.com/eventbridge/pricing/ Service quotas: https://docs.aws.amazon.com/eventbridge/latest/userguide/eb-quota.html

Azure equivalent: Azure Event Grid. GCP equivalent: Google Eventarc.

How EventBridge Works

EventBridge receives events (JSON objects describing something that happened) and evaluates them against rules. A rule matches events using a pattern and forwards matching events to one or more targets. Targets include Lambda, Step Functions, SQS, SNS, and many more.

The default event bus carries events from AWS services automatically - S3, Rekognition, CodePipeline, and 200+ others publish here without configuration. You can also create custom event buses to separate concerns (e.g., one bus per application domain).

EventBridge Pipes provide point-to-point connections between a source (SQS, DynamoDB Streams, Kinesis) and a target, with optional filtering and transformation in between. Useful for event enrichment before triggering downstream processing.

EventBridge Scheduler replaces CloudWatch Events for cron-based triggers. It supports one-time and recurring schedules with timezone awareness, and is more reliable than cron-on-Lambda for precise scheduling.

AI Pipeline Patterns

S3 to processing pipeline: When a video file lands in S3, an EventBridge rule matches the ObjectCreated event and starts a Step Functions execution. The rule pattern filters by prefix (raw/) and file extension (.mp4) so only relevant uploads trigger processing.

Async AI job completion: Rekognition video analysis is asynchronous. When a label detection job finishes, Rekognition publishes a completion event to SNS, which you forward to EventBridge. A rule matches the completion and triggers the next pipeline stage.

Scheduled batch processing: Run nightly summarization, embedding refresh, or cost reporting jobs using EventBridge Scheduler instead of managing cron infrastructure.

Cross-service fan-out: A single S3 upload can trigger multiple independent processes simultaneously - metadata extraction, virus scanning, thumbnail generation - by routing the same event to multiple Lambda targets. Each process runs independently without coupling.

Rule Patterns

EventBridge rule patterns use JSON matching. A pattern like this matches only MP4 uploads to the raw/ prefix in a specific bucket:

{
  "source": ["aws.s3"],
  "detail-type": ["Object Created"],
  "detail": {
    "bucket": { "name": ["my-ai-pipeline-bucket"] },
    "object": { "key": [{ "prefix": "raw/" }] }
  }
}

Content filtering at the rule level means Lambda functions are invoked only for relevant events, reducing cost and complexity.

Cross-Cloud Comparison

Azure Event Grid uses topics and subscriptions with a similar pattern-matching model. GCP Eventarc routes events from Cloud Storage, Pub/Sub, and Audit Logs to Cloud Run or Cloud Functions. EventBridge has the most extensive native AWS service integration of the three.