AWS Lambda triggers and event sources are fundamental concepts for building serverless applications. A trigger is a resource or configuration that invokes a Lambda function, while an event source is the AWS service or custom application that generates events causing the function to execute.
Event …AWS Lambda triggers and event sources are fundamental concepts for building serverless applications. A trigger is a resource or configuration that invokes a Lambda function, while an event source is the AWS service or custom application that generates events causing the function to execute.
Event sources fall into two categories: push-based and pull-based. Push-based sources like API Gateway, S3, SNS, and CloudWatch Events invoke Lambda functions by sending events to the Lambda service. The source service pushes the event data, and Lambda handles the invocation. Pull-based sources include Amazon Kinesis, DynamoDB Streams, and SQS, where Lambda polls these services for new records and processes them in batches.
Common Lambda triggers include:
1. **Amazon S3**: Triggers functions when objects are created, modified, or deleted in buckets.
2. **API Gateway**: Enables HTTP endpoints that invoke Lambda functions for REST or WebSocket APIs.
3. **DynamoDB Streams**: Processes table changes in real-time for data synchronization or analytics.
4. **SNS/SQS**: Handles message processing from notification and queue services.
5. **CloudWatch Events/EventBridge**: Schedules functions or responds to AWS resource state changes.
6. **Kinesis**: Processes streaming data for real-time analytics.
When configuring triggers, developers must consider permissions through IAM roles. Lambda needs appropriate execution roles to read from event sources and perform actions. For push-based sources, resource-based policies grant the source permission to invoke the function.
Event source mappings connect poll-based sources to Lambda, configuring batch sizes, starting positions, and error handling. Understanding concurrency is essential as each event can spawn function instances up to account limits.
For the Developer Associate exam, focus on identifying appropriate triggers for use cases, understanding synchronous versus asynchronous invocations, and configuring proper IAM permissions for seamless integration between Lambda and other AWS services.
Lambda Triggers and Event Sources - Complete Guide
Why Lambda Triggers and Event Sources Are Important
Lambda triggers and event sources are fundamental to building serverless, event-driven architectures on AWS. Understanding them is crucial for the AWS Developer Associate exam because they determine how and when your Lambda functions execute. Mastering this topic enables you to design scalable, decoupled applications that respond automatically to events across the AWS ecosystem.
What Are Lambda Triggers and Event Sources?
A trigger is a resource or configuration that invokes a Lambda function when a specific event occurs. An event source is the AWS service or custom application that generates these events.
There are two primary invocation models:
1. Push Model (Event Source Mapping Not Required) - The event source invokes Lambda by calling the Invoke API - Examples: API Gateway, S3, SNS, Cognito, CloudWatch Events, Alexa Skills - Permissions are configured on the Lambda function's resource-based policy
2. Pull Model (Event Source Mapping Required) - Lambda polls the event source for new records - Examples: SQS, DynamoDB Streams, Kinesis Data Streams, Amazon MSK, DocumentDB - Lambda uses an execution role with permissions to read from the source
How Lambda Triggers Work
Push-Based Triggers: - S3 bucket notifications trigger Lambda when objects are created, deleted, or modified - API Gateway forwards HTTP requests to Lambda for processing - SNS delivers messages to Lambda as a subscriber - CloudWatch Events/EventBridge invokes Lambda on schedule or in response to AWS events
Poll-Based Triggers (Event Source Mappings): - Lambda service polls the stream or queue - Batches records together based on batch size and batching window settings - Invokes your function with the batch of records - For streams (Kinesis, DynamoDB), Lambda processes records in order per shard - For SQS, Lambda scales automatically based on queue depth
Key Configuration Options
- Batch Size: Number of records to send per invocation (varies by source) - Batch Window: Maximum time to gather records before invoking - Concurrency: Number of simultaneous executions - Retry Behavior: Differs between synchronous and asynchronous invocations - Dead Letter Queues (DLQ): Capture failed events for later analysis - Destination Configuration: Route successful or failed async invocations to SNS, SQS, Lambda, or EventBridge
Exam Tips: Answering Questions on Lambda Triggers and Event Sources
1. Know the invocation model: If the question mentions Kinesis, DynamoDB Streams, or SQS, remember these use poll-based event source mappings. S3, SNS, and API Gateway use push-based invocation.
2. Understand permission requirements: Push sources need resource-based policies on Lambda. Poll sources need execution role permissions to access the source.
3. Remember ordering guarantees: Kinesis and DynamoDB Streams maintain order per shard. SQS Standard queues do not guarantee order; use FIFO for ordering.
4. Know batch processing behaviors: For streams, a failed record blocks the shard until resolved or the record expires. Configure error handling with bisect batch, maximum retry attempts, and destination on failure.
5. Scaling differences matter: SQS scales up to 1,000 concurrent executions. Kinesis scales with the number of shards. DynamoDB Streams also scale with shards.
6. S3 event specifics: S3 events are asynchronous. Enable versioning to capture all modifications. Events may be delivered at least once.
7. API Gateway integration types: Know the difference between Lambda proxy integration (passes full request) and Lambda custom integration (transforms request/response).
8. DLQ vs Destinations: DLQs work for asynchronous invocations and event source mappings. Destinations provide more flexibility and metadata about failures.
9. Reserved concurrency: Setting reserved concurrency to zero effectively disables the function. Use this for throttling or maintenance scenarios.
10. Watch for keywords: Questions mentioning real-time processing often point to Kinesis. Questions about decoupling typically involve SQS or SNS. Questions about scheduled tasks point to EventBridge rules.