In this lab, you’ll build a sophisticated event-driven architecture on AWS using SNS, SQS, and Lambda, and extend it with S3 triggers, API Gateway endpoints, and CloudWatch monitoring. You’ll design message patterns, configure dead-letter queues (DLQs), handle FIFO ordering, implement batch processing, and set up monitoring and cost optimization strategies. You’ll also explore operational procedures and build a basic testing framework for validation.
This lab guides you through the steps of architecting, implementing, and optimizing an asynchronous event-driven workflow that is scalable, fault-tolerant, and observable.
This workshop assumes you already have basic familiarity with AWS services like IAM, Lambda, and S3. You’ll also benefit from knowledge of JSON message formats, retry policies, and async patterns.
SNS is a managed pub/sub messaging service that enables message fan-out to multiple subscribers. It helps route messages to multiple destinations like Lambda, SQS, and HTTP endpoints.
SQS is a fully managed message queuing service that enables decoupling of microservices. It supports standard queues (at-least-once delivery, best-effort ordering) and FIFO queues (exactly-once processing, strict ordering).
AWS Lambda is a serverless compute service that runs your backend code in response to triggers such as SQS messages, S3 events, and API Gateway HTTP calls. It scales automatically and supports concurrency settings and DLQ handling for robust message processing.
Amazon S3 is a storage service for objects like JSON files, images, and logs. You can trigger Lambda functions when a new file is uploaded to an S3 bucket, making it ideal for ingesting event data like user submissions or batch inputs.
API Gateway allows you to expose HTTPS endpoints to trigger AWS services. It integrates directly with Lambda to receive incoming requests (e.g., a quiz submission), which can then be routed via SNS or processed directly.
CloudWatch is the monitoring, logging, and alerting backbone of AWS. You’ll use it to:
A DLQ is a standard SQS queue used to capture failed messages after exceeding retry attempts. DLQs are critical for troubleshooting failures and maintaining resilience.
We’ll use CloudWatch Metrics, Logs, and Alarms to track system behavior. You’ll also use AWS Cost Explorer, CloudWatch Logs Insights, and Lambda cost calculators to optimize expenses.