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Walter Fernández
Walter Fernández

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Building Reliable Distributed Systems with AWS Serverless

Diagram

Full resolution diagram: Microservices Diagram

Introduction

Most microservices architectures share similar trade-offs. Two of the most common challenges are transactional consistency and keeping services synchronized with data changes. As a result, distributed systems often deal with duplicate events, lost messages, and partial failures.

This is where idempotency becomes essential. In simple terms, idempotency means an operation can be executed multiple times without changing the final result. That property makes it especially valuable in transactional domains like retail, finance, or travel.

Another key piece of the puzzle is the Outbox Pattern. Instead of notifying external systems directly—which risks message loss if the network or broker fails—the service persists both the data change and the event message in a single atomic transaction. This guarantees reliable event delivery.

In this demo, we’ll explore a retail scenario that combines idempotency, the Outbox Pattern, and a simplified saga orchestration using AWS Step Functions.

Here’s the high-level flow:

  • 1. Entry Point: An HTTP POST request hits API Gateway, triggering the Order Lambda.
  • 2. Data Integrity: The Lambda checks an Idempotency Table and performs a TransactWrite across the Orders and Outbox tables.
  • 3. Event Trigger: A DynamoDB Stream detects the new Outbox record and invokes the Outbox Processor.
  • 4. Workflow Execution: The processor starts a Step Functions workflow:
    • Inventory & Payment: Attempts to reserve stock and process payment.
    • Success Path: Sends a notification when everything succeeds.
    • Failure Path: Executes a compensation step to release inventory if payment fails.

This combination provides important benefits:

  • Avoid duplication: Returns the original response for repeated requests with the same identifier.
  • Performance optimization: Skips expensive logic for already processed requests.
  • Deterministic behavior: The same input always leads to the same final state.
  • Consistency: Helps services converge to the same state despite communication failures. ## Idempotency Pattern

There are two main ways to implement idempotency in distributed systems: building a custom solution or leveraging a managed library. For this demo, we’ll use AWS Powertools for TypeScript, which provides built-in idempotency utilities for Lambda functions.

The library stores request state in Amazon DynamoDB, tracking whether a request is in progress or completed. This allows safe retries and ensures duplicate invocations return cached responses instead of re-executing business logic.

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Outbox Pattern

The Outbox implementation relies on DynamoDB TransactWrite operations across the Orders and Outbox tables, combined with DynamoDB Streams. Whenever a new Outbox record appears, a Lambda function is triggered to start the Step Functions workflow, enabling reliable event propagation without tight coupling.

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Step function

The Step Functions workflow orchestrates the full order lifecycle. It handles both successful execution and failure scenarios by triggering compensation logic when needed. For demonstration purposes, some steps are mocked or simplified.

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Testing

End-to-End Test with cURL

To validate the full integration, deploy the stack and submit a sample order. This request triggers the complete execution chain, including idempotency validation, the Outbox event, and the Step Functions workflow.

The screenshot below shows a successful order request triggered from Postman.

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Expected Behavior

  • First request: The workflow executes normally, and the order status is updated upon completion.
  • Subsequent requests: When the same request is retried with the same idempotency key, the system skips execution and returns the cached response stored in the Idempotency Table.

This guarantees safe retries without duplicating side effects.

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X-Ray

Tracing is essential in distributed systems. With AWS X-Ray enabled, we can visualize how a request travels across API Gateway, Lambda, DynamoDB Streams, and Step Functions.

The following trace illustrates the full request lifecycle.

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  • The Order Lambda handles idempotency and performs the atomic write.
  • The DynamoDB Stream triggers the Outbox Processor.
  • The Step Functions workflow orchestrates inventory and payment operations.

This level of visibility makes debugging faster and helps identify bottlenecks in event-driven architectures.

Workflow Orchestration

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The Step Functions graph clearly illustrates the workflow execution. In this demo, all steps completed successfully:

  • ReserveInventory – Validates and holds product stock
  • ProcessPayment – Executes the payment transaction
  • SendNotification – Sends the order confirmation

The CompensateInventory branch acts as a safety net. If payment fails, the workflow automatically releases the reserved stock, ensuring system consistency without manual intervention.

Production Readiness

While this demo highlights core patterns, production environments require additional safeguards. A resilient serverless architecture should focus on:

  • Observability: Enable X-Ray tracing and CloudWatch alarms to detect failures early
  • Retries & DLQs: Configure exponential backoff and Dead Letter Queues for exhausted events
  • Cost Optimization: Use Step Functions Express for high-volume, short-lived workflows
  • Lifecycle Management: Apply DynamoDB TTL on idempotency records to automatically purge stale data

Final Thoughts

Distributed systems introduce unavoidable complexity, but patterns like Idempotency, Outbox, and Step function Orchestration help transform fragile event-driven flows into robust architectures.

Together, they ensure:

  • Safe retries without duplicate side effects
  • Reliable event delivery across services
  • Automatic recovery through compensation logic

By combining these patterns with strong observability and operational safeguards, you can build serverless systems that remain consistent—even when individual components fail.

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