Synchronous API to SNS/SQS Fan-Out Blueprint

What and Why

Synchronous APIs that do heavy work inline (sending emails, generating reports, calling slow third parties) hold the caller waiting and fail under load spikes. Amazon SNS and SQS let you accept the request fast, publish an event, and process it asynchronously with durable buffering and built-in retries. SNS fan-out delivers one event to many SQS queues so several consumers react independently.

This blueprint offloads slow or spiky work from synchronous handlers to an SNS/SQS pipeline.

Phases

Assessment. Find synchronous endpoints whose latency or failure rate is driven by downstream work. Separate operations that must be synchronous from those that can return an accepted-status immediately.

Topic design. Define SNS topics per domain event and SQS queues per consumer. Plan message schemas (CloudEvents/JSON), partitioning needs (FIFO vs standard), and dead-letter queues. Choose FIFO where strict ordering and exactly-once-ish semantics matter, standard for max throughput.

Async offload. Change the API to validate, persist, publish to SNS, and return 202 Accepted. SNS fans out to subscribing SQS queues.

Consumer migration. Implement consumers (Lambda or services) that pull from SQS, process idempotently, and handle retries. Move flows over one at a time.

Hardening. Configure visibility timeouts, max-receive counts, dead-letter queues, and redrive. Add alarms on queue depth and DLQ size.

Key Risks and Mitigations

• Duplicate delivery: standard SQS is at-least-once. Make consumers idempotent with idempotency keys and dedupe tables; use FIFO with content dedup where needed.
• Poison messages: a malformed message can loop forever. Set max-receive and a dead-letter queue, and alert on DLQ growth.
• Data consistency: publishing after a DB commit can drop events on crash. Use the transactional outbox or persist-then-publish with retries.

Recommended Tooling

SNS for fan-out, SQS (standard and FIFO) for buffering, Lambda or container consumers, dead-letter queues with redrive, and CloudWatch alarms on queue depth and age. Validate schemas before publishing.

Success Metrics

Measure synchronous request latency drop after offloading, sustained throughput under spikes, error rate, and queue age staying within SLA.

Prerequisites

An AWS account with IAM for SNS/SQS, idempotency strategy in consumers, and clear rules on which operations may become asynchronous.