System integration is the work of making independently evolving software cooperate without pretending that networks are reliable or that every system shares the same model of the world.
The technology matters, but the first design question is simpler: does the caller need an answer now, or can the work happen later?
APIs for immediate interaction
A synchronous API is appropriate when a consumer needs a response to continue—for example, retrieving an account or validating an operation. The contract should define inputs, outputs, authentication, authorization, errors, timeouts, and compatibility expectations.
Every synchronous dependency adds latency and availability coupling. Use explicit timeouts, bounded retries, and circuit-breaking or load-shedding where appropriate. Retrying a state-changing request is safe only when the operation is idempotent or carries an idempotency key.
Webhooks for outbound notification
A webhook allows one system to notify another through an HTTP callback. It is useful for partner integrations and event notifications when the receiver can expose a reachable endpoint.
Production webhooks need signed payloads, timestamp validation, retries with backoff, stable event identifiers, delivery history, and a recovery mechanism. A successful HTTP response confirms receipt according to the agreed contract; it does not necessarily mean the receiver completed all downstream business work.
Queues for asynchronous work
A queue separates the producer’s request path from work that can happen later. It can absorb bursts and allow consumers to process at a sustainable rate. Common examples include sending email, generating reports, or processing background jobs.
Consumers must handle duplicate delivery and define what happens after repeated failure. Monitor queue depth, oldest-message age, processing time, and dead-letter volume. A queue should reduce temporal coupling, not become a place where failures disappear.
Events for shared facts
An event states that something happened: order.placed, payment.authorized, or customer.address.changed. Multiple consumers can react independently, which reduces direct coupling between producer and consumer implementations.
Good events represent stable business facts, include a unique identifier and occurrence time, and use a versioned schema. They should carry enough context for consumers without exposing unnecessary personal or internal data.
Events introduce their own complexity: eventual consistency, duplicates, out-of-order delivery, schema evolution, replay, and operational ownership. Use them when those trade-offs solve a real coupling or scale problem—not because event-driven architecture sounds modern.
Combine patterns deliberately
Real systems often use several patterns together. An API accepts a command, commits a transaction, and publishes an event. A queue schedules slow processing. A webhook notifies an external partner. The boundaries should remain explicit.
One critical challenge is publishing an event consistently with a database change. Patterns such as a transactional outbox can prevent a successful database commit from being followed by a lost event. Consumers still need idempotency and observable processing.
Define ownership and evidence
Every integration needs an owner, a contract, service objectives, security controls, and a deprecation process. Track requests or events with correlation identifiers, but never place secrets or unnecessary personal data in telemetry.
Choose the simplest pattern that satisfies the required delivery contract. APIs optimize for immediate answers. Webhooks notify remote subscribers. Queues decouple work over time. Events distribute facts to independent consumers.
The goal is not to remove every dependency. It is to make each dependency understandable, observable, and resilient when one part of the system inevitably fails.
Reference
AWS Prescriptive Guidance documents the transactional outbox pattern for coordinating database changes and event publication.