API integrations between platforms

How to connect your systems reliably, scalably and maintainably

10 min

Modern businesses operate with dozens of platforms: CRM, ERP, ecommerce, marketing tools, logistics systems, payment gateways. The real value isn’t in each isolated tool, but in how they communicate with each other. API integrations are the connective tissue of any digital ecosystem.

However, integrating platforms is far more than connecting two endpoints. It requires a clear strategy for architecture, error handling, monitoring and evolution. This guide covers the patterns and practices that separate a solid integration from a ticking time bomb.

Integration types: REST, webhooks and events

The integration type defines how information flows between systems. REST APIs are the standard for on-demand queries: one system requests data and the other responds. Webhooks reverse the direction: the source system sends an automatic notification when a relevant event occurs.

Event-driven architectures take this further with message queues (RabbitMQ, Kafka, AWS SQS) that decouple sender and receiver. Each pattern has its place depending on volume, latency and the criticality of the integration.

  • REST API: ideal for synchronous queries and CRUD, widely supported
  • Webhooks: perfect for reacting to real-time events (new order, payment confirmed)
  • Event-driven: suited for high volume, asynchronous processing and full decoupling
  • GraphQL: useful when the consumer needs to control exactly which data it receives

Middleware and iPaaS: when to use an integration layer

When connecting more than 3–4 systems, point-to-point integrations become an unmaintainable tangle. A middleware or iPaaS (Integration Platform as a Service) acts as a central hub that orchestrates data flows, transforms formats and manages retries.

Tools like MuleSoft, Workato, Make (formerly Integromat) or n8n offer pre-configured connectors and visual workflows. The decision between an iPaaS and custom middleware depends on volume, transformation complexity and the need for control over business logic.

  • iPaaS (Workato, Make, Tray.io): quick to set up, ideal for standard SaaS-to-SaaS integrations
  • Custom middleware (Node.js, Python): full control, better for complex logic or high volume
  • API Gateway (Kong, AWS API Gateway): centralised security, rate limiting and versioning layer

Design principles for integration APIs

A well-designed API is predictable, versioned and documented. Use clear naming conventions, standard HTTP codes and consistent pagination. Documentation (OpenAPI/Swagger) isn’t an extra — it’s a requirement for other teams and systems to consume your API without friction.

  • Explicit versioning (v1, v2) to evolve without breaking existing integrations
  • Robust authentication: OAuth 2.0 or API keys with periodic rotation
  • Rate limiting to protect the system from accidental or malicious overload
  • Idempotency in write operations to prevent duplicates during retries
  • Consistent responses with appropriate HTTP codes and descriptive error messages

Error handling and retries

In integrations, errors are inevitable: network timeouts, services down, malformed data, rate limits exceeded. The difference between a robust integration and a fragile one is how it handles those errors.

Implement retries with exponential backoff, dead-letter queues for messages that fail repeatedly, and automatic alerts when the error rate exceeds a threshold. Every failed transaction should be logged with enough context to diagnose and resolve the problem.

  • Retries with exponential backoff (1s, 2s, 4s, 8s…) and a maximum limit
  • Dead-letter queues for messages that exhaust retries without success
  • Circuit breaker pattern to avoid overwhelming a service that’s already down
  • Structured logging with correlation IDs to trace a transaction across systems

Monitoring and observability

An integration without monitoring is a broken integration you just don’t know about yet. You need visibility into latency, error rates, processed message volume and queue status. Tools like Datadog, Grafana or even simple CloudWatch dashboards can make the difference between detecting a problem in 5 minutes versus 5 days.

Define clear SLAs for each integration: maximum processing time, minimum success rate, maximum recovery time. Set up proactive alerts — don’t wait for a user to report that something isn’t working.

Evolution and maintenance strategy

Third-party APIs change, data formats evolve and volumes grow. A mature integration strategy includes versioning plans, automated contract testing (with Pact or similar tools) and up-to-date documentation.

Periodically review the health of your integrations: are there deprecated APIs that need migration? Have a provider’s terms of service changed? Does current volume exceed the original design’s capacity? Technical debt in integrations is especially costly because it affects multiple systems simultaneously.

Key Takeaways

  • Choose the integration pattern (REST, webhooks, events) based on the use case, not trends
  • Use middleware or iPaaS when connecting 3+ systems to avoid point-to-point spaghetti
  • Design versioned, documented and idempotent APIs from the start
  • Implement retries, circuit breakers and dead-letter queues to handle inevitable errors
  • Monitor latency, error rates and volume with proactive alerting

Need to integrate your platforms?

We design and implement robust integrations between your systems, with monitoring and ongoing support. Tell us about your case.