Synchronous APIs
Request-response protocols provide an immediate result. They fit flows that require a timely response, and need timeouts, contract validation, authentication and clear handling of partial responses or unavailability.
Companies rarely operate on a single application. Management, support, inventory, billing and digital platforms use different models and rhythms. Integration requires data contracts, ownership, transformation rules and defined behavior when a dependency fails.
Reliable integration considers latency, synchronization frequency, source limits, authentication, versioning and traceability. A synchronous call is appropriate in some scenarios; events, queues or batch processing suit others. Operational requirements should guide the choice.
Explore the approachActivities, depth and support are defined by the agreed scope and the conditions of the environment.
An order created in a sales channel may reserve inventory in an ERP and update delivery status elsewhere. Each step depends on identifiers, business rules and separate systems. If a call fails between reservation and confirmation, blindly retrying can create duplicates; ignoring it can leave records inconsistent.
The flow must address consistency, retries and exceptions: detect duplicate messages, define retry conditions, record persistent failures and reconcile temporarily divergent records. This is a conceptual example rather than a client implementation.
Invalid contract → intervention required. Reason recorded for review.
Transient failure → retry with backoff. Reprocess without duplicating effects.
Request-response protocols provide an immediate result. They fit flows that require a timely response, and need timeouts, contract validation, authentication and clear handling of partial responses or unavailability.
Messages decouple producers and consumers running at different speeds. They suit deferred or distributed work, but require care with duplicates, ordering, retention, consumer failures and processing observability.
ETL/ELT, file imports and scheduled jobs can serve data without low-latency requirements. They still need file versioning, incremental processing, reconciliation and safe repeated execution.
An intermediary can centralize protocol adaptation, transformations, security and orchestration. It also needs monitoring, capacity planning and governance; excessive centralization can create new coupling.
| Pattern | Best fit | Main trade-off |
|---|---|---|
| Synchronous API | The current flow needs a response | Coupling to availability and response time |
| Events and queues | Independent or deferred work | Duplicates, ordering and eventual consistency |
| Batches / files | A controlled delay is acceptable | Refresh windows and reconciliation |
| Middleware | Shared transformations | Operating and governing the central layer |
A reference path adapted to each project.
A reference path adapted to each project.
Identify systems, owners, rules, documentation, authentication, API restrictions and required fields. Establish the source of truth for customers, products, orders, payments and events.
Specify schemas, identifier mapping, validation, transformations, versioning and incompatible-change policy. Fields with the same name can have different meanings across systems.
Choose synchronous, asynchronous or hybrid processing. Define idempotency, backoff, timeouts, dead-letter queues where appropriate and reconciliation according to criticality and delay tolerance.
Separate credentials and endpoints by environment. Test realistic boundary and error cases, contracts, authorization, duplicates and unavailable dependencies.
Record correlation identifiers, relevant events, success rates, latency and pending queues. Dashboards do not replace retry mechanisms and exception handling.
Follow supplier and contract changes, review consumption, document ownership and plan for field changes, new API versions and endpoint retirement.
Executions must be traceable without exposing sensitive data in logs. Correlation identifiers connect origin, intermediate processing and destination effects. Useful metrics include received volume, successes, failure categories, processing time, oldest-message age and items needing human attention.
An operational guide explains how to identify failures, when to retry, who validates differences and what to do when an external API changes its contract. Without these definitions, simple automation can become difficult to maintain.
Automating an inconsistent process reproduces its exceptions at a larger scale. Define triggers, decision rules, stopping conditions and human approval cases before choosing APIs, messaging, files or interface automation when a suitable technical interface is unavailable.
APIs define contracts for exchanging information or executing operations between applications. Integration also requires authentication, formats, versioning, limits, error handling and availability planning.
Integrations may connect ERPs, CRMs, BI tools, sales platforms and custom applications with viable communication mechanisms. Design depends on available interfaces, permissions and supplier rules.
An event or condition starts actions governed by explicit rules. The project includes validation, exceptions, auditability and owners for cases that cannot be resolved automatically.
Intermediary components mediate communication, transformations, protocols and policies. They can reduce point-to-point connections but need their own governance and operations.
Maintenance may cover observability, failures, contract adjustments, connector updates and performance within the agreed scope. External dependencies require tracking supplier changes.