Integrations

Fundamentally, an integration is simply the exchange of data between two systems. For example, an e-commerce store sends an order to an ERP, inventory balances update back, a payment gateway confirms a transaction, or customer data syncs to a CRM. Whether it is a real-time API call, a scheduled synchronization, or an event-driven message, the principle remains the same: data moves between systems so the process does not require manual intervention.

When multiple integrations are involved, they are no longer isolated connections but part of a production chain. In this context, semantic consistency becomes paramount: data must mean the same thing at both ends. Questions regarding the Single Source of Truth, data finality, identifier generation, and conflict resolution during downtime must be answered. Most integration failures are not due to connectivity issues, but rather undefined meanings, responsibilities, and exception handling.

Off-the-shelf integration tools are useful when the chain is short and exceptions are rare. However, as the ecosystem grows, the same limitations arise: changes at one end break the other, error states remain ambiguous, and minor discrepancies accumulate, requiring manual reconciliation. Typical symptoms include duplicate customer records, state drift between orders and payments, inventory latency, and scenarios where an action succeeds in one system but fails in another.

This is why integrations should be engineered as system components, not merely as "automations." Data interpretation and transformation are executed in a controlled manner, exceptions are anticipated, and the overall state remains observable. When an API changes, the impact is contained rather than propagating through the entire chain. When a failure occurs, the root cause is visible, and the process can be recovered without resorting to guesswork.

In practice, this allows the system to be modified and extended without every change causing a regression. Dependencies can be swapped in a controlled manner, data remains auditable, and error states do not cascade into customer service tickets or manual labor. An integration is then no longer a set of loose connections, but a cohesive part of a production-grade environment.