What Is a Webhook? The Difference Between APIs and Webhooks

A webhook automatically sends an HTTP notification to another system when an event occurs, for example a completed payment or new order.

Compared with repeatedly polling an API for changes, this model can be faster and more resource-efficient.

How does a webhook work?

The receiver provides a callback URL. The source sends event data to it when the event occurs.

Difference from API polling

With polling, clients ask at intervals whether anything changed. With webhooks, the source system notifies the client when a change occurs.

Webhook Payload

Payloads can contain event type, resource ID, timestamp and related data. Another common approach sends only the resource ID and retrieves details through an API.

Signature verification

Because a webhook endpoint is internet-accessible, verify that requests really come from the expected provider. HMAC signatures are a common method.

Retry mechanism

If the receiver is temporarily unavailable, the source can resend the webhook. Document the retry count and backoff strategy.

Duplicate events

The same webhook can come more than once. Duplicate processing must be prevented using Event ID or business key.

Using queues

An endpoint can validate the payload and enqueue it instead of performing heavy work during the request. This allows a quick acknowledgement.

Webhook Monitoring

Number of failed events
Retry count
Processing latency
Duplicate event
Signature verification failure
Queue backlog

Production integration checklist

In production, webhook operation, API polling differences and webhook payloads belong to the operating model, not just development. Define the source and destination systems, data owner, authentication method, mapping table and person responsible for failures for each integration. A working endpoint is not a successful integration if it updates the wrong product, customer or order.

Treat timeouts, rate limits, temporary network outages, duplicate requests and unexpected responses as normal production scenarios. Retry only temporary failures, and use idempotency where repeating an operation could have financial or operational side effects. Moving long-running work to a queue decouples the user request from external service performance; failed jobs can then be reprocessed in a controlled way.

Monitor business outcomes as well as HTTP status codes. An API may return HTTP 200 even though no orders reach the ERP. Show request count, error rate, P95 latency, retry count, queue backlog and last successful synchronisation alongside business metrics such as orders, stock or customer records transferred. Correlation IDs and structured logging help trace one operation across services during an incident.

Authentication and secret management
Data mapping and schema validation
Timeout and retry policy
Idempotency and duplicate detection
Request rate-limit management
Structured logs and correlation IDs
Business data reconciliation
Alert and dashboard

API Contract, Failure Mode, and Data Consistency

Do not design only the successful request-response path. Define a clear API contract covering webhook operation, API polling differences and webhook payloads, including required fields, data types, enum values, authentication, timeouts, error codes and handling of breaking changes. Decide in advance which responses trigger retries, which stop processing and which require human intervention to make integration behaviour more predictable.

Failure-mode design must cover not only total external service outages but also slow responses, partial data, duplicate or out-of-order events, rate limits and temporary authentication failures. Retries can use exponential backoff and, where appropriate, jitter. Idempotency or unique business keys reduce duplicate-record risk when orders, payments, inventory or customer operations are processed again.

A successful API response alone does not establish data consistency. Periodically reconcile source and destination systems by record count, total amount, last synchronisation time or business ID to detect discrepancies. Structured logs, correlation IDs and central error tracking can identify the failing service faster. These checks turn a working connection into an auditable, sustainable operational component.

Request and response schema validation
Timeout and retry matrix
Idempotency or unique business keys
Request rate limits and capacity management
Correlation IDs and structured logging
Source-to-destination reconciliation checks
Breaking-change and versioning policy

B10 Digital Agency’s integration approach

B10 Digital Agency treats integration as system architecture, not just an API connection: data contracts, security, retries, queues, observability, reconciliation and operational processes are designed together.

Frequently Asked Questions

Is Webhook real-time?

Delivery is usually close to the event, but network delays and retries may prevent an absolute real-time guarantee.

Do you need an API for Webhook?

Not always. In many architectures, an API is used alongside webhooks to retrieve details after an event.

How to Make Webhook Safe?

Use TLS, signature verification, timestamp checks and appropriate authorisation.

Can Webhook come twice?

Yes. The consuming system must therefore be designed for idempotent processing.

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