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A webhook receiver can return 200 OK and still lose work, apply an old update over a new one, or perform the same business action twice. Treat the HTTP response as an acknowledgment—not proof that processing was correct. Verify each request, make side effects idempotent, handle events without assuming arrival order, and reconcile your local data against the source system.

What a successful webhook response does—and does not—prove

A successful response tells the sender that your endpoint replied according to its delivery rules. It does not prove that a background job completed, that an event was applied once, or that your system received every event. Those are separate reliability problems and need separate safeguards.

A robust receiver therefore has two jobs: accept a delivery safely within the provider’s deadline, and process it in a way that can withstand duplicates, delays, reordering, and recovery after an outage.

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Make duplicate deliveries safe

Providers may retry a delivery after a timeout, connection error, or unsuccessful response. Your system can also encounter duplicate work internally—for example, if a worker completes a side effect but crashes before recording completion. Design business effects to be idempotent: repeating the same event should not repeat a payment, create a second record, or send a second notification.

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Use the right identifier

Persist a delivery identifier and use it to prevent processing the same delivery more than once. The identifier is provider-specific. For GitHub, X-GitHub-Delivery identifies a delivery, and GitHub says a redelivery uses the same value. For Shopify, use X-Shopify-Webhook-Id to identify and deduplicate a delivery. Shopify notes that separate subscriptions for the same topic have distinct webhook IDs but can share an X-Shopify-Event-Id, which correlates deliveries from the same merchant action.

Keep delivery deduplication distinct from business-level idempotency. If the sender issues a new delivery ID for an event that represents an already-applied change, a delivery-ID check alone may not protect your business operation. Use a stable domain key or a state transition guard where appropriate.

Make the check and work durable

Do not rely on an in-memory set of IDs: it disappears on restart and cannot coordinate multiple server instances. Store the ID in durable storage, and make claiming it atomic so concurrent copies cannot both pass the check. A common pattern is to insert the ID under a unique constraint in the same transaction that records the accepted work. If the ID already exists, acknowledge the duplicate without repeating the effect. For effects that cannot share a database transaction, use an outbox or another durable workflow so a crash does not leave the event marked complete while its side effect was never performed.

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Shopify specifically recommends acknowledging a duplicate delivery as successful when skipping an already-seen X-Shopify-Webhook-Id. That prevents an unnecessary retry; it is Shopify guidance, not a universal response rule for every provider.

Verify authenticity before trusting payload data

Validate the provider’s signature before acting on the payload. For Shopify HTTPS deliveries, X-Shopify-Hmac-SHA256 contains a base64-encoded HMAC calculated with the app client secret and the raw request body. Capture the raw bytes before JSON parsing or other body transformations, compute the expected HMAC, and compare it using a constant-time comparison. Reject a request with a missing or invalid signature without allowing its contents to drive application behavior.

GitHub recommends HTTPS with SSL verification and a high-entropy webhook secret. Follow the verification scheme documented by the provider you actually use; header names, signed representations, and response requirements are not interchangeable.

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Accept quickly, process durably

Long-running work inside the HTTP request makes a timeout more likely. Where the provider permits asynchronous handling, validate the request, durably record or enqueue it, and acknowledge only after that durable acceptance succeeds. A background worker can then perform slower work, with retry and failure handling of its own. Returning success before the event is safely stored risks losing it if the process crashes; waiting for every downstream task risks missing the provider’s response deadline.

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Provider deadlines differ

Provider Documented response behavior Recovery detail
GitHub GitHub says the endpoint should return a 2XX response within 10 seconds; it terminates a slower connection and treats the delivery as failed. GitHub suggests asynchronous queue processing and recommends redelivering missed deliveries after a server outage.
Shopify Shopify documents a one-second connection timeout and five-second timeout for the full request. It expects 200 OK; responses outside the 200 range, including redirects, are errors. On no response or an error, Shopify retries 8 times over the next 4 hours. After 8 consecutive failures, a subscription configured through the Admin API is automatically deleted.

These are provider-specific limits documented in the GitHub webhook best practices and Shopify delivery verification pages, reviewed in 2026. Do not apply either provider’s deadlines, status-code rules, or retry behavior to another sender without checking its documentation.

Handle out-of-order events without trusting arrival order

Network delays, retries, and processing queues can make an older event arrive or finish after a newer one. If your handler blindly applies each payload in arrival order, stale data can overwrite current state.

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Shopify explicitly says it does not guarantee ordering within a topic or across topics for the same resource. It recommends organizing events using X-Shopify-Triggered-At or a payload’s updated_at timestamp. Compare timestamps against the state you have already applied, and reject an update that is older when that comparison is meaningful for your application. Timestamps are a useful signal, not a substitute for domain rules: account for equal timestamps, clock semantics, and events whose meaning is not a simple replacement of state.

For workflows where event order is critical or timestamps are insufficient, use the event as a signal to fetch the resource’s current state from the source system, then apply an update only if it advances your own state machine. Shopify’s documentation cautions: “As with other webhook systems, Shopify doesn’t guarantee ordering within a topic, or across different topics for the same resource.”

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Retries are not a missed-event recovery plan

A sender’s retry policy can help with temporary delivery failures, but it cannot guarantee that every change reaches your application. Shopify says delivery is not guaranteed and recommends periodic reconciliation through API queries to keep local data consistent. Its documentation also says, “Your app shouldn’t rely on receiving data from Shopify webhooks.”

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Build a reconciliation process appropriate to the data: periodically query the source system for records or updates changed since a durable checkpoint, compare them with local state, and repair missing or stale records. Use overlap or another safe checkpoint strategy so an interruption during a reconciliation run does not create a gap. Record what was checked and what was repaired so failures can be investigated. The exact API query and checkpoint design depend on the provider and resource.

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Test the failure paths, not just the 200 response

The following is a practical test matrix based on documented failure modes, not a standardized webhook test suite. Run it against the provider and delivery path you deploy, including the durable queue or database used in production.

Test What to simulate What to verify
Duplicate delivery Send the same delivery twice in sequence, then concurrently. The business effect occurs once, the duplicate is recognized durably, and the response follows the provider’s rules.
Signature verification Send a validly signed request, then alter its body or use an invalid signature. Verification uses the raw body; tampered or invalid requests are rejected before payload data is trusted.
Slow handling Delay a downstream operation until the request would exceed the provider’s deadline. Durable acceptance and background work are separated where appropriate, and acknowledgment latency remains within the provider’s documented limit.
Reverse order Deliver two updates for one resource in reverse chronological order. A stale update cannot overwrite newer state under the application’s timestamp or fetch-current-state policy.
Temporary failure and recovery Return a failure for a period, then restore service. The actual provider’s retry or redelivery behavior is understood, and processing remains idempotent when delivery resumes.
Outage beyond retries Keep the receiver unavailable beyond the provider’s retry window, then run reconciliation. Missing records or updates are detected and repaired even when delivery retries have ended.

Instrument the path from delivery to repair

Log and measure enough to trace an event end to end: provider delivery ID, event ID when available, signature result, acknowledgment latency, queue state, processing attempts, and reconciliation outcome. Alert on growing queue age, repeated processing failures, or reconciliation discrepancies. These are implementation recommendations; the cited provider documents do not prescribe a shared logging schema.

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Choose an ingress approach that matches the operational need

Building the receiver and queue yourself gives you control over persistence and processing, but also makes your team responsible for operational reliability, delivery visibility, replay, and fan-out to downstream services. Managed ingress or delivery infrastructure can provide some combination of verification, storage, filtering, transformation, retries, and fan-out; evaluate the specific service’s provider coverage, recovery controls, operational fit, and verified cost and terms. GitHub names Hookdeck as one example for asynchronous queueing, while Svix describes an ingress service with these capabilities. These descriptions are not a comparative performance assessment or a recommendation.

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