How Temporal Makes Webhook Workflows Durable and Automatically Retried

Temporal changed what is possible in distributed systems. That sentence is not marketing — it is a reasonable assessment from engineers who have operated large-scale event processing at companies where partial failures used to mean manual recovery scripts at 2 AM. The core idea is profound and simple to state: make function execution durable. Record what happened. If the process crashes, replay it from the recorded history. Your application code does not need to know that any of this is happening.

For webhook processing specifically, this means your handler can survive crashes, worker restarts, arbitrary delays, and downstream timeouts — and the execution will continue exactly where it left off. No manual intervention. No lost state. No duplicated side effects.

This is not a small improvement over the alternatives. It is a different architectural category.

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What Durable Execution Actually Means

Temporal's durable execution model is the most carefully engineered solution to processing reliability in the open-source ecosystem — but the term gets thrown around loosely and deserves a precise description. The Temporal documentation covers the execution model in full, and Temporal on GitHub shows the active engineering investment behind the project.

When a Temporal workflow starts, every step it takes is recorded to a persistent event history. The workflow itself runs as a sequence of activities — discrete units of work, each with their own retry policy. If the worker process crashes mid-workflow, Temporal replays the event history on another worker. Activities that already completed are not re-executed — their recorded results are used. Only the in-progress activity is retried.

This deterministic replay guarantee has a constraint: workflow code must be deterministic. The same input, at any replay, must produce the same sequence of activity calls. You cannot use Math.random() inside a workflow, or call Date.now() directly. These constraints are real and require architectural discipline.

The payoff is that your workflow is effectively a long-lived, fault-tolerant process that can span seconds, minutes, or days — with no external coordination required to resume after failure.

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Temporal for Webhook Handlers

The natural way to use Temporal for webhook processing: your HTTP endpoint receives the payload, then starts a Temporal workflow and returns 200 immediately. The workflow does the actual work — parsing, validation, database writes, downstream API calls — as a series of activities.

// Your webhook endpoint (Next.js API route, Express, etc.)
export async function POST(req: Request) {
  const payload = await req.json();

  // Start the workflow — returns immediately
  await temporalClient.workflow.start(processWebhookWorkflow, {
    taskQueue: 'webhook-processing',
    workflowId: `webhook-${payload.id}`,
    args: [payload],
  });

  return new Response('accepted', { status: 200 });
}

// The durable workflow
export async function processWebhookWorkflow(payload: WebhookPayload) {
  // Each activity has its own retry policy
  const normalized = await wf.proxyActivities<typeof activities>({
    retry: {
      maximumAttempts: 5,
      initialInterval: '1s',
      backoffCoefficient: 2,
      maximumInterval: '30s',
    },
  });

  const event = await normalized.parseAndValidate(payload);
  await normalized.writeToDatabase(event);
  await normalized.notifyDownstreamServices(event);
}

The activity retry policy is configurable at a granular level. maximumAttempts: 0 means unlimited retries (the default). backoffCoefficient: 2 gives exponential backoff. maximumInterval caps the delay so you do not end up waiting days between retries on a permanent failure. Non-retryable error types — business logic failures that should not be retried — can be specified explicitly.

If the writeToDatabase activity throws a transient error, Temporal retries it according to the policy. If the worker process crashes during that retry, Temporal brings up another worker, replays the history, and continues. Your database does not receive a duplicate write because Temporal tracks which activities have completed.

That guarantee — exactly-once activity execution from the application's perspective, even across crashes — is the core value.

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The Learning Curve Is Real

None of this is free — and teams that commit to Temporal fully tend to describe it as a paradigm shift. The mental model takes time to internalize, and the versioning story requires deliberate planning. For teams evaluating Temporal versus simpler alternatives, see our webhook debugging guide for the failure modes Temporal addresses, and the webhook vendor evaluation checklist for a broader tooling framework. The testing story is mature but different from standard unit testing. The versioning story — how to deploy new workflow code without breaking in-flight executions — is well-documented but requires deliberate planning.

Teams that commit to Temporal fully tend to describe it as a paradigm shift. The mental model takes time to internalize. The operational overhead of running Temporal Cloud is manageable; the operational overhead of self-hosting the Temporal server is a real engineering investment.

For a team processing millions of events per day where processing reliability is the core engineering challenge — this investment is justified. For a team with one engineer who also maintains the billing system — it probably is not the right starting point.

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Inngest: The Managed Alternative

Inngest is worth serious consideration as an alternative to Temporal for teams who want the core ideas — durable functions, automatic retries, idempotency steps — without the architectural commitment.

Inngest functions run on your existing infrastructure (deployed as serverless functions or server routes). You define functions that receive events, and Inngest handles retrying failed steps, managing concurrency, and preventing duplicate executions. Their "Replay" feature is positioned explicitly as a DLQ alternative: when events fail, you can replay them from the Inngest dashboard without writing custom recovery code.

// Inngest function — much closer to writing a normal function
export const processWebhook = inngest.createFunction(
  { id: 'process-webhook', retries: 5 },
  { event: 'webhook/received' },
  async ({ event, step }) => {
    // Each step.run() is an idempotency boundary
    const normalized = await step.run('parse-payload', async () => {
      return parseAndValidate(event.data);
    });

    await step.run('write-to-database', async () => {
      return writeToDatabase(normalized);
    });
  }
);

The adoption cost is materially lower. You do not need to learn Temporal's execution model, run a Temporal server, or think about workflow determinism. The tradeoff is power: Temporal's workflow history, long-running process support, and cross-language SDK ecosystem are more capable. If Inngest fits your requirements, the implementation cost is a fraction.

Both tools are good. Inngest is faster to adopt. Temporal is more powerful and more complex. The honest recommendation is: if you can do what you need with Inngest, start there. Temporal is the step up when you need it.

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What Neither Tool Is: A Webhook Receiver

Here is the critical architectural point that determines whether Temporal or Inngest solves your problem — both are execution engines that process events they have already received. Neither captures events that arrive when nothing is running. See HookTunnel's webhook inspection features for how boundary capture fills that gap, and the flat $19/month Pro plan for what Pro replay provides.

Both are execution engines. They process events that have been received and handed to them. But who receives the webhook?

Your HTTP endpoint does. And if that endpoint is down — your worker is deploying, your serverless function is cold-starting, your server is being replaced — the webhook arrives at a moment when nothing is listening. Stripe fires the request, gets a connection error or a 500, and puts the event in its retry queue. Depending on Stripe's retry schedule, the next attempt might be in 1 hour. In the meantime, your Temporal workflow never started. There is no event history because no event was received.

Temporal's durable execution guarantees nothing about events that never reached the execution layer.

HookTunnel operates at the HTTP boundary — before the execution layer. It receives the incoming webhook request, stores the raw payload, and keeps it for the history window (24 hours on Free, 30 days on Pro). If your worker is down when the webhook arrives, HookTunnel still captures it. When your worker is back up, Pro users can replay the original HTTP payload to any target endpoint — including the Temporal workflow starter endpoint.

The replay semantics are different and complementary. HookTunnel's replay is: re-send the original HTTP payload. Temporal's replay is: re-execute the workflow from its event history. These are different operations at different layers solving different failure modes.

The failure scenario they address together:

1. Stripe fires payment.succeeded at 2:47 AM.
2. Your worker is in the middle of a rolling deploy. The endpoint returns 503.
3. HookTunnel captured the payload. Temporal has no workflow yet — it was never handed the event.
4. Your deploy completes. Workers are healthy.
5. HookTunnel Pro: you replay the captured event to your webhook endpoint.
6. Your endpoint receives it, starts the Temporal workflow.
7. From here, Temporal's durability guarantees apply normally.

Without HookTunnel, step 5 does not exist. You are waiting for Stripe's retry schedule, or you are manually reconstructing the event from Stripe's dashboard.

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Who Should Use What

Use Temporal if: webhook processing reliability is your core engineering challenge, your team has the bandwidth to learn the execution model, you need long-running workflows spanning hours or days, or you are processing at a scale where exactly-once guarantees in the execution layer are non-negotiable.

Use Inngest if: you want Temporal's core ideas with lower adoption cost, you are deploying as serverless functions, or you want managed infrastructure rather than operating your own Temporal server.

Use HookTunnel if: you need to capture and preserve inbound webhook payloads at the HTTP boundary, forensic history and replay capabilities for failed deliveries, or a stable inspection URL for development and debugging — regardless of what execution engine you use downstream.

These are not competing choices at the same layer. Temporal and Inngest answer: "how do I make my processing durable?" HookTunnel answers: "how do I make sure the payload gets to my processing layer in the first place?"

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A Direct Assessment

Temporal is extraordinary infrastructure. The team that built it — originally at Uber as Cadence, then as the independent Temporal project — did some of the most careful distributed systems engineering in the open-source ecosystem. The durable execution model is genuinely one of the best ideas in the last decade of backend infrastructure.

If webhook processing reliability is your core engineering challenge and you are ready for the architectural commitment — it is one of the best tools available.

But the commitment is real. Most teams adopting Temporal for the first time underestimate the ramp. The mental model shift from stateless request handlers to durable workflow functions takes weeks to fully internalize, not days. The operational investment in Temporal Cloud is reasonable; self-hosting is a larger project.

If your team needs forensics and replay today — before you have stood up a Temporal cluster, before you have written your first workflow — there is a $19/month layer that gives you boundary capture, event history, and guardrailed replay right now. Not as a replacement for Temporal. Not even as a competitor. As a boundary layer that makes Temporal more effective by ensuring your durable execution engine actually receives the events it is supposed to execute.

Not mutually exclusive. Temporal is the right answer for many teams. HookTunnel is the right boundary layer before it.

There is a new dog in this neighborhood, and it operates at a different part of the stack. Worth knowing it exists.