For work that cannot reliably finish within an HTTP response window, an asynchronous request-reply API can acknowledge durable acceptance and let the client track a separate operation through completion. The queue can absorb bursts and workers can scale independently, but the design must also handle duplicate submissions, growing backlogs, failures, and completion notifications.
Why use asynchronous request-reply?
In a synchronous API call, the client waits while the service performs the requested work. If a backend takes too long, a timeout leaves an important question unanswered: did the service never receive the request, accept it but keep working, or finish while its response was lost? A retry may then create a second operation.
The asynchronous request-reply pattern gives long-running work its own lifecycle. The API accepts a request, returns a reference to the operation, and lets the client check or receive its eventual outcome. This is useful when work cannot reliably finish within the response window or when buffering and independent scaling are valuable. It is not automatically better for a short operation whose result the client needs immediately; asynchronous processing adds state and operational responsibilities.
Define the API contract from acceptance to completion
The queue is only one component. The caller-facing contract should say what acceptance means, how to locate the operation, which states it can enter, and how the client learns the result. AWS Prescriptive Guidance and the Microsoft Azure Architecture Center describe durable acknowledgment, status resources, and completion mechanisms as central parts of asynchronous communication.
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- Submit: The client sends a request to start work. The API validates it and records the operation or places it in durable storage.
- Acknowledge: Once the operation is durably accepted, the API responds with an operation identifier or status location. “Accepted” should not mean only that a process received the request in memory.
- Process: A worker retrieves the work and performs it independently of the original client connection.
- Expose status: A status endpoint reports whether the operation is pending, running, succeeded, or failed. Where useful, it can include progress or timing information.
- Deliver completion: The client polls the status resource or receives a callback, event, or update over a bidirectional connection.
Make the response semantics explicit: acceptance is not completion, and a status lookup should distinguish work still in progress from a terminal result. If the API supports cancellation, define what it guarantees. Work may already have produced partial effects; stopping a worker does not necessarily undo them. Explain whether cancellation prevents future steps, triggers rollback, or requires a compensating action.
Make client retries safe
A lost acknowledgment creates uncertainty for the client: the request may have been accepted even though no response arrived. Retrying a POST without deduplication can enqueue the same logical work twice.
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Accept an idempotency key or request identifier that lets the service associate retries with the existing operation. When a client repeats a request with the same key, return the existing operation reference and status instead of creating another operation. Amazon’s Builders’ Library guidance on safe retries emphasizes that the identifier and the associated operation must be recorded consistently; otherwise a retry can still race with persistence.
- Define the key’s scope, such as the authenticated caller and operation type, so unrelated requests do not collide.
- Define how long keys are retained and what happens after expiry.
- Specify behavior when a client reuses a key with changed parameters. Reject the mismatch or document a deliberate alternative.
- Ensure the operation record and its deduplication key are persisted consistently with enqueueing.
Do not promise generic “exactly once” execution. A worker can fail after performing an effect but before recording success, so a retry may repeat the work. Design for safe retries and define the externally observable effect: for example, whether repeating a payment or job submission can create a second result.
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A common architecture is client → API → durable queue → workers. The queue separates producers from consumers and can absorb temporary bursts; the API and workers can be scaled separately. It does not create unlimited capacity. When requests arrive faster than workers can process them, queue age rises and users wait longer for completion. AWS Prescriptive Guidance for SQS integration and AWS Well-Architected reliability guidance both treat queue behavior and failure handling as operational concerns, not details a queue removes.
- Measure user-visible delay: Monitor queue depth and message age alongside processing latency. A small queue of slow work can be more concerning than a larger queue workers are draining quickly.
- Bound admission and backlog: Set queue limits or apply admission control so overload is visible and controlled instead of accumulating indefinitely. Return a clear rejection or retryable response when the service cannot safely accept more work.
- Retry deliberately: Use bounded retries with backoff for transient failures. Unbounded or rapid retries can amplify load on an already unhealthy dependency.
- Isolate repeated failures: Route messages that exhaust retries to a dead-letter destination and define who investigates them and how safe redrive works.
- Handle stale requests: If a job has lost its value by the time capacity becomes available, discard or deprioritize it according to an explicit policy.
- Acknowledge after durable acceptance: Persist the operation and its queued work before telling the caller it has been accepted.
These controls help keep a queue a buffer rather than a hidden backlog that makes every accepted request appear healthy while completion becomes arbitrarily delayed.
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The right completion channel depends on the required notification delay, client capabilities, expected concurrency, and the burden the service can operate. AWS and Microsoft guidance describe polling, long polling, callbacks, and bidirectional communication as options with different costs.
| Mechanism | How it works | Trade-offs |
|---|---|---|
| Periodic polling | The client requests the operation’s status at intervals. | Simple and resilient to a temporarily disconnected client; creates repeated requests and detection delay. Caching or rate limits can reduce unnecessary load. |
| Long polling | The client makes a status request that the server holds open until an update or timeout. | Can reduce repeated checks, but requires careful connection management and timeout behavior. |
| Callback or webhook | The service calls a client-provided endpoint when the operation changes or completes. | Avoids constant client checks, but the service must secure destinations and handle delivery failures, timeouts, and retries. |
| Bidirectional connection | The service sends updates over an established two-way channel. | Useful for interactive updates, but adds connection state and requires clear handling for ordering, disconnection, and recovery. |
Polling is often a straightforward starting point when eventual notification is sufficient. For tighter updates or large numbers of waiting clients, compare the connection and delivery costs rather than assuming a push mechanism is simpler. A callback also cannot replace an inspectable operation status: clients need a way to recover if a notification is missed.
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Decide whether asynchronous processing fits
Before adopting the pattern, answer the questions that determine its contract and operating cost:
- Can the operation finish predictably within the HTTP response window, and does the client actually need its final result immediately?
- What durable guarantee does an acceptance response make?
- How will the API recognize a duplicate request after a lost response?
- What happens when the queue backs up, a worker fails repeatedly, or a request becomes stale?
- How will a client inspect progress, recover from a missed notification, or request cancellation?
Asynchronous request-reply is a useful way to improve responsiveness and scale producers and consumers independently when the workload warrants it. The trade-off is that operation lifecycle visibility, deduplication, notification, retry policy, and backlog management become part of the API design.
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