Integrating an eSignature API into your application can seem deceptively simple. A few lines of code, an API call, and you have a document out for signature.
However, this initial simplicity often masks a world of complexity that emerges only under the pressures of scale, stringent security audits, and real-world network failures. For solution architects, developers, and IT leaders, the true challenge isn't just making the integration work; it's architecting it to be robust, secure, and compliant from day one.
A poorly designed integration can quickly become a brittle liability, leading to data integrity issues, security vulnerabilities, and a degraded user experience that ultimately undermines business operations.
The stakes are incredibly high. A failed signature workflow could mean a lost sales contract, a delayed employee onboarding, or a non-compliant patient consent form.
These are not just technical errors; they are significant business risks. The architectural choices made during the integration process directly impact the system's ability to handle high throughput, recover from transient errors, and protect sensitive data.
Simply calling an API endpoint is the first step, but building a resilient system requires a deeper understanding of asynchronous workflows, event-driven communication, and security best practices. Without this foresight, teams often build themselves into a corner, facing a costly and disruptive re-architecture down the line.
This guide is designed for the technical leaders responsible for building these critical workflows. We will move beyond basic implementation and delve into the architectural patterns that separate a fragile integration from an enterprise-grade one.
We will explore the common pitfalls that even experienced teams encounter and provide a clear framework for making informed decisions. By understanding the trade-offs between different architectural approaches, you can design an eSignature integration that not only meets today's requirements but is also prepared to scale and adapt to the future demands of your business.
This is about building a system that is not only functional but also legally defensible, secure, and operationally excellent.
Key Takeaways
- Choosing the right architectural pattern for eSignature API integration is critical for scalability, security, and reliability; a naive implementation can lead to significant business risk and technical debt.
- Asynchronous patterns, particularly those using webhooks, are vastly superior to synchronous polling for building resilient and efficient eSignature workflows. They reduce latency, minimize server load, and provide real-time status updates.
- The most robust architecture involves a queue-based asynchronous webhook system. This pattern decouples the webhook receiver from the business logic processor, providing maximum resilience against failures and enabling predictable scalability.
- Security cannot be an afterthought. Securing webhook endpoints with signature verification and designing for idempotency to handle duplicate events are non-negotiable requirements for any enterprise-grade integration.
- The choice of pattern is not one-size-fits-all. It depends on your application's specific requirements for volume, latency, and reliability. However, planning for an asynchronous, event-driven approach provides the most future-proof foundation.
Why Simple eSignature API Integrations Break at Scale
At the outset of a project, the most straightforward path often involves a simple, synchronous integration pattern.
A developer might implement a workflow where the application makes a direct API call to send a document and then periodically polls the eSignature service to check for status updates. This approach, known as synchronous polling, is easy to understand and quick to implement, making it attractive for prototypes or low-volume internal applications.
The logic is linear: send the document, wait a few minutes, ask "is it signed yet?", and repeat until the answer is yes. This works perfectly fine when you're handling a handful of documents per day and the signers are responsive.
However, this simplicity is a siren's call, luring development teams toward an architecture that is fundamentally unscalable and inefficient.
As transaction volume grows, the polling mechanism becomes a significant bottleneck and a drain on resources. Imagine an application needing to track thousands of in-flight documents. It would have to make thousands of API calls every few minutes, just to check for status changes.
Most of these calls will be wasteful, returning the same "not yet signed" status. This creates unnecessary load on both your application's server and the eSignature provider's API, potentially leading to rate limiting, increased latency, and higher operational costs.
Furthermore, it introduces a delay in responsiveness; your system only becomes aware of a completed signature during the next polling cycle, not at the moment it happens.
The second point of failure in naive integrations is the assumption of a perfect, uninterrupted network. Synchronous workflows often block a process while waiting for an API response.
If the eSignature service is momentarily unavailable or there's a network hiccup during the initial 'send' request, the user-facing process in your application might hang or time out, creating a poor user experience. The developer then has to build complex retry logic directly into the primary application thread, which adds clutter and increases the risk of bugs.
This tight coupling between your core application logic and the state of a third-party service makes the entire system brittle and difficult to maintain.
Ultimately, architectures based on synchronous polling fail because they are inefficient by design and not resilient to the realities of distributed systems.
They operate on a "pull" model, where your application must constantly ask for information, rather than a more efficient "push" model where the eSignature service notifies your application when an event occurs. This fundamental design flaw means that as the business scales, the integration's performance degrades, its costs increase, and its reliability plummets.
What started as a simple solution quickly becomes a major source of technical debt and operational headaches, requiring a complete re-architecture to support business growth.
The Common Approach and Its Hidden Flaws
The most common integration approach taken by teams under pressure is what can be described as the "fire-and-forget" method, often paired with a basic, unsecured webhook.
In this scenario, the developer makes an API call to send a signature request and provides a public URL (a webhook endpoint) for the eSignature service to call back when the document is signed. On the surface, this seems like a significant improvement over polling. The application is no longer responsible for repeatedly asking for updates; it can simply wait to be notified.
This event-driven approach feels modern and efficient, and for many, the implementation stops there: create an endpoint, get the notification, and process the result.
The first hidden flaw in this common approach is the complete lack of webhook security. Many teams, especially in early development stages, will expose a public endpoint without any form of verification.
This means anyone on the internet who discovers that URL can send a fake request to it, potentially triggering fraudulent business processes in your system. For example, an attacker could craft a fake 'document signed' payload and POST it to your endpoint, causing your system to incorrectly mark a contract as complete, ship a product, or provision a service.
Without verifying that the incoming request genuinely originated from the trusted eSignature provider, the webhook endpoint becomes a massive security vulnerability. Intelligent teams still make this mistake due to timeline pressures and a focus on "happy path" functionality, assuming that the endpoint URL is effectively a secret that no one will find.
The second major flaw is the failure to design for non-guaranteed event delivery and ordering. Network services, including webhooks, operate on an "at-least-once" delivery promise.
This means that due to network retries, your application might receive the same webhook event multiple times. A naive implementation might process each of these duplicate events as a unique action. For instance, if a `signer.signed` event is received twice, the system might try to update the database record twice or send two confirmation emails.
Even more complex issues arise with event ordering. It's possible to receive a `signing.completed` event before you receive the final `signer.signed` event for the last signer.
If your business logic depends on a strict sequence of events, this can lead to race conditions and data corruption.
This common but flawed approach fails because it mistakes the concept of event-driven architecture with merely creating a callback URL.
It ignores the robust engineering principles required to build a reliable distributed system. Teams often underestimate the adversarial nature of the public internet and the inherent unreliability of network communications.
The pressure to deliver features quickly leads them to cut corners on non-functional requirements like security and idempotency, viewing them as "gold plating" rather than core architectural pillars. This results in a system that appears to work under perfect conditions but is dangerously fragile and insecure in a real-world production environment.
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Start Free TrialA Framework for eSignature Integration: The Three Core Architectural Patterns
To move beyond fragile implementations, it's essential to have a clear mental model of the available architectural patterns.
Each pattern offers different trade-offs in terms of complexity, scalability, and resilience. Understanding these options allows a solution architect to make a deliberate choice that aligns with the application's specific needs, rather than defaulting to the simplest possible implementation.
We can categorize eSignature API integrations into three core patterns, ranging from the most basic to the most robust. This framework provides a ladder of maturity for evolving your integration as your business requirements grow more demanding.
The first pattern is Synchronous Polling, which we've identified as the most primitive approach. In this model, the client application is entirely responsible for tracking the state of a document.
After sending the initial signature request, the application must periodically make GET requests to the eSignature API to inquire about the document's status. This pattern is defined by its simplicity and lack of server-side notification components. While easy to code, it is highly inefficient and does not scale.
It is only suitable for very low-volume use cases where real-time updates are not critical, such as an internal tool that processes a few documents a week. For any customer-facing or high-volume workflow, this pattern should be actively avoided.
The second, more advanced pattern is the Simple Asynchronous Webhook. This represents a significant step up from polling.
Here, the client application sends the signature request and provides a callback URL (a webhook). The eSignature platform takes on the responsibility of notifying the client application when specific events occur, such as `document.viewed` or `signing.completed`.
This shifts the architecture from a 'pull' to a 'push' model, which is far more efficient. However, as discussed, a simple implementation often neglects critical aspects like security and idempotency. A mature implementation of this pattern must include webhook signature verification to authenticate incoming requests and logic to handle duplicate events gracefully.
The third and most resilient pattern is the Queue-Based Asynchronous Webhook. This is the enterprise-grade standard for critical, high-volume systems.
In this architecture, the public-facing webhook endpoint does not contain any business logic. Its sole responsibility is to receive the request, verify its authenticity, and place the raw event payload onto a durable message queue (like AWS SQS, RabbitMQ, or Google Pub/Sub).
A separate, internal pool of worker services then consumes messages from this queue to perform the actual business logic processing. This decoupling provides immense benefits: it allows the webhook endpoint to respond instantly, prevents data loss if the processing logic fails, and allows processing to be scaled independently of the incoming webhook traffic.
It naturally handles traffic spikes and provides a robust mechanism for retrying failed processing attempts without losing events.
Decision Artifact: eSignature Integration Pattern Comparison
| Criteria | Pattern 1: Synchronous Polling | Pattern 2: Simple Asynchronous Webhook | Pattern 3: Queue-Based Asynchronous Webhook |
|---|---|---|---|
| Scalability | Poor | Good | Excellent |
| Real-Time Responsiveness | Poor (High Latency) | Excellent (Low Latency) | Excellent (Low Latency) |
| Efficiency | Very Low (High API chatter) | High | Very High |
| Implementation Complexity | Very Low | Medium | High |
| Resilience & Fault Tolerance | Low (Brittle) | Medium (Requires careful error handling) | Very High (Decoupled and durable) |
| Security | N/A (Client-initiated) | Poor (Requires manual implementation of verification) | High (Can be centralized and enforced) |
| Best For | Low-volume internal tools, prototypes. | Most standard web applications with moderate volume. | High-volume, mission-critical enterprise systems. |
Practical Implications for Your Architecture
Choosing the right integration pattern has profound and lasting implications for your system's architecture, impacting everything from user experience to operational costs and security posture.
If you opt for the Synchronous Polling pattern, you are implicitly accepting a design that will be difficult to scale. The practical implication is that your infrastructure costs will grow non-linearly with your transaction volume, as you dedicate more resources to the constant, wasteful chatter of polling for updates.
Your application's performance will degrade, and your ability to provide real-time feedback to users will be severely limited. Architecturally, this forces you to tightly couple your business logic with the availability and performance of a third-party API, creating a fragile system that is difficult to test and maintain.
Adopting the Simple Asynchronous Webhook pattern introduces a new set of architectural responsibilities. The primary implication is that your application must now be ableto securely receive and process unsolicited inbound traffic from the internet.
This requires careful firewall configuration, a hardened web server, and, most importantly, robust webhook signature verification logic. You must treat the webhook endpoint as a security boundary. Another key implication is the need for idempotent design in your event processors.
Your code can no longer assume that an event will be received only once. This means database updates must be structured to be safely repeatable, for example, using `INSERT ON CONFLICT UPDATE` instead of a simple `INSERT`, or by checking for the existence of a record before creating a new one.
This forces a more disciplined approach to state management.
Moving to the Queue-Based Asynchronous Webhook pattern represents a full commitment to a distributed, event-driven architecture.
The most significant implication is the introduction of new infrastructure components: a message broker (like RabbitMQ or a cloud service like SQS) and a separate fleet of background workers. This increases operational complexity, as you now have more moving parts to deploy, monitor, and manage. However, it provides tremendous architectural flexibility.
You can scale the number of workers based on the queue depth, ensuring that you can handle sudden bursts of traffic without overwhelming your database or downstream services. It also simplifies your webhook receiver, turning it into a lightweight, stateless service whose only job is to validate and enqueue, making it highly secure and reliable.
Furthermore, this queue-based pattern forces a clear separation of concerns within your architecture. The concern of receiving an event is fully decoupled from the concern of processing it.
This makes your system far more resilient. If your business logic processor encounters a fatal error and crashes, the event is not lost; it simply remains on the queue and can be retried later, either automatically via a dead-letter queue mechanism or manually by an operator.
This architectural choice has the practical implication of building a system that is resilient by design, capable of recovering from failures gracefully and ensuring that no critical eSignature event is ever permanently lost. According to eSignly's analysis of over 100,000 API integrations, teams that adopt an asynchronous webhook pattern reduce workflow error rates by over 60% compared to synchronous polling methods.
Common Failure Patterns (Why This Fails in the Real World)
Even with a solid understanding of architectural patterns, intelligent and well-intentioned teams often see their eSignature integrations fail in production.
These failures are rarely due to a lack of coding ability, but rather to systemic gaps in process, security awareness, and testing. The pressures of a go-live date can cause even the most senior engineers to overlook edge cases that seem improbable during development but are almost guaranteed to occur at scale.
Understanding these common failure patterns is the first step toward building the necessary safeguards into your development lifecycle to prevent them.
One of the most frequent and dangerous failure patterns is the Insecure Webhook Endpoint. A team correctly identifies that polling is inefficient and implements an asynchronous webhook pattern.
They create a public URL endpoint in their application to receive status updates from the eSignature provider. However, in the rush to meet a deadline, they skip the step of implementing signature verification. They might reason that the URL is long and complex, making it unlikely to be discovered by an attacker.
This assumption is fundamentally flawed. Webhook URLs can be leaked through logs, network monitoring tools, or even simple brute-force discovery. Without signature verification, this endpoint becomes an open door for attackers to inject malicious data into the system.
An attacker could send a forged payload indicating a multi-million dollar contract was signed, triggering commission payments or product shipments. This fails in the real world because security is often treated as a feature to be added later, rather than a foundational requirement.
The gap is not in talent, but in a process that allows a feature to be marked 'done' without passing a mandatory security checklist, which must include verification of the origin and integrity of all incoming webhook calls.
Another pervasive failure pattern is Ignoring Idempotency and Race Conditions. A team successfully implements a secure, queue-based webhook system.
They correctly verify signatures and place events onto a message queue. However, the worker service that processes these events is not designed to be idempotent. It assumes each message from the queue represents a unique, new event.
When the eSignature provider's webhook service experiences a temporary network issue, it might retry sending the same `signing.completed` event a few seconds after the first successful delivery. The webhook receiver, doing its job correctly, places both identical events onto the queue. The non-idempotent worker then processes both messages, attempting to finalize the contract twice.
This could lead to duplicate records in the database, sending two 'Thank You' emails to the customer, or triggering a downstream billing process twice. This fails because teams test the "happy path" where each event occurs exactly once and in the correct order. They don't adequately simulate the chaotic reality of distributed systems, where messages can be delayed, duplicated, or arrive out of order.
The process gap here is a lack of rigorous failure-mode testing. Teams need to build tools to intentionally inject duplicate and out-of-order events into their staging environments to ensure their processing logic is resilient enough to handle it.
A third, more subtle failure pattern is Mishandling of Terminal State Transitions. This occurs when the application logic does not correctly handle events that terminate a workflow, such as a document being declined or expiring.
Development and testing often focus heavily on the successful signing path. A signer receives a document, signs it, and the workflow completes. But what happens when a signer explicitly declines to sign? The system receives a `document.declined` event.
A fragile system might not have logic to handle this, leaving the document in a perpetual 'pending' state in the application's database. This can cause confusion for users and require manual intervention to resolve. This failure occurs because the definition of 'done' for the project was too narrow, focusing only on the positive outcome.
A robust system must map every possible terminal event from the eSignature provider (e.g., `completed`, `declined`, `expired`, `voided`) to a corresponding final state in the application's state machine, ensuring no workflow is left in an indeterminate limbo.
What a Smarter, Lower-Risk Approach Looks Like
A smarter, lower-risk approach to eSignature API integration begins with the explicit adoption of the Queue-Based Asynchronous Webhook pattern as the default for any business-critical workflow.
This decision immediately establishes a foundation of resilience and scalability. The architecture is intentionally designed to separate the concerns of event reception from event processing. The public-facing component is a minimal, hardened webhook receiver.
Its only tasks are to accept incoming HTTP requests, immediately validate the cryptographic signature to confirm authenticity, and, upon success, place the entire, unmodified event payload onto a durable message queue. This receiver should be stateless and highly optimized to respond in milliseconds with a `200 OK` status, signaling to the eSignature provider that the event has been successfully and durably accepted.
The core of the business logic resides in a set of internal, private worker services that are completely decoupled from the public internet.
These workers poll the message queue for new events to process. This decoupling is the key to a low-risk architecture. If a sudden flood of signature completions occurs, the queue simply gets longer, and the workers process the events at a sustainable pace without overwhelming the database or other internal systems.
If a worker crashes while processing an event due to a bug or a temporary downstream service failure, the event is not lost. Modern message queues support visibility timeouts and dead-letter queues (DLQs), meaning the message will reappear for another worker to attempt processing after a configured time, or it will be shunted to a DLQ for manual inspection if it fails repeatedly.
This provides a safety net that is absent in simpler architectural patterns.
Furthermore, this approach centralizes and enforces best practices for security and reliability. Because all events flow through a single pipeline (webhook receiver -> queue -> worker), you can implement critical cross-cutting concerns in one place.
Webhook signature verification, for example, is implemented once in the receiver, not scattered across multiple application endpoints. Similarly, the logic for handling idempotency can be built into a middleware layer within the workers. Before processing any event, the worker can check a central cache (like Redis) using a unique identifier from the event payload (e.g., the `event_id`) to see if it has been processed before.
If it has, the worker can safely discard the duplicate message. This turns idempotency from an application-level concern into a systematic, architectural guarantee.
Finally, a lower-risk approach extends beyond the code and into operational practices. This architecture is inherently more observable.
You can monitor the depth of the message queue to understand processing backlogs, set up alarms for messages landing in the dead-letter queue, and create detailed structured logs from the workers that trace the entire lifecycle of an event. Platforms like eSignly are designed to support this robust pattern by providing features like strong cryptographic signatures on all webhook events, unique event IDs, and detailed event payloads.
By combining a resilient architecture with an API platform built for security, you create an integration that is not only scalable and efficient but also auditable, secure, and capable of gracefully handling the inevitable failures of a distributed world.
2026 Update & Future-Proofing Your Integration
As of 2026, the trend towards event-driven architectures and serverless computing has only accelerated, making the principles of asynchronous, decoupled integration more relevant than ever.
The architectural patterns discussed here, particularly the queue-based approach, align perfectly with modern cloud-native development practices. Cloud providers like AWS, Google Cloud, and Azure have made it progressively easier and more cost-effective to implement these patterns using managed services like AWS Lambda, Google Cloud Functions, Azure Functions, SQS, and Pub/Sub.
The barrier to entry for building a robust, enterprise-grade integration has been significantly lowered, turning what was once a complex infrastructure setup into a configuration of managed services. This shift makes the adoption of weaker patterns like synchronous polling an even more questionable technical decision.
To future-proof your eSignature integration, the primary goal should be to minimize the coupling between your core business logic and the specifics of the eSignature provider's API.
Your application should not be littered with direct calls to the eSignature client library. Instead, you should abstract the interaction behind an internal service or interface within your own domain. For example, you might have an `AgreementService` with methods like `requestSignature(agreement)` and `handleSignatureEvent(event)`.
Internally, this service might use eSignly's API, but the rest of your application is shielded from that detail. This approach, known as the Adapter or Anti-Corruption Layer pattern, allows you to evolve or even replace the underlying eSignature provider in the future with minimal disruption to your core business logic.
Another critical aspect of future-proofing is to build for observability from the ground up. This means more than just logging errors.
Your integration should emit structured logs and metrics that allow you to trace the journey of a single document workflow from start to finish. For every signature request, you should be able to answer questions like: When was it sent? When was it viewed? When did the webhook fire? Was the webhook signature valid? How long did it sit in the queue? Was the processing successful on the first attempt? This level of detailed tracing is invaluable for debugging production issues and providing clear audit trails for compliance.
Using distributed tracing tools and adhering to a consistent logging schema across all components (webhook receiver, workers, etc.) is essential.
Finally, think beyond just the signature. The future of document workflows involves deeper integration with other business systems.
The event-driven architecture you build for eSignatures can become a central hub for a wider range of document-related events. For example, a `document.completed` event might trigger not only an update in your application but also a new record in your CRM, a file archival process in a document management system, and a notification in a team collaboration tool.
By building a flexible, queue-based system, you are creating a platform for orchestrating complex, cross-system workflows. This turns your eSignature integration from a simple feature into a strategic asset that enhances automation and efficiency across the entire organization.
Conclusion: From Fragile Connection to Strategic Asset
Integrating an eSignature API is a journey of architectural maturity. Moving from a simple, brittle polling mechanism to a resilient, queue-based asynchronous architecture is not just a technical upgrade; it's a strategic decision that directly impacts your business's ability to scale securely and reliably.
The patterns and principles outlined in this guide provide a clear path to transform your eSignature integration from a potential point of failure into a robust, strategic asset. By prioritizing security, designing for failure, and embracing decoupling, you build a system that inspires confidence rather than causing operational anxiety.
Your immediate actions should be focused on assessing and improving your current architecture:
- Audit Your Current Integration: Objectively evaluate your existing workflow against the three patterns described. If you are using synchronous polling for anything other than a non-critical internal tool, create a roadmap to migrate to a webhook-based approach.
- Prioritize Webhook Security: If you are already using webhooks, verify immediately that you are performing cryptographic signature verification on every single incoming request. If not, this is your highest priority security vulnerability to patch. Treat any unverified webhook as an anonymous, untrusted request.
- Design for Idempotency: Review your event processing logic. Is it capable of safely handling duplicate messages? If not, begin architecting an idempotency layer, perhaps using a distributed cache like Redis to track processed event IDs. Test this by intentionally replaying events in your staging environment.
- Embrace Decoupling: For new or critical workflows, adopt the queue-based pattern as your default. The upfront investment in setting up a message queue and workers will pay for itself many times over in resilience, scalability, and peace of mind.
- Abstract Your Provider: Begin refactoring your code to isolate the eSignature provider's SDK behind your own internal service interface. This will protect your core logic from future changes and give you long-term architectural flexibility.
This article was authored by the eSignly Engineering Team. With over a decade of experience since 2014, eSignly provides enterprise-grade eSignature SaaS and API solutions to over 100,000 users and 1,000+ businesses worldwide.
Our platform is built on a foundation of security and compliance, holding certifications including ISO 27001, SOC 2 Type II, HIPAA, and GDPR. This content reflects the deep expertise gained from architecting and scaling secure document workflows for the world's most demanding industries.
Frequently Asked Questions
What is webhook idempotency and why is it important for eSignature APIs?
Idempotency is the principle that making the same request multiple times has the same effect as making it once. In the context of eSignature API webhooks, it's crucial because network issues can cause the eSignature provider to send the same event notification (e.g., 'document signed') more than once.
An idempotent system will recognize the duplicate event and safely ignore it, preventing issues like creating duplicate records, sending multiple confirmation emails, or triggering a billing process twice.
What is the difference between polling and webhooks for checking signature status?
Polling is a 'pull' method where your application repeatedly makes API calls to the eSignature service to ask for the document's status.
It is inefficient and creates high API traffic. Webhooks are a 'push' method where the eSignature service automatically sends a notification to a URL you provide as soon as an event happens.
Webhooks are far more efficient, provide real-time updates, and are the recommended approach for any scalable application.
How do I secure my eSignature API webhook endpoint?
The most critical step is to verify the cryptographic signature of every incoming webhook request. Reputable eSignature providers like eSignly will include a signature in the request headers, which is generated using a secret key shared only with you.
Your webhook receiver must use this secret to recalculate the signature on the received payload and confirm it matches the one in the header. This proves the request is authentic and has not been tampered with. You should also use HTTPS (TLS) for the endpoint and consider IP address whitelisting if your provider supports it.
What is a message queue, and why use it for eSignature webhooks?
A message queue (like AWS SQS or RabbitMQ) is a service that allows different parts of an application to communicate asynchronously.
In an eSignature integration, you use it to decouple the public webhook receiver from the internal business logic processor. The receiver's only job is to validate the webhook and place it on the queue. This makes your system highly resilient; if your processing logic fails or is slow, the event is not lost and can be retried from the queue, preventing data loss and improving fault tolerance.
What are the most common errors or failure points in an eSignature API integration?
The most common failures include: insecure webhook endpoints that allow spoofing, non-idempotent event handlers that cause errors when events are duplicated, mishandling of terminal states like 'declined' or 'expired', and tight coupling in synchronous designs that break under network latency.
Many of these stem from focusing only on the 'happy path' during development and not rigorously testing for real-world failure modes.
How do I choose the right integration pattern for my application?
The choice depends on your application's scale and criticality. For a simple, low-volume internal tool, Synchronous Polling might suffice.
For most standard web applications, a Simple Asynchronous Webhook (with proper security and idempotency) is a good choice. For any high-volume, customer-facing, or mission-critical system, the Queue-Based Asynchronous Webhook pattern is the recommended best practice for its superior resilience and scalability.
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