Sit down, take a breath, and let’s explore a bit about asynchronous operations in web APIs. If you are out of time, please, use the table of contents above. And let’s start it!

With the increasing complexity of data operations performed through APIs, the demand for more efficient methods for handling these requests has grown. Traditional synchronous REST APIs have the client wait for the request to be processed, which can lead to long wait times and inefficiencies. The solution to this problem is asynchronous operations, allowing the client to make a request, then continue with other tasks until the result is ready. In this article, we will delve deep into different approaches to perform asynchronous operations or results in REST APIs, discussing their merits, challenges, and suitable use-cases.

Synchronous Vs. Asynchronous APIs

In the world of REST APIs, the synchronous approach has been the standard for a long time. With this model, the client makes a request and waits for the response. The connection remains open, and the client is essentially blocked until the server processes the request and sends back the response.

On the contrary, asynchronous APIs are designed to perform tasks in a non-blocking manner. When a client makes a request, the server acknowledges the request and frees up the client to perform other tasks. Once the task is completed, the server notifies the client that the results are ready. This model can be beneficial when dealing with operations that require heavy computation or involve waiting for some external process.

The move towards asynchronous APIs is driven by the need for efficiency and the desire to improve the user experience. The non-blocking nature of asynchronous APIs means they can handle more requests simultaneously, reducing the likelihood of system bottlenecks. From the user’s perspective, applications feel faster and more responsive because they don’t have to wait for a response before they can proceed with other tasks.

Now that we understand the difference between synchronous and asynchronous operations let’s explore various approaches to implementing asynchronous operations in REST APIs.

Polling Approach

Polling is a straightforward and commonly used approach to handle asynchronous operations in REST APIs. The essence of polling lies in the client periodically making requests to the server to check if the response is ready. This approach is quite simple to understand and implement, but it also comes with its own set of challenges and considerations.

How Polling Works

The client initiates a request to the server, expecting that the processing of the request will take some time. The server acknowledges the request, often by providing a unique identifier or a ’ticket’ for the task, and starts processing.

While the server is working on the request, the client periodically sends a new request to check the status of the task using the provided identifier. These ‘polling’ requests ask the server if the processing is completed and if the result is ready.

When the server completes the task, it flags the job as finished and holds the results. The next time the client polls the server for the status, the server responds that the job is done and provides the requested data.

Pros and Cons of Polling

The polling approach has several advantages. For one, it’s easy to implement and understand. It doesn’t require any special infrastructure or complex mechanisms on the client or the server. It works well with HTTP and fits naturally into the request-response paradigm.

However, polling has some significant drawbacks. The primary one is inefficiency. If the client polls too frequently, it can put an unnecessary load on the server, especially if the processing of the request takes a long time or if there are many clients polling the server simultaneously. On the other hand, if the client polls infrequently, it can lead to a delay in receiving the response once the processing is completed.

Another potential issue with polling is the extra overhead. Each polling request and response carries a certain amount of data overhead for headers, establishing and closing connections, and other HTTP protocols. This overhead can add up, particularly when the polling frequency is high.

Best Practices for Polling

Despite its challenges, polling can be an effective solution for asynchronous operations in certain scenarios. To get the most out of it, it’s essential to follow some best practices:

  1. Adaptive Polling: Instead of polling at a fixed frequency, the client can adjust the polling rate based on factors like server load and historical data on how long the processing typically takes.

  2. Exponential Backoff: This strategy involves gradually increasing the wait time between polling requests. The client starts by polling frequently, then slows down over time. This approach can help reduce server load while still providing relatively timely results.

  3. Long Polling: Long polling is a variation where the server holds the client’s polling request open until it has a response ready or a certain amount of time has passed. This can help reduce the delay in receiving the response and the number of polling requests.

While polling has its drawbacks, it is a tried-and-tested method for handling asynchronous operations in REST APIs. By understanding its strengths and weaknesses and applying best practices, developers can leverage polling effectively in the right scenarios.


Webhooks offer another method for handling asynchronous operations in REST APIs. Unlike the polling approach, where the client continuously checks the server for a response, webhooks are all about the server notifying the client once the processing is completed. This “reverse” communication method is often referred to as a “push” mechanism, and it presents a proactive, efficient, and real-time solution to the challenge of asynchronous operations.

How Webhooks Work

At the most basic level, a webhook is a callback mechanism via HTTP POST that triggers when specific events occur.

The client, while initiating the original request, provides the server with a callback URL — essentially telling the server where to send the response once the processing is done. The server acknowledges the request and begins processing. Unlike the polling approach, the client does not make any additional requests during this time.

Upon completion of the task, the server makes a POST request to the callback URL provided by the client, including the results of the operation in the body of the request. This way, the client receives the data as soon as it’s ready.

Pros and Cons of Webhooks

Webhooks have some significant advantages over polling. The most noticeable one is efficiency: the server only needs to send a response when the data is ready, and the client doesn’t have to keep checking back. This reduces the load on both the client and the server, improving overall performance.

Webhooks also allow for near real-time communication. As soon as the processing is completed, the client receives the data, making webhooks an excellent choice for time-sensitive operations.

However, webhooks are not without their challenges. Implementing webhooks requires more effort than polling as the client needs to set up an endpoint that can accept and handle incoming POST requests from the server. Security can also be a concern as the client has to ensure that incoming requests are indeed from the trusted server and not an attacker.

Moreover, since webhooks depend on the server pushing data to the client, issues like firewalls, network outages, or server downtime can disrupt the communication.

Best Practices for Webhooks

Despite these challenges, webhooks can be an incredibly effective solution for asynchronous operations when implemented correctly. Here are some best practices to consider when working with webhooks:

  1. Security Measures: Employ security measures such as verifying incoming requests, using HTTPS for the callback URLs, and protecting against attacks like replay attacks.

  2. Error Handling and Retries: The server should handle scenarios where the client’s endpoint is unavailable or not ready to receive the response. This could involve queuing the requests and implementing a retry mechanism.

  3. Monitoring and Logging: Both client and server should have robust logging and monitoring in place to track the requests and responses, identify failures, and troubleshoot issues.

  4. Webhook Management: If your API supports webhooks, providing users with a management interface can be incredibly helpful. This interface could allow users to set up, modify, and delete webhooks, as well as review recent webhook activity.

Webhooks provide an efficient and proactive approach to handling asynchronous operations in REST APIs. With careful implementation, thoughtful error handling, and robust security measures, they can offer significant benefits over traditional polling methods.

GraphQL Subscriptions

While REST APIs have been the traditional way to interact with server-side data, GraphQL has rapidly gained popularity due to its efficiency and flexibility. One of the most compelling features of GraphQL in the context of handling asynchronous operations is GraphQL Subscriptions.

How GraphQL Subscriptions Work

GraphQL Subscriptions allow the server to send real-time updates to the client over a persistent connection. This feature is especially beneficial for events like real-time messaging, live updates, or any scenario where the client needs to be notified as soon as data changes on the server.

When the client makes a subscription request to the server, it provides the specifics of the data it’s interested in. This is done in the form of a query, similar to standard GraphQL queries, but using the subscription keyword instead of query.

The server acknowledges this subscription and keeps track of the client’s interest. Whenever the relevant data changes, the server prepares a response (just like it would for a regular query) and pushes this data to the client.

Pros and Cons of GraphQL Subscriptions

The key advantage of GraphQL Subscriptions is the real-time, two-way communication between the client and the server, providing the client with immediate data updates. Moreover, like other GraphQL operations, subscriptions are flexible; clients can specify exactly what data they need updates about, reducing unnecessary network traffic.

Additionally, GraphQL Subscriptions follow the GraphQL specification, ensuring predictability and consistency across different implementations.

However, implementing GraphQL Subscriptions can be complex. It requires maintaining a persistent connection between the client and the server, typically using WebSockets. The server also needs to track all active subscriptions and their associated clients, which can be resource-intensive.

Best Practices for GraphQL Subscriptions

When implementing GraphQL Subscriptions, keep the following best practices in mind:

  1. Use For The Right Use Cases: Subscriptions are best suited for real-time updates. For requests that don’t require instant updates, traditional GraphQL queries or mutations are more appropriate.

  2. Limit the Amount of Data: Just like with queries and mutations, it’s crucial to design your subscriptions to avoid unnecessary data in the responses. Ensure the clients ask only for the data they need.

  3. Error Handling: Implement appropriate error handling for issues such as network disruptions or data access violations.

  4. Security and Authorization: Ensure that only authenticated clients can subscribe to updates, and they can only receive updates they are authorized to access.

GraphQL Subscriptions offer an effective way to handle real-time updates in a GraphQL API. While they require careful implementation and consideration, they can provide a level of responsiveness and efficiency that’s hard to achieve with traditional REST APIs.


WebSockets provide a persistent, bi-directional communication channel between the client and the server, enabling real-time interaction. They are particularly suitable for applications that require instant, two-way communication, such as multiplayer games, real-time collaboration tools, or chat applications.

How WebSockets Work

Unlike HTTP/HTTPS, which are designed for request-response interaction, WebSockets are designed for real-time, two-way communication. The connection is initiated with a standard HTTP handshake, during which the client requests an upgrade to WebSocket communication. If the server supports this protocol and approves the request, the connection is upgraded, and the client and server can then send data both ways as “messages”.

WebSockets keep the connection open until either the client or the server decides to close it. This persistent connection allows for the immediate transmission of data in either direction, providing a real-time experience.

Pros and Cons of WebSockets

WebSockets’ primary advantage is their real-time, bi-directional communication capability. They provide a level of interaction between client and server that’s impossible with standard HTTP/HTTPS. They also use less network resources for real-time updates than repeated HTTP requests, as once the WebSocket connection is established, only message data is transmitted, without the overhead of HTTP headers.

However, WebSockets have some drawbacks. Implementing WebSockets can be complex, as handling connections and messages is more complicated than a simple request-response model. They require persistent connections, which could increase server load if not managed properly. WebSockets also bypass traditional HTTP security measures, requiring a rethinking of security, authentication, and authorization.

Best Practices for WebSockets

When working with WebSockets, consider the following best practices:

  1. Use for the Right Use Cases: WebSockets shine in scenarios that require real-time, bi-directional communication. If your application doesn’t require such interaction, other techniques might be more suitable.

  2. Fallback Mechanism: Not all clients or networks support WebSockets. Ensure you have a fallback mechanism, like long-polling or Server-Sent Events, for these scenarios.

  3. Keep Connections Brief: Although WebSockets support persistent connections, you should close connections when not in use to conserve server resources.

  4. Secure Your WebSockets: Just like with HTTP, encrypt your WebSocket connections using WSS (WebSocket Secure), especially when dealing with sensitive data.

WebSockets offer a robust solution for real-time, bi-directional communication in APIs. While they require careful implementation and management, they can provide a level of interactivity and responsiveness that is vital for many modern applications.

Server-Sent Events

Server-Sent Events (SSE) represent a standard allowing a server to push real-time updates to the client over a single, long-lived HTTP connection. This specification is perfect for situations that require near real-time updates, like live news updates, social media feeds, or live sports scores. It’s usually forgotten and developers always go for WebSockets implementations, but it’s also a good approach for web applications.

How Server-Sent Events Work

Unlike long-polling, where the client repeatedly requests updates from the server, Server-Sent Events establish a one-way communication channel from the server to the client. Once the client opens an HTTP connection, the server keeps that connection open and sends data to the client whenever new information is available.

This data is sent in a specially formatted text stream, which the client can parse and react to. Each update sent by the server triggers an event on the client-side, which can be listened to using the EventSource API in JavaScript.

Pros and Cons of Server-Sent Events

The most significant advantage of Server-Sent Events lies in its simplicity and efficiency. SSE allows for real-time data updates without requiring a complex protocol like WebSockets or extensive server resources, like long-polling. Furthermore, SSE is designed to automatically reestablish a connection if it gets closed, and can even resend missed events, providing a resilient real-time communication channel.

However, Server-Sent Events are not without their limitations. SSE is a one-way communication channel—from the server to the client—which makes it less suited to use cases that require instant bi-directional communication. Additionally, while most modern browsers support SSE, Internet Explorer and older versions of other browsers do not, which may limit its application depending on your user base.

Best Practices for Server-Sent Events

When working with Server-Sent Events, keep the following best practices in mind:

  1. Use for Appropriate Use Cases: Server-Sent Events work best for applications that need server-to-client communication. If your application requires frequent client-to-server communication, consider using WebSockets or another bi-directional protocol.

  2. Error Handling: Implement proper error handling mechanisms. Even though SSE will automatically try to reconnect, you should handle scenarios where the connection cannot be reestablished.

  3. Handle Reconnections Correctly: Make use of the reconnection features of SSE. You can specify a reconnection time and identify where to resume updates if the connection drops.

  4. Heartbeats: Since proxies and firewalls may close idle connections, sending “heartbeat” messages can be a good practice to keep the connection open.

Server-Sent Events provide a simple and efficient method for real-time, one-way communication from the server to the client. While it’s not suitable for every use case, SSE is a powerful tool for developers to have in their asynchronous operations toolkit.

Message Queuing

In the world of distributed systems, Message Queuing is a well-established pattern for handling asynchronous operations. With its ability to decouple producers (senders) and consumers (receivers) of a message, it fits perfectly into scenarios where we need to perform time-consuming tasks without holding up the client.

How Message Queuing Works

In the context of a REST API, when a client initiates a request that may take a significant amount of time to process, the server wraps the task details in a message and puts it into a queue, thus achieving immediate return. This message queue acts as a buffer holding the messages until they are processed.

Workers, running separately from the main server process, continuously monitor the queue and pick up messages for processing as they become available. Once the task encapsulated in the message is completed, the result can be sent back to the client using any of the methods we’ve discussed, like polling, webhooks, or Server-Sent Events.

Popular message queuing systems include RabbitMQ, Apache Kafka, Amazon SQS, and Google Cloud Pub/Sub, each offering different features, guarantees, and trade-offs.

Pros and Cons of Message Queuing

One of the primary benefits of using message queues is the ability to handle varying loads. By acting as a buffer, they help manage tasks during peak times, ensuring that no request is dropped due to heavy traffic.

Message Queuing also brings in fault tolerance. If a worker fails during the processing, the task can be returned to the queue and picked up by another worker. Similarly, if a server fails, the messages remain in the queue, ready to be processed when the server is back online.

However, implementing a message queuing system introduces additional complexity into your system architecture. It requires managing the message queue service and ensuring its availability and reliability. Message ordering can also be a challenge in certain systems.

Best Practices for Message Queuing

If you decide to use a message queuing system for handling asynchronous operations, here are some best practices:

  1. Message Durability: Make sure your queue is durable, meaning it won’t lose messages if the queuing service crashes.

  2. Acknowledgments: Consider using acknowledgments to confirm that a message has been received and processed successfully.

  3. Dead Letter Queues: Implement dead letter queues to handle messages that can’t be processed correctly.

  4. Monitoring: Monitor queue length, processing times, and failures to detect and diagnose issues.

In conclusion, message queuing is a powerful pattern for handling asynchronous operations in REST APIs. It provides load balancing, fault tolerance, and scalability, making it a strong choice for heavy-duty or mission-critical applications.

Security Considerations for Asynchronous APIs

Asynchronous operations in APIs, while providing substantial advantages, do introduce unique security challenges that must be addressed. These considerations range from protecting the data in transit and ensuring its integrity, to access controls and avoiding Denial-of-Service (DoS) attacks. It could be also attached to the approach used (this text does not exaustively cover all possibilities related to each apporach, but gives an insight about some commom security considerations). Security is a critical aspect that must be baked into the design of an asynchronous API. It’s not an afterthought but a crucial part of the development process. By considering the unique security implications of the various approaches to handling asynchronous operations, we can build APIs that are not only performant and scalable, but also secure.

Data Security

In all the approaches discussed above, the data must often travel through untrusted networks, exposing it to potential eavesdropping or tampering. Using HTTPS (HTTP over SSL/TLS) can ensure the confidentiality and integrity of the data during transit.

Access Control

The API should ensure that the client making the request is authorized to initiate the operation and retrieve the results. This control is critical in cases like webhooks and Server-Sent Events, where the server pushes data to the client or another server. Access tokens or API keys are typically used for this purpose.

Replay Attacks

Replay attacks are a threat where an attacker intercepts a valid data transmission and fraudulently delays or repeats it. To protect against such attacks, APIs can implement timestamping, sequential nonces, or one-time tokens.

Denial-of-Service (DoS) Attacks

Asynchronous APIs can be vulnerable to DoS attacks, where an attacker overwhelms the system with a large number of requests, aiming to make it unavailable to legitimate users. Rate limiting and request throttling can help mitigate such attacks.

Securing Long-Polling and WebSockets

Long-polling and WebSockets involve keeping connections open for extended periods, which could potentially be exploited by attackers. It’s important to manage and close idle connections and ensure that these technologies are securely configured.

Securing Message Queues

When using message queues, it’s vital to ensure that only authorized services can access the queues. The queues themselves should be protected, and the messages within them should be encrypted. In addition, measures should be taken to ensure the integrity of the messages, such as using message signing.

Securing GraphQL Subscriptions

Just like with GraphQL queries and mutations, subscriptions need careful consideration regarding authorization. Only authenticated clients should be allowed to subscribe, and they should only receive data they are permitted to access.

The Bottom Line: Choosing the Right Approach

Handling asynchronous operations is a common necessity in modern API development. As we’ve seen, there are several approaches available - long-polling, webhooks, Server-Sent Events, GraphQL Subscriptions, and Message Queuing - each with their own strengths and weaknesses. Choosing the right approach largely depends on the specific requirements of your application.

Long-Polling is a relatively straightforward technique that simulates real-time communication by keeping the connection open until the server has data to send. It’s easy to implement and doesn’t require any specific protocol or persistent connection. However, it can create heavy loads on the server, especially if there are many clients or if the wait times are long.

Webhooks are great for scenarios where the client can afford to receive updates at irregular intervals and doesn’t require immediate notification of changes. They allow the server to push data to the client as and when it’s available, minimizing resource usage. However, they can be more complex to implement and maintain, and security is a major consideration.

Server-Sent Events (SSE) and WebSockets provide a communication channel from the server to the client, making them perfect for sending real-time updates. Nowadays supported by most of the browsers. They can provide a great and flexible solution for server and client data communication. SSEs is a bit less flexible due to their one channel and not so used and hyped solution, but still a good solution. A note about the resources usage, is good to remember that both keep a persistent connection.

GraphQL Subscriptions offer a solution for real-time updates within the GraphQL ecosystem. If you’re already using GraphQL, subscriptions can be a powerful way to add real-time functionality to your API. However, they require a persistent connection, usually via WebSockets, and can be complex to set up and manage.

Finally, Message Queuing systems are a robust choice for managing asynchronous tasks in large, distributed systems. They decouple the producers and consumers of messages, providing fault tolerance and load balancing. However, they introduce additional components into your system and can be complex to manage.

Choosing the right approach for your asynchronous API operations will ultimately depend on your specific use case, the real-time requirements of your application, the resources you have at your disposal, and the trade-offs you are willing to make. Remember that these strategies can also be combined in a single application to fit various needs.

As with all things in software development, the best solution is often found not in selecting the most popular or modern approach, but in understanding the problem at hand and applying the right tool for the job.