10 API Polling Best Practices

API polling is a powerful tool for developers to access data from external sources. It allows developers to query an API at regular intervals to check for new data or changes in existing data. This can be used to create real-time applications or to keep track of changes in data over time.

However, API polling can be a tricky process to get right. To ensure that your API polling is efficient and effective, it’s important to follow best practices. In this article, we’ll discuss 10 API polling best practices that you should follow.

1. Use HTTP headers to control the polling frequency

When you use HTTP headers to control the polling frequency, it allows your API to respond more quickly and efficiently. This is because the server can set a limit on how often requests are made, which helps reduce the amount of unnecessary traffic that could potentially overload the system.

Additionally, using HTTP headers also makes it easier for developers to understand what’s going on with their API calls. By setting specific parameters in the header, they can easily see when a request was sent, how long it took to process, and any other relevant information. This makes debugging much simpler and faster.

2. Keep your polling interval as high as possible

API polling can be resource-intensive, and if you’re making too many requests in a short period of time, it can cause performance issues. Additionally, some APIs have rate limits that restrict the number of requests you can make within a certain timeframe. If you exceed these limits, your API calls will fail.

To avoid these problems, set your polling interval as high as possible while still ensuring that you get the data you need. This way, you’ll reduce the load on your system and ensure that your API calls are successful.

3. Don’t poll more than once per second

When you poll an API more than once per second, it can cause the server to become overloaded and slow down. This can lead to poor performance for other users of the API, as well as your own application. Additionally, if you are polling too frequently, you may be in violation of the terms of service of the API provider.

To ensure that you don’t overload the server, make sure to set a reasonable polling interval. For most applications, this should be no less than one minute. If you need faster updates, consider using webhooks or streaming APIs instead.

4. Use a random delay on each request

When you make multiple requests to an API in quick succession, it can put a strain on the server and cause performance issues. To avoid this, you should add a random delay between each request so that they are spread out over time. This will help ensure that your requests don’t overwhelm the server and reduce the chances of getting rate-limited or blocked.

5. Avoid polling at fixed intervals

When you poll at fixed intervals, your API requests are sent out in a predictable pattern. This makes it easier for malicious actors to detect and exploit the patterns in your API traffic. It also increases the chances of overloading your server with too many requests at once.

Instead, use randomization techniques such as jittering or exponential backoff when polling your APIs. This will help spread out your requests more evenly and reduce the risk of overloads. Additionally, make sure to set reasonable limits on how often you can poll an API endpoint.

6. Implement exponential backoff

Exponential backoff is a technique used to reduce the rate of requests sent to an API. It works by increasing the amount of time between each request, starting with a short delay and gradually increasing it until the desired rate is achieved. This helps prevent overloading the API server with too many requests at once, which can cause performance issues or even lead to errors.

By implementing exponential backoff, you can ensure that your API polling is done in a responsible manner, while still getting the data you need in a timely fashion.

7. Consider using webhooks instead of polling

Webhooks are a way for an API to send real-time notifications when something changes. This means that instead of your application having to constantly poll the API, it can just wait for the webhook notification and then take action.

This is much more efficient than polling because you don’t have to waste resources on unnecessary requests. It also makes your application more responsive since it will be able to react to events as soon as they happen. Finally, it’s easier to maintain since you don’t have to worry about setting up and managing a polling schedule.

8. Monitor API usage and enforce rate limits

API rate limits are designed to protect the API from being overloaded with requests. If too many requests come in at once, it can cause performance issues and even crash the system. By monitoring usage and enforcing rate limits, you can ensure that your API is running smoothly and efficiently.

You should also consider setting up alerts so that you know when a certain threshold of requests has been reached. This way, you can take action before any problems arise. Additionally, you may want to set up different rate limits for different types of users or applications. That way, you can make sure that everyone gets fair access to the API.

9. Provide an endpoint for checking changes

When you provide an endpoint for checking changes, it allows your users to check if there have been any updates since the last time they checked. This is especially useful when dealing with large datasets that may take a long time to download or process. By providing this endpoint, users can quickly and easily determine if anything has changed since their last request, saving them both time and resources.

Additionally, having an endpoint for checking changes also helps reduce unnecessary API requests. If nothing has changed since the user’s last request, then they don’t need to make another one. This reduces strain on your servers and ensures that your API remains responsive and reliable.

10. Make sure you have enough capacity

If you don’t have enough capacity, your API requests will start to back up and slow down. This can lead to timeouts or errors in the response from the server, which can cause problems for your application.

To ensure that you have enough capacity, it’s important to monitor your API usage closely. You should also consider setting up alerts so that you know when your API is reaching its limits. Additionally, if possible, try to use caching techniques to reduce the number of API calls you need to make. Finally, be sure to scale up your infrastructure as needed to handle increased traffic.