Overview of API Rate Limits

Rate limiting is a crucial aspect of API management, as it ensures the stability and performance of API endpoints by preventing abuse or overconsumption of resources.

Paylocity API Rate Limiting Strategy

To ensure optimal performance and maintain system integrity, each API endpoint has a designated rate limit that controls the number of requests an API user can make within a specified time period. When an API user exceeds this rate limit, they will receive an HTTP status code 429 - "Too Many Requests", indicating that their request rate has surpassed the allowed threshold.

Our strategy is to establish healthy rate limits that allow clients and partners to operate without hindrance while also balancing the system's performance for the large number of users accessing our platform. This approach ensures that we can provide a stable and efficient service at scale without compromising functionality.

To avoid encountering the 429 error, we strongly recommend designing your API usage to stay within the specified rate limits. Implementing rate-limiting logic, retries with backoff strategies, and monitoring request frequency will help maintain efficient and uninterrupted interactions with our API.

See: API Error Handling

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Weblink API Rate Limits are different

For information regarding rate limiting related to calls made to the weblink API, please review the API specific documentation

Preventing and Handling Rate Limit Threshold Errors

To ensure seamless integration and prevent receiving a 429 error response due to exceeding rate limits, developers should implement the following strategies:

• Design Efficient Code: Optimize your code to minimize the number of API calls made within a minute, staying within the allowed limit. This can involve caching data, reducing redundant requests, and only requesting the data you need.
• Implement Rate Limiting Logic: Add logic in your code to track and limit the number of API calls made within a minute. This can be achieved using various techniques, such as token bucket algorithms or leaky bucket algorithms, depending on your specific use case.
• Handle Error Responses Gracefully: In the event that an error occurs, implement a retry mechanism in your code to pause and retry the API call later. This can involve exponential back-off algorithms to progressively increase the waiting time between retries and ensure that the API is not overwhelmed.

By following these best practices, development teams can prevent and handle rate limiting issues when building integrations using our APIs. This will help maintain the stability, reliability, and performance of both the API and the integrated applications, leading to a better user experience for our mutual customers and streamlined HR processes.