Understanding Sisense REST API request rate limits

Understanding Sisense REST API request rate limits

Introduction

This article provides guidance on handling request rate limits when using the Sisense REST API. Users often need to perform operations such as creating multiple users or assigning permissions, which raises concerns about how many requests the Sisense API can handle concurrently without issue.

Since Sisense deployments can vary significantly based on infrastructure, usage, and configuration, understanding how to manage request rates effectively is key to ensuring system stability and performance.

Understanding API Rate limits

Sisense does not publicly define strict rate limits (e.g., a maximum number of requests per second) for its REST API. However, it would be best to proceed with care during bulk operations, particularly when using write-heavy or resource-intensive endpoints—to help prevent performance issues or API errors.

Important:

The guidance provided in this article is based on practical experience. It is not an official Sisense-enforced limit, and actual safe limits may vary per environment.

Recommended practices

1. Estimate Safe Throughput

As a general guideline:

• Write-heavy endpoints (e.g., /users, /elasticubes/security) can typically support a rate of 5–10 requests per second in well-provisioned environments.
  
• Higher volumes are recommended to be batched, and requests spaced with short delays (e.g., 100–200ms intervals) to prevent overloading.
  

NOTE: Not all endpoints behave the same. Operations involving Elasticube builds or data model changes are usually more resource-intensive than operations on users.

2. Conduct controlled testing

Each Sisense environment is unique in its configuration and data workload. Before running any large-scale API operations:

• Simulate your use case in a staging or low-traffic environment.
  
• Monitor system behavior: CPU usage, memory, API latency, and error responses.
  
• Adjust your API pacing based on performance indicators.
  

3. Implement error handling and retry logic

Common errors from overloading the API include:

• 429 Too Many Requests: Indicates that the system is receiving more requests than it can handle.
  
• 500 Internal Server Error / 504 Gateway Timeout: Can result from system resource exhaustion.
  

To manage this:

• Implement exponential backoff when retrying failed requests. See below reference for more details.
  
• Log and analyze errors to detect patterns in overload or timeout conditions.
  
• Ensure your automation scripts or middleware can gracefully pause and resume batches as needed.
  

4. Monitor and adjust dynamically

During bulk operations or automation runs, continuously monitor:

• API response times
  
• Error rates
  
• System load (CPU, memory, disk I/O)
  

Based on these metrics, dynamically adjust the number of concurrent requests or introduce delays to stay within safe limits.

Applicability across Sisense REST APIs

While the 5–10 requests per second benchmark is a helpful generalization, not all endpoints share the same performance characteristics:

Always test specific endpoint behavior before bulk automation in production environments.

Conclusion

Sisense's REST API is powerful and flexible, but it’s essential to approach high-volume operations with caution. While Sisense does not enforce a fixed request rate limit, following best practices, such as limiting throughput, monitoring, and error handling, ensures robust and stable API usage.

By conducting tests in your environment and adjusting based on real-world behavior, you can confidently scale your integration or automation safely and efficiently.

References / related content

• Sisense Community - API Rate Limiting Clarification
  Sisense REST API Documentation
• Effective API Querying: Best Practices and Recommendations
• exponential backoff
• HPA was introduced to help with scaling challenges

Disclaimer: This post outlines a potential custom workaround for a specific use case or provides instructions regarding a specific task. The solution may not work in all scenarios or Sisense versions, so we strongly recommend testing it in your environment before