Apps Development, AWS, Cloud Computing

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Enhanced Timeout Limits for Amazon API Gateway: A Game-Changer for Long-Running Integrations

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In the ever-evolving world of cloud computing, Amazon Web Services (AWS) continues to introduce enhancements that cater to the diverse needs of its users. AWS has announced a significant update to Amazon API Gateway, allowing the integration timeout limit to extend beyond the previous 29-second restriction. This change, which extends the timeout from 29 seconds, opens up new possibilities for developers and architects who require extended processing times for their long running computations or data processing.

Amazon API Gateway

Amazon API Gateway is a fully managed service that simplifies the process of creating, deploying, and managing APIs at any scale.

It acts as the gateway between your application’s frontend and your backend services, handling tasks such as authentication, traffic management, and monitoring. With API Gateway, you can create RESTful APIs and WebSocket APIs, facilitating real-time two-way communication for various applications.

It supports a wide range of workloads, including serverless applications, web applications, and containerized workloads.

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Changes of Timeout Limit

One of the fundamental aspects of API Gateway is its ability to integrate with various backend services, including AWS Lambda functions, HTTP endpoints, and even external third-party services. However, The integration timeout setting plays a crucial role in determining the maximum time that API Gateway will wait for a response from the backend before considering the request as timed out or failed.

Earlier maximum timeout limit was set at 29 seconds which was in many use cases insufficient for more complex or long-running backend operations.


  • Support for Complex Use Cases: Applications involving Generative AI, large data processing, and other resource-intensive tasks can now operate seamlessly. For instance, Generative AI use cases with Large Language Models (LLMs) often require extended processing times, making this update highly beneficial.
  • Improved User Experience: By accommodating longer processing times, APIs can provide more comprehensive responses, improving the overall user experience. This is particularly important for applications where incomplete or timed-out responses could lead to user frustration or system inefficiencies.
  • Enhanced Flexibility: Developers have greater control over their API configurations, allowing for more tailored solutions to meet specific business needs. This flexibility can lead to more innovative and efficient applications.

Implementation and Considerations

To take advantage of the increased timeout limit, users may need to adjust their account-level throttle quota limit. This ensures that the increased processing time does not negatively impact the overall performance and reliability of the API. Additionally, while the increased timeout limit is available at no additional cost, it is important to monitor the performance and cost implications of extended processing times.


The ability to increase the integration timeout limit in Amazon API Gateway marks a significant enhancement for developers and businesses utilizing AWS. By accommodating longer processing times, AWS has expanded the potential use cases for API Gateway, enabling more complex and resource-intensive applications. This update not only improves the flexibility and functionality of APIs but also supports the development of innovative solutions across various industries.

For more details on this update, visit the official AWS announcement.

Drop a query if you have any questions regarding Amazon API Gateway and we will get back to you quickly.

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WRITTEN BY Nisarg Desai

Nisarg Desai is a certified Lead Full Stack Developer and is heading the Consulting- Development vertical at CloudThat. With over 5 years of industry experience, Nisarg has led many successful development projects for both internal and external clients. He has led the team for development of Intelligent Quarterly Remuneration System (iQRS), Intelligent Training Execution and Analytics System (iTEAs), and Cloud Cleaner projects among many others.



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