Resolving `Significant Performance Loss in Laravel 9 with Swoole on Docker

Discover how to tackle significant performance issues in your Laravel 9 and Swoole application running in Docker, specifically on Rocky Linux 9. Learn about optimizing custom network configurations and routing.
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This video is based on the question https://stackoverflow.com/q/77155292/ asked by the user 'Virendra' ( https://stackoverflow.com/u/12168279/ ) and on the answer https://stackoverflow.com/a/77157494/ provided by the user 'Virendra' ( https://stackoverflow.com/u/12168279/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Troubleshooting Performance Loss in Laravel 9 with Swoole on Docker

If you've been developing with Laravel 9 and Swoole while containerizing your applications with Docker on Rocky Linux 9, you may have encountered a critical issue. Many users have reported observing significant performance degradations when using custom Docker networks, drastically affecting response times for API calls. In this guide, we will explore the problem and provide a comprehensive solution to help you optimize your setup.

The Problem

As you might have experienced, running a Laravel application integrated with Swoole in Docker can deliver excellent performance under the right conditions. For instance, the original API call latency can be around 63ms when using network_mode: host. However, once the application is switched to custom Docker networks like backend, frontend, and mongodb, performance takes a nosedive, with latency spiking to over 6000ms.

This sudden drop in performance is a challenge, particularly for microservices architectures that rely heavily on efficient inter-service communication. Understanding the cause of this issue is essential to maintain optimal application performance.

Setup Details

To give context to this performance issue, consider the following setup:

Host OS: Rocky Linux 9

Laravel Version: 9

Swoole Version: 4.8.4

Docker Networks: backend, frontend, mongodb

Tech Stack:

Backend Microservices: Laravel 9

Frontend: ReactJS

Database: MongoDB

Cache: Redis

Web Server for Frontend: Nginx

Backend Server: Swoole (each application runs in its own container)

Observations

Your observation of performance differences becomes evident:

With network_mode: host, the API call latency is roughly 63ms.

With Custom Docker Networks, the same calls are taking over 6000ms.

With various configurations checked – Docker host resources, volume mounts, Swoole and Laravel settings, and different Docker network configurations – you might find yourself perplexed by this performance difference.

Solution: Update Your Service Configuration

To optimize performance, one effective strategy is to modify the .env settings responsible for routing. Here’s how to do it:

Service Name to IP Update:

If you are currently using the service name in your microservices to forward API requests, consider changing this to use the IPv4 gateway of your external network (e.g., 172.20.0.1).

This adjustment could significantly improve inter-container communication speed and thus tackle the performance degradation you observed.

Example Update Steps:

Open your .env file in your microservice directory.

Replace references like SERVICE_NAME with the specific IPv4 gateway address mentioned above.

Test the Changes:

After updating the configurations, test the performance of your API calls again to see if latency returns to an acceptable level.

Conclusion

By simply updating your service routing from service names to using the external network's IPv4 gateway, you can potentially resolve significant performance loss in your Laravel 9 application running with Swoole over Docker on Rocky Linux 9.

As with all optimizations, be sure to monitor the performance after making changes, ensuring that your application remains responsive under expected loads. Remember, proper configuration is key to building scalable and efficient microservices.

If you face any further issues, do not hesitate to share your experiences. We'd love to help you through your troubleshooting journey!

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