I’m using AWS API Gateway along with Lambda, but I can only handle around 3,000 requests per second due to apparent limitations. I wonder if there is another service I should try instead of Lambda. I also question whether API Gateway is part of the problem. I enjoy its seamless integration with other AWS tools, but I’m willing to explore alternatives if necessary. Any advice or suggestions would be really appreciated.
Based on my experience managing high throughput workloads, I’ve found that while API Gateway and Lambda work well for many applications, moving certain components to container-based solutions has been key when scaling demands become extreme. In my case, using a dedicated container orchestration platform allowed for customized scaling policies and more granular resource management. Transitioning to such an architecture did require extra setup and maintenance but delivered superior performance under high load, ultimately providing the flexibility needed for high concurrency demands.
After working on a project that demanded continuous high throughput, I managed to improve performance by moving away from Lambda and embracing containerized solutions on AWS Fargate. This implementation allowed for better control over resource allocation and more predictable scaling compared to the traditional API Gateway and Lambda combo. Although shift required careful infrastructure tuning and improved monitoring practices, the benefits have been significant, particularly regarding latency reduction and handling unexpected traffic spikes. This approach proved to be a viable alternative for scenarios requiring a sustained high request rate.
hey, try looking into k8s or ecs setups on dedicated instnces. i’ve seen some solid performance improvements with more fine-tuned autoscaling. it can get a bit tricky, but it might just be what u need for handling extreme load.
In my personal experience, transitioning away from a fully managed API Gateway and Lambda setup for extreme throughput requirements has led me to explore more customizable architectures. I moved to a configuration that includes a dedicated reverse proxy layer using NGINX in combination with a container-based backend. This allowed me to precisely manage connections and implement more efficient caching and rate limiting strategies. Managing a self-hosted solution demanded more hands-on monitoring and tuning, but the control over network settings and system resources significantly improved request handling capacity. The increased flexibility in scaling and optimization ultimately provided much more stable performance under persistent high loads compared to traditional serverless approaches.