Specify the name of the shared memory zone as the first parameter, and the number of allowed connection per key as the second parameter:.
Rate limiting can be used to prevent DDoS attacks, or prevent upstream servers from being overwhelmed by too many requests at the same time. The method is based on the leaky bucket algorithm: requests arrive at the bucket at various rates and leave the bucket at fixed rate.
With this configuration, the shared memory zone one with the size of 10 megabytes is created. Thus, state information for about 16, IP addresses occupies 1 megabyte of the zone. Processing of these requests is delayed in such a way that the overall rate is not greater than specified. However, such excessive requests are still accounted in the shared memory zone and logged.
If the number of requests exceeds the specified rate and the shared memory zone becomes full, NGINX will respond with an error. As traffic tends to be bursty, returning the error in response to a client request during traffic bursts is not the best case.
With this configuration, if request rate exceeds 1 request per second, requests beyond the rate will be put into the zone one.
When the zone is full, excessive requests will be queued burst , the size of this queue is 5 requests. Request processing in the queue is delayed in such a way that the overall rate is not greater than specified. Requests above the burst limit will be rejected with the error.
If delaying of request is not desired during traffic burst, add the nodelay parameter:. With this configuration, excessive requests within the burst limit will be served immediately regardless of the specified rate , requests above the burst limit will be rejected with the error.
This value defines the maximum number of TCP sessions per worker. By increasing this value, the hope is that we can increase the capacity of each worker process.
For this first test, we will try to change this setting to and measure the impact of that change. Like the previous configuration change, in order for this adjustment to take effect we must restart the NGINX service. Once again, our parameter change has resulted in a significant increase in performance. The only way to find this out is to make the parameter change and test again. The reason this parameter is now specified is because, when adjusting the number of connections per worker, you must also adjust the open file limitations.
By setting the maximum number of connections to , we are essentially defining that every worker can open up to files. From the results of the ab test run, it seems we were able to add about requests per second. While this may not be as significant of a change as our earlier requests per second, this is still an improvement in throughput. As such, we will leave this parameter as is to move on to our next item.
When tuning NGINX or anything else for that matter, it's important to keep in mind the workload of the service being tuned. There is a set of tuning parameters that are very useful when serving static HTML. However, of those files, the cache will be invalidated if they are not accessed within 10 seconds. This means less overall work per request, which should mean a higher throughput. Let's test our theory with another run of the ab command. While this parameter might seem very useful, it is important to remember that this parameter works in our example because we are simply serving static HTML.
If we were testing an application that was serving dynamic content every time, these parameters may result in rendering errors for end users. As a result, we've gotten an increase of roughly requests per second. We did this by not only changing a few key parameters, but also experimenting with those parameters.
While this article only touched on a few key NGINX parameters, the methods used in this article to change and measure impact can be used with other common NGINX tuning parameters, such as enabling content caching and gzip compression. We'll never share your email address and you can opt out at any time, we promise.
Platform Platform. Platform Capabilities. Continuous Integration Build and test at scale Continuous Delivery Eliminate scripts and automate deployment pipelines Release Orchestration Adaptable model-driven release orchestration. Analytics A single source of truth for real-time visibility Feature Management Manage feature rollouts and effectiveness Compliance Coming Soon! Use Cases Use Cases. Use Cases. Resources Resources. Because Nginx is asynchronous , each request can be executed by the worker concurrently without blocking other requests.
Some common features seen in Nginx include: Reverse proxy with caching. Share: A reverse proxy is a service that takes a client request, sends the request to one or more proxied servers, fetches the response, and delivers the server's response to the client.
Apache is an open-source HTTP server whereas Nginx is an open-source, high-performance asynchronous web server and reverse proxy server. How many connections can Nginx handle? Category: technology and computing browsers. The default is , but most systems have enough resources to support a larger number. How can I speed up Nginx? Which is better Nginx or Apache? How much RAM does Nginx need? How many request per second can a server handle? What does Nginx mean?
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