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This article introduces how Nginx performance tuning solves C10K problems. The content is very detailed. Interested friends can refer to it for reference. I hope it can help you.

The technical director of the company recently asked our group of developers to design an architecture problem. The title is like this: There is a check-in function that needs to record the check-in of each user every day of the year. Assuming that the number of users is in the tens of millions, even billions, how to design.

After thinking about this problem, my design solution is as follows:

Layer 1: Through DNS, multiple IPs are bound to the same domain name, and Load Balancer is performed on DNS.

Layer 2: Central Nginx cluster, after DNS Load Balancer, secondary Nginx Load Balancer (Nginx configuration needs to be adjusted according to server configuration, such as number of connections, number of processes, etc.);

Layer 3: The web layer deploys applications on multiple nodes.

The fourth layer: message engine layer, write the upper layer data into the message engine, the consumer side asynchronous data storage, it is recommended to use kafka, throughput is large.

The fifth layer: database layer, the amount of data is huge, the traditional relational database is not suitable, even through the horizontal sub-database table, by date or userid sub-database, it is difficult to solve the storage and cross-database query problem. Consider using MongoDB or Big Data technologies (HDFS and HBASE) to store check-in data.

I don't know if it makes sense, but the overall design concept is: Load Balancer + Asynchronous. Nginx and Linux kernels should also be optimized to withstand greater stress.

About Nginx performance tuning how to solve the C10K problem is shared here, I hope the above content can be of some help to everyone, you can learn more knowledge. If you think the article is good, you can share it so that more people can see it.

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