As small as the concurrent reading volume and online chat function of the portal website, as large as the number of concurrent purchases of the 12306 official website during the Spring Festival travel period, the concurrent transaction volume during e-commerce major promotions such as Double Eleven, e-commerce spikes, and the concurrent volume of WeChat red envelopes on New Year’s Eve ...These all reflect the rigid requirements of high concurrency technology.

After the Double Eleven and other e-commerce promotion events, in addition to the record-breaking transactions, another very eye-catching feature is the amount of concurrency processed by the major e-commerce platforms at peak times. Obviously, the ability to master high concurrency reflects the technical level of an e-commerce platform to a certain extent. We can also often see that some domestic and foreign Internet companies frequently launch various high-concurrency new technology frameworks. It can be seen that the ultimate pursuit of high concurrency has always been the research direction of major Internet companies that continue to challenge and enjoy. In fact, since the birth of software technology, developers have never stopped studying high-concurrency technology. With the advent of the data age, how to deal with massive data is also one of the research directions of high concurrency.

"High concurrency technology" is a broad concept, refers to an efficient solution to achieve concurrency requirements, is the name of the technical field, can include architecture design, SOA (service-oriented architecture), distributed, microservices, data Many subdivided knowledge of processing, multithreading, etc.

Now briefly introduce how to handle high concurrent requests from a technical point of view. For example, the spike activity of an e-commerce company will bring about very large high concurrent requests. In order to avoid excessive high concurrent requests from overwhelming the e-commerce server, all concurrent requests need to be processed. Generally speaking, you can first intercept illegal user requests by means of verification codes and IP restrictions, and then set up a service cluster to diverge legitimate concurrent requests. After that, you can also set service parameters such as the maximum number of connections and the maximum number of concurrency within the server, and use the message queue to cut peaks and fill valleys for massive concurrent requests. In addition, in order to allow the database to handle high concurrent requests stably, it is necessary to reduce the number of user requests to the database through caching middleware, and reduce the access pressure on the system during high concurrency peaks through strategies such as service degradation. Finally, in order to still ensure data security in extreme cases, it is also necessary to build a database cluster and set up a reasonable isolation mechanism. It can be seen that high concurrency runs through all aspects of project design, from gateway to server development to data design and other links need to consider countermeasures in high concurrency situations. The technical knowledge explained in this book is the solution under this high concurrency environment.

Today I want to share this learning resource is the "Billion-level Concurrency Tuning Manual", this learning resource is compiled under the background of Ali's billion-level architecture, and there are many things that everyone can learn from! Below I will take a screenshot silently, and the full version is free to get at the end of the article, just scan the code to get it!

Basics