How much qps is considered high concurrency?

Four angles of high concurrency

To say that concurrency does not improve usability is to be a rogue. This issue can be discussed from four perspectives.

First of all, the stateless front-end machine is not enough to carry the request traffic and needs to be expanded horizontally. Generally, the QPS is thousands of levels. Then the relational database cannot handle the read or write peaks, and requires horizontal expansion of the database or the introduction of NoSQL, which is generally thousands to ten thousand levels. After that, nosql cannot be hosted on a single machine, and nosql needs to be horizontally expanded, usually from 100,000 to one million QPS. Finally, it is difficult to simply scale NoSQL horizontally. For example, Weibo has introduced a multi-level cache architecture. This architecture can generally handle millions to tens of millions of QPS access to NoSQL. Of course, user-facing interface requests generally do not reach this level of magnitude. The increase in QPS is mostly due to the pressure caused by read amplification, which is also considered by high-concurrency architecture.

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PV and QPS

For example, Weibo’s system with more than 100 million PVs per day generally only has 1500QPS and a peak of 5000QPS.

For example, someone said:

2C4G machine is generally 1000QPS per machine.

8C8G machine can withstand 7000QPS alone.

Written at the back

The specific QPS is closely related to the business. The read-only interface reads the cache and puts pressure on the cache. 3000 per machine is no problem. Write requests of 1000 are also normal. , it is also more complicated and may only be a few hundred QPS.

So QPS is closely related to business scenarios and designs. For example, QPS can be improved through browser local caching, using cache to query hotspot data, and writing transaction MQ asynchronous processing.

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