Hello everyone, I am your Xiaomi! Today I want to talk to you about a challenging and creative topic: how to solve the problem of instantaneous large traffic and high concurrency? Presumably many friends have encountered this headache in the development process. Don't worry, I'm here to share my experience with you, so that you can easily handle high concurrency without fear of traffic storms!

understand the problem

First, we need to have a clear understanding of the problem. Instantaneous large traffic and high concurrency actually means that the system needs to process a large number of requests in a short period of time. Typical scenarios include seckill activities, popular article releases, etc. Faced with such a scenario, the system often suffers from increased delays, accumulation of requests, and even crashes. So, how to effectively solve these problems?

optimize database

The database is often one of the bottlenecks of system performance. In high concurrency scenarios, the read and write pressure on the database will increase rapidly. In order to effectively optimize database performance, we can adopt the following strategies:

Database index optimization: Ensure that appropriate indexes are established on the key fields of the database table to improve query efficiency.

Separation of reading and writing: Separate the reading and writing operations of the database to improve the overall concurrency of the system.

Application of caching technology: Use caching to reduce the pressure on the database, such as using Redis to cache popular data to speed up read operations.

Horizontal expansion

When the concurrency is high, a single server may not be able to withstand the huge request pressure. At this time, the method of horizontal expansion can effectively increase the processing capacity of the system:

• Load balancing: Use a load balancer to distribute requests to multiple servers to prevent a server from becoming a performance bottleneck.
• Distributed Architecture: Split the system into multiple service modules and deploy them on different servers to improve the overall concurrency capability of the system.

asynchronous processing

In high-concurrency scenarios, synchronous processing of requests often leads to request accumulation, which in turn affects the response speed of the system. Using asynchronous processing can effectively avoid this problem:

• Message Queue: Convert requests into messages, and perform asynchronous processing through message queues to improve system throughput.
• Delay processing: For some non-critical operations, processing can be delayed to reduce the pressure on the system.

Current limiting strategy

In order to protect the system from being overwhelmed by too many requests, we can introduce a throttling strategy to control the request volume of the system:

• Token Bucket Algorithm: Realize the restriction on requests to ensure that the system can only process an acceptable number of requests per unit time.
• IP current limiting: Limit requests for the same IP to avoid malicious requests from occupying resources.

emergency response

Even with adequate preparations, unexpected situations may still occur in high-concurrency scenarios. At this time, we need to take emergency measures:

• Automatic downgrade: When the system pressure is too high, the priority of some functions can be automatically reduced to ensure the normal operation of core functions.
• Emergency expansion: When large-scale requests occur, server resources can be temporarily increased to ensure system stability.

Continuous optimization

Solving the high concurrency problem does not mean relaxing, continuous optimization is the key to keep the system stable:

• Monitoring and early warning: Set up a monitoring system to track system performance in real time, and give an early warning in case of abnormality.
• Performance testing: Regularly conduct system performance testing to find problems and continue to optimize.

END

Instantaneous large traffic and high concurrency is a challenging but fun problem. By optimizing the database, horizontal expansion, asynchronous processing, current limiting strategy and other means, we can show our talents in this field and create a stable and efficient system. In the process of solving problems, it is not only technology, but also a kind of collision and innovation of thinking. I hope that today's sharing can help you who are facing this problem, and let you sail to a broader blue ocean in the ocean of technology!