Alibaba high-concurrency business spike system landing actual document, a large spike scenario has been implemented

Foreword:

High concurrency is an experience that almost every programmer wants to have. The reason is simple: as the traffic becomes larger, we will encounter various technical problems, such as interface response timeout, increased CPU load, frequent GC, deadlock, large data storage, etc. These problems can promote us in Continuous improvement in technical depth.
We know that high concurrency represents large traffic, and the charm of high-concurrency system design lies in our ability to design clever solutions with our own ingenuity to resist the impact of huge traffic and bring users a better experience. These solutions seem to be able to manipulate the flow, making the flow more smoothly processed by the services and components in the system.

What kind of system is considered a highly concurrent system? Today, let's take a look at the architecture of a typical spike system in the high-concurrency business scenario of Ali P9 technology boss.

After you need to get the trouble-like like article of "High Concurrency Business System Design and Bottleneck Breakthrough" compiled by Ali boss, then click here, the code: CSDN .

• 1.1 Highly concurrent system: what is its general design method
• 1.2 Architecture layering: Why do we have to do this?
• 1.3 System design goal (1): How to improve system performance?
• 1.4 System design goal (2): How to achieve high availability of the system?
• 1.5 System design goal (3): How to make the system easy to expand?
• 1.6 The first phase of the interview site: When asked about the principle of component implementation, is the interviewer making things difficult for you?

database

• 2.1 Pooling technology: How to reduce the performance loss of frequently creating database connections?
• 2.2 Database optimization plan (1): How to separate master and slave when query requests increase?
• 2.3 Database optimization plan (2): How to implement database and table splitting when the amount of written data increases?
• 2.4 Number issuer: How to ensure the global uniqueness of ID after sub-database and sub-table?
• 2.5 NoSQL: How do databases and NoSQL complement each other in high concurrency scenarios?

Cache

• 3.1 Cache: After the database becomes the bottleneck, how to speed up the query of dynamic data?
• 3.2 The usage posture of the cache (1): How to choose the read and write strategy of the cache?
• 3.3 The usage posture of cache (2): How to make cache highly available?
• 3.4 Cache usage posture (3): What should I do if the cache penetrates?
• 3.5 CDN: How to accelerate static resources?

message queue

• 4.1 Message Queue: How to handle tens of thousands of order requests per second during the spike?
• 4.2 Message Delivery: How to ensure that the message is only consumed once?
• 4.3 Message queue: How to reduce the delay of messages in the message queue system?
• 4.4 The second phase of the interview site: When asked about the project experience, what exactly does the interviewer want to know?

Distributed service

• 5.1 System architecture: Will the system with 10,000 requests per second be service-oriented?
• 5.2 Microservice architecture: After microservices, how to transform the system architecture?
• 5.3 RPC framework: How to implement millisecond-level service calls under 100,000 QPS?
• 5.4 Registration Center: How to address the distributed system?
• 5.5 Distributed Trace: How to troubleshoot slow requests that span dozens of distributed components?
• 5.6 Load balancing: How to improve the horizontal expansion capability of the system?
• 5.7 API Gateway: How to do the facade of the system?
• 5.8 Multi-room deployment: How to do cross-regional distributed systems?
• 5.9 Service Mesh: How to shield the service governance details of the service system?

maintain

• 6.1 Adding eyes to the system: how to do server-side monitoring?
• 6.2 Application performance management: How should the user experience be monitored?
• 6.3 Stress test: How to design a full-link stress test platform?
• 6.4 Configuration management: How to manage thousands of configuration items?
• 6.5 Degraded fusing: How to shield the effects of non-core system failures?
• 6.6 Flow Control: How do we manipulate flow in a highly concurrent system?
• 6.7 The third session of the interview site: How do you prepare for a technical interview?

Actual combat

• 7.1 Counting system design (1): How to do counters facing massive data?
• 7.2 Counting system design (2): How to design an unread system under 500,000 QPS?
• 7.3 Information flow design (1): How to do the push mode of the general information flow system?
• 7.4 Information flow design (2): How to do the pull mode of the general information flow system?

High Concurrency is one of the factors that must be considered in the design of Internet distributed system architecture. It usually refers to the design to ensure that the system can process many requests in parallel at the same time.

In fact, high concurrency experience is a time to test a programmer or an architect's foundation and ability

Therefore, we must do a good job of high concurrency, and if conditions permit, we must have a lot of enthusiasm for the technology, from the bottom to the top, from the business logic, from the various components, from the system to make various optimizations and breakthroughs. , Forcing you to learn more about the underlying knowledge and move forward without shrinking.

You need to get the trouble of "High Concurrency Business System Design Landing and Bottleneck Breakthrough" compiled by Ali boss. After you like this article, then click here, the code: CSDN .