E-commerce billion-level system architecture design notes are divided into: basic articles, database articles, cache articles, message queue articles, distributed services articles, maintenance articles, and actual combat articles. By studying this note, you can systematically learn to build a billion-level system architecture from scratch. In each of them, there are specific design and implementation notes for your reference.
Basics
01. Highly concurrent system: What is its general design method?
02. Architecture layering: why do we have to do this?
In the system from 0 to 1, in order to get the system online quickly, we usually do not consider layering. However, as the business becomes more and more complex and a large amount of code is entangled, problems such as unclear logic, interdependence of various modules, poor code scalability, and changes to one place will affect the whole body.
At this time, layering the system will be put on the agenda, so how do we layer the architecture? What is the relationship between architecture layering and high-concurrency architecture design? In this lesson, I will take you to find the answer.
03. System design goal (1): How to improve system performance?
When it comes to Internet system design, the words you may hear most are "three highs", that is, "high concurrency," "high performance," and "high availability". They are the eternal theme of Internet system architecture design. In the first two classes, I took you to understand the meaning, significance and principle of hierarchical design of high-concurrency system design. Next, I want to take you to understand the goals of high-concurrency system design as a whole, and then on this basis, enter Our topic today: How to improve the performance of the system?
04. System design goal (2): How does the system achieve high availability?
05. System design goal (3): How to make the system easy to expand?
Database articles
07. Pooling technology: How to reduce the performance loss of frequently creating database connections?
From the beginning of this section, I will use a virtual system as the main line throughout the course to explain what problems we will encounter when the system reaches a certain stage, and what solutions should be adopted to deal with it, and the response process involves Which technical points. Through this way of narration, we strive to elicit problems with cases, so that you can understand how to solve different problems when you encounter different problems. Of course, in this process, I hope you can think more and learn the knowledge you have learned. Use it in actual projects.
08. Database optimization plan (1): How to separate master and slave when query requests increase?
09. Database optimization plan (2): When the amount of written data increases, how to implement database and table splitting?
10. Number issuer: How to ensure the global uniqueness of ID after sub-database and sub-table?
11. NoSQL: How do databases and NoSQL complement each other in high concurrency scenarios?
Cache articles
12. Cache: After the database becomes the bottleneck, how to speed up the query of dynamic data?
13. Cache usage posture (1): How to choose a cache read and write strategy?
14. Cache usage posture (2): How does the cache achieve high availability?
In the previous few lessons, I took you to understand the principle, classification and use of common caches. We began to use the cache to bear most of the read pressure, thereby alleviating the query pressure of the database, and ensuring the stability of the system while improving performance. At this time, the overall architecture of your e-commerce system evolved into the following figure:
15. Cache usage posture (3): What should I do if the cache penetrates?
16. CDN: How to accelerate static resources?
Message Queue
17.Message queue: How to handle tens of thousands of order requests per second during the spike?
First of all, I will take you to understand the three goals of high-concurrency system design: performance, availability, and scalability. In terms of improving system performance, we have been focusing on system query performance. I also spent a lot of space to explain the distributed transformation of the database, the principles and use skills of various caches. The reason is that most of the scenarios we encounter are read more and write less, especially in the initial stage of a system.
18.Message delivery: how to ensure that the message is only consumed once?
19.Message queue: how to reduce the delay of messages in the message queue system?
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Distributed Service
21. System architecture: Will the system with 10,000 requests per second be service-oriented?
22. Microservice architecture: After microservices, how to transform the system architecture?
23. RPC framework: How to implement millisecond-level service calls under 100,000 QPS?
24.Registration Center: How to address the distributed system?
25. Distributed Trace: How to troubleshoot slow requests across dozens of distributed components?
26. Load balancing: how to improve the horizontal scalability of the system?
27. API Gateway: How to do the facade of the system?
So far, your vertical e-commerce system has been running for a period of time after it has been split into microservices. The scalability of the system has been greatly improved, and it has been able to smoothly pass the peak traffic.
Recently, however, you have discovered that as your e-commerce website becomes more and more well-known, the system welcomes some "uninvited customers". In the early morning, the number of search products and user interface calls in the system will rise sharply. After a period of time, it returned to normal.
28. Multi-computer room deployment: How to do cross-regional distributed systems?
29. Service Mesh: How to shield the service governance details of the service system?
Maintenance
30. Add eyes to the system: how to do server-side monitoring?
In the life cycle of a project, operation and maintenance occupies a large proportion. In terms of importance, it almost keeps pace with project development. In the process of system operation and maintenance, it is the job of every team to discover and solve problems in time. Therefore, at the beginning of your vertical e-commerce system, the operation and maintenance team must have completed basic monitoring of the machine's CPU, memory, disk, network, etc., and hope to find and deal with problems in a timely manner. You thought everything was going well, but you didn't expect to get complaints from users frequently during the system operation. The reasons are:
- The master-slave delay of the used database becomes longer, causing problems in business functions;
- The response time of the interface becomes longer, and a blank page appears on the user feedback product page;
- A large number of errors occurred in the system, which affected the normal use of users.
31. Application performance management: How should the user experience be monitored?
32. Stress test: How to design a full-link stress test platform?
33. Configuration management: How to manage thousands of configuration items?
34. Downgrade fusing: How to shield the impact of non-core system failures?
35. Flow control: How do we manipulate flow in a highly concurrent system?
Actual combat
37. Counting system design (1): How to do counters facing massive data?
38. Counting system design (2): How to design an unread system under 500,000 QPS?
In the previous lesson, I took you to understand how to design a universal counting system that supports high concurrent access and storage of large amounts of data. Through caching technology, message queue technology and deep transformation of Redis, we can support trillions Count data storage and millions of read requests per second. However, there is a special type of counting that does not fully use the scheme we mentioned, that is, unreading.
39. Information flow design (1): How to do the push mode of the general information flow system?
40. Information flow design (2): How to do the pull mode of the general information flow system?
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