下設 ke:chaoxingitcom/1585/
The whole process of developing the first high-concurrency seckill system of GO actual e-commerce.
I. Introduction. With the rapid development of the e-commerce industry, the high-concurrency seckill system has become one of the core functions of e-commerce. In order to cope with the increasing business needs and the number of users, this article will introduce how to use the Go language and related technologies to build an efficient, stable and scalable e-commerce ** high-concurrency seckill system.
Second, the system architecture.
The following is a simple system architecture design of the e-commerce ** high concurrency seckill system:
1.Front-end design:
Static Resource Server: Use a dedicated server to store and serve static resources such as HTML, CSS, J**ascript, etc.
Front-end caching: Use the CDN service to cache static resources to reduce the pressure on the static resource server.
Front-end load balancing: Load balancing is used to distribute front-end requests to ensure that the pressure on each server is balanced.
2.Back-end design:
Web server: Use Go's web framework to process user requests, such as GIN or BEGOGO.
Application-layer caching: Use the cache to store some frequently accessed data to reduce the pressure on the database, and you can choose Redis or Memcached.
Business logic layer: Handles the business logic of spikes to ensure the proper handling of concurrent requests, such as avoiding overselling through distributed locks.
Distributed throttling and circuit breakers: Use throttling and circuit breakers to prevent system crashes caused by excessive requests.
3.Data Storage:
Databases: Use a high-performance database such as MySQL or TIDB. Read/write splitting can be used to improve the read/write capabilities of the database.
Database and table sharding: If the amount of data is large, consider using database and table sharding to spread the pressure on the database.
Database connection pooling: Use connection pooling to effectively manage database connections and reduce the overhead of establishing and destroying connections.
4.Caching Layer:
Caching databases: Use Redis to store hot data such as product information, inventory, and more.
Local caching: Use local caching at the application layer to alleviate requests for cached databases.
5.Message Queuing:
Message queues: Use message queues, such as RabbitMQ or Kafka, to process user spike requests asynchronously to improve the system's concurrent processing capabilities.
Asynchronous processing: Use message queues to asynchronously process operations such as order creation and payment to improve system throughput.
6.Service Monitoring & Logs:
Monitoring system: Integrated monitoring systems, such as Prometheus, Grafana, to monitor the performance indicators of each component of the system in real time.
Log system: Use the log system to record key information about the system during operation, which is convenient for troubleshooting and performance optimization.
7.Security by design:
Anti-swiping and captcha: Anti-swiping and captcha mechanisms are introduced to prevent malicious requests.
SSL TLS: Secures user data transmission with SSL TLS encryption.
Permission control: Restricts users' access to the Lightning Deals API to ensure that only legitimate users can participate in the Lightning Deals.
8.High Availability and Disaster Recovery Design:
Multi-node deployment: Deploy multiple nodes in different geographic locations to improve system availability.
Automated deployment and containerization: Use containerization technologies, such as Docker and Kubernetes, to automate deployment and rapid scaling.
3. Key technologies.
Distributed locks: Use distributed locks to ensure concurrent access control to critical resources, such as commodity inventory, to prevent overselling.
Commonly used distributed lock implementations include distributed locks based on REDIS.
2.Caching technology:
Leverage caching to reduce the strain on your database and improve your system's read performance.
Use Redis as a caching database to store hot data such as product information and inventory.
3.Message Queuing:
Message queues are used to implement asynchronous processing, and user spike requests are asynchronous to improve the concurrent processing capacity of the system.
Common message queues include RabbitMQ and Kafka.
4.Current Limiting and Fuse:
The throttling mechanism is introduced to control the concurrent access traffic of the system and prevent the system from crashing.
Implement a circuit breaker mechanism to prevent abnormal requests from further affecting the normal operation of the system.
5.Database Design & Optimization:
Use a high-performance database such as MySQL or TiDB.
Read/write splitting is used to improve the read performance of the database.
Consider using database connection pooling to manage database connections and reduce the overhead of establishing and destroying connections.
6.Distributed System Design:
Build a distributed system, split the system into multiple modules, and improve the horizontal scalability of the system.
Consider adopting a microservices architecture to split different functions into separate services.
7.Concurrent programming with goroutines:
Using the concurrent programming characteristics of the Go language, goroutines are used to achieve high concurrency processing.
Use go's channel to communicate between different goroutines.
8.Security Measures:
Introduce anti-flashing and verification code mechanisms to prevent malicious requests.
SSL TLS is used to encrypt user data transmission to ensure data security.
9.Performance Optimization:
Conduct performance testing to identify and optimize system bottlenecks.
Use a performance optimization tool for the Go language, such as PPROF, for performance analysis.
10.Containerization & Automated Deployment:
Use Docker to containerize applications to improve deployment flexibility and consistency.
Use container orchestration tools, such as Kubernetes, to automate deployment and scaling.
Fourth, the spike process.
User login: The user logs in to the e-commerce platform and authenticates the user.
Participate in the Lightning Deal: The user selects the product on the Lightning Deal page and submits the order.
System processing: The system allocates resources (such as inventory) according to user requests, and performs operations such as order processing and deduction.
Notify users: The system sends SMS or email notifications to users about the success or failure of the lightning deal.
5. Testing and optimization.
Stress test: Test the performance and stability of the system by simulating a large number of users to perform a flash kill operation at the same time.
Performance optimization: According to the test results, the performance of the system is optimized, such as adjusting the database configuration and optimizing the logic.
Fault drills: Simulate common fault scenarios in flash sales activities, such as network failures and server failures, to improve the fault tolerance and recovery speed of the system.
6. Summary and outlook.
Through the above introduction, we learned that using the GO language and related technologies, we can build an efficient, stable and scalable e-commerce ** high-concurrency seckill system. However, with the development of the e-commerce industry, the challenges faced by the flash sale system will continue to increase. In the future, we need to continue to explore and innovate on the basis of existing technologies, such as introducing artificial intelligence and machine learning technology, improving the best and decision-making capabilities of flash sales activities, and achieving a more intelligent flash sale system.