Having been engaged in IT for many years, I suddenly felt weak in my career. Especially recently, the tumultuous Pinduoduo incident has made it difficult for Internet IT workers to let go of their working spirit.
01
However, as an ordinary programmer, how to improve his abilities and possess a skill in the workplace has become an urgent need for ordinary people and me.
What kind of ability do you have to not be eliminated? The answer is: high concurrency , it has almost become an experience that every programmer wants to have.
The reason is simple: traffic is a necessary requirement for large e-commerce companies. For example, Taobao’s Double Eleven will generate a lot of high concurrency, with hundreds of millions of users, billions of traffic per day, and 100,000 concurrency during peak periods. Therefore, how to resist high concurrency is what this large company needs to face.
Therefore, if you master this technology, your salary will dig into your pocket.
02
When you go to interview a senior Java engineer, the high concurrency area is often asked by the interviewer. For example, he will carefully ask what system architecture you use? How is it deployed? How many machines are deployed? How is the cache used? How to use MQ and database? It is to dig deep into how you can handle high concurrency. To put it bluntly, they just want to see if you have experience in dealing with high concurrency.
Moreover, interface response timeout, increased CPU load, frequent GC, deadlock, large data storage, etc., these problems can promote continuous improvement in technical depth.
Anyone who has really done high concurrency knows that if you break away from the business system architecture, you are actually talking on paper. When dealing with high concurrency in complex business scenarios, you can’t simply use MQ and Redis to get it done . The business scenario is much more complicated than this.
03
However, everyone's understanding of high concurrency is completely wrong.
1. Most people have no idea about data-based indicators
They do not know what indicators to use to measure high concurrency systems? I don’t know the concurrency and QPS, and I don’t even know the total number of users, active users, QPS and TPS during peak and peak periods.
2. Although some schemes have been designed, the understanding of details is deviated
Can't tell the technical points that the plan needs to pay attention to, and the possible side effects. For example, they ignore the cache hit rate, hot key, data consistency and other issues.
3. Understand high concurrency design as performance optimization
Talking about concurrent programming, multi-level caching, asynchronization, and horizontal expansion, but ignoring high-availability design, service governance, and operation and maintenance guarantees.
4. Although mastering the big plan, the most basic things are ignored
I can only explain the big ideas such as vertical layering, horizontal partitioning, and caching, but I don't know whether the data structure is reasonable and the algorithm is efficient. I never thought about optimizing the details from the most fundamental IO and computing dimensions.
04
So, how can I improve my high-concurrency technical ability, and get advanced, and take great offers? Taking this opportunity, I strongly recommend to everyone a top-secret Alibaba internal material "Ten billion-level concurrent system design". After finishing this information, you will definitely be able to stand up in front of the interviewer, and your salary will rise!
The actual combat tutorial of "Ten billion-level concurrent system design" is divided into basic articles + database articles + caching articles + message queue articles + distributed services articles + maintenance articles + actual combat articles, full of dry goods!
Due to space reasons, the article only introduces the general content. Troublesome one-click triple + comment, and then add VX (tkzl6666) to get the full version of this top-secret Alibaba internal information "Ten-Billion Concurrent System Architecture" practical tutorial for free. (Promise 100% free)
1. Basics
01 | High Concurrency System: What is its general design method?
02 | Architecture Layering: Why do we have to do this?
03 | System design goal (1): How to improve system performance?
04 | System design goal (2): How to achieve high availability of the system?
05 | System design goal (3): How to make the system easy to expand?
06 | The first phase of the interview site: When asked about the principle of component implementation, is the interviewer making things difficult for you?
Two, database articles
07 | Pooling technology: How to reduce the performance loss of frequently creating database connections?
08 | Database optimization plan (1): How to separate master and slave when query requests increase?
09 | Database optimization plan (2): How to implement database and table splitting when the amount of written data increases?
10 | 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?
Three, cache articles
12 | Caching: After the database becomes the bottleneck, how to speed up the query of dynamic data?
13 | The posture of the cache (1): How to choose the read and write strategy of the cache?
14 | Cache usage posture (2): How to achieve high availability of cache?
15 | Cache usage posture (3): What should I do if the cache penetrates?
16 | CDN: How to accelerate static resources?
Four, message queue articles
17 | Message Queue: How to handle tens of thousands of order requests per second during the spike?
18 | Message Delivery: How to ensure that the message is only consumed once?
19 | Message Queuing: How to reduce the delay of messages in the message queuing system?
20 | The second session of the interview site: When asked about the project experience, what exactly does the interviewer want to know?
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?
28 | Multi-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 | Adding eyes to the system: how to do server-side monitoring?
31 | Application Performance Management: How to monitor user experience?
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 effects of non-core system failures?
35 | Flow Control: How do we manipulate the flow in a highly concurrent system?
36 | Interview Site Phase 3: How do you prepare for a technical interview?
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?
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?
Due to space reasons, the article only introduces the general content. Troublesome one-click triple + comment, and then add VX (tkzl6666) to get the full version of this top-secret Alibaba internal information "Ten-Billion Concurrent System Architecture" practical tutorial for free. (Promise 100% free)