Ali architect: several technical abilities that programmers must master

1. Source code analysis

Source code analysis is a kind of critical knowledge. Once you have mastered this critical knowledge, you can adapt to any changes. For many people, source code analysis is boring, jerky and difficult to understand.

Source code reading, I think there are three core points: technical foundation + strong curiosity + patience.

I think it is the core driving force of reading source code. I have seen the vast majority of programmers, and their attitude towards learning is basically these levels (very extreme):

1. Just focus on the project itself, if you don't understand it, just baidu it.

2. In addition to doing a good job in the project, I also read technical books related to the project, see wikipedia.

3. In addition to reading books related to projects, I will also read books in the IT industry. For example, when learning Java, I will also learn about functional languages, such as LISP.

4. Look for some open source projects, try a lot of third-party frameworks, and write demos.

5. Read the basic framework, J2EE specification, Debug server kernel.

Most programs are type 1, and reaching type 5 requires not only intense interest, but also courage: Can I read it? Actually, you can read it.

Patience is really important. Because you rarely see instructive articles or books for reading source code, and no one asks or recommends that you read them. You will often get stuck while reading, and one card owner may be stuck in a maze. At this time, what you need to do may be to temporarily interrupt it, and then look at it from the periphery: such as the API structure and the design diagram of the framework.

The following figure is my summary of the source code knowledge points that should be learned most at present:

2. Distributed Architecture

Distributed system is an old and broad topic, but in recent years, due to the rise of the concept of "big data", it has radiated new youth and vitality. In addition, distributed system is also a subject content that attaches equal importance to theoretical models and engineering techniques. Compared with the research direction of machine learning, students who study distributed systems often feel: "It is easy to get started, but difficult to go deep." Indeed, learning distributed systems hardly requires much math.

Distributed systems is a complex and broad field of study, and taking an online course or two and reading a book or two may not cover it all.

In general, the task of a distributed system is to organically combine and connect multiple machines, so that they can cooperate to complete a task, which can be a computing task or a storage task. If we must make a classification of distributed system research in recent years, I personally think that it can include three major parts:

• Distributed Storage System

• distributed computing system

• Distributed Management System

The following figure is my summary of the most mainstream distributed technologies in recent years:

3. Microservices

At present, microservices are very hot, and everyone claims to be using microservice architecture, but what exactly is microservice architecture? Is the microservice architecture a development trend? We all lack a clear understanding of these issues.

In order to solve various problems under the monolithic architecture, the microservice architecture came into being. Rather than building a bloated, untamable monster, it's better to break up the service sooner rather than later. The core idea of ​​microservices is to split and decouple services to reduce complexity. Microservices emphasize the rational disassembly of functions, ensure that each service has a single function as much as possible, and define roles according to the Single Responsibility Principle. Each service is made lighter, so as to be flexible and reusable, and it can also be deployed and scaled independently according to the resource requirements of each service.

The following figure is my summary of the knowledge points that microservices need to learn:

Fourth, performance optimization

Whether it’s dealing with front-end interviews or improving product experience, performance optimization is an inescapable topic.

The purpose of optimization is to make users feel "fast", so how to make users feel fast?

• The loading speed is really fast, the user opens the input URL and presses enter to see the page immediately

• It doesn't load faster, but users feel your site is fast

Performance optimization depends on several factors, including garbage collection, virtual machine, and underlying operating system (OS) settings. There are several tools available to developers for analysis and optimization, you can learn and use them by reading Java Tools for Source Code Optimization and Analysis.

It must be understood that no two applications can use the same optimization, and there is no perfectly optimized reference path for a java application. Use best practices and stick to the proper way to handle performance optimizations. To achieve the truly highest performance optimizations, you as a Java developer need to have a proper understanding of the Java Virtual Machine (JVM) and the underlying operating system.

The above five knowledge systems are the experience that I have summarized for many years in the industry, and they are the most mainstream technologies at present.

The following figure is a summary of several knowledge systems that I should learn and understand about performance optimization:

Five, Java engineering

If you want to do a good job, you must first sharpen your tools. Whether you are a novice or a senior developer, you need to choose a good tool first. Improve development efficiency and team collaboration efficiency. Allow yourself more time to think.

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