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Performance stress testing tools:

Usually use tools: Jmeter and LoadRunner to initiate stress tests and collect stress test indicators.

Nmon: testing the performance of Linux, it is widely used in linux system for monitoring and analysis tools.

Memory usage: MAT, GC log, vmstat

Situation: iostat

Network situation: Netstat

Hot codes: JProfiler, BTrace, JStack, JStat

CPU case: top command under Linux

Optimization methodology:

Amdahl's law: analyze and optimize the points that have the greatest impact on the whole.

Do not access unnecessary data: reduce unnecessary links, reduce points of failure and maintenance

Load nearby: cache is king

Fault isolation: don't crush the whole system because of one system bottleneck.

Have good scalability: make rational use of resources, improve processing efficiency and avoid single point of failure

Optimize the entire link: reduce serial synchronous calls and split reasonably (horizontal or vertical meals)

Performance is as important as functionality: if the performance index of the five functions is 90% of that of the design phase, the overall performance becomes 59% of that of the design.

Optimization ideas:

1. Understand the current situation and find problems

2. Determine a clear optimization goal, analyze the gap between the current situation and the goal, and confirm the implementation route.

3. Split the system and optimize the logical layer (Web layer, business layer, persistence layer) and physical layer (client, network, application server, database server) respectively.

4. Use tools to monitor and test the system, and analyze the monitoring results.

5. To optimize the system scientifically, we need to follow certain procedures: monitoring / performance testing-> analyzing the causes of the bottleneck to verify that the bottleneck factors modify the system to confirm whether the optimization goal is achieved.

Factors affecting performance: CPU, memory, IO, network, or other factors

Identify major bottlenecks: resolve key factors first, and then repeat monitoring or test verification

Avoid over-optimization, modify one bottleneck at a time, and don't optimize where you don't need it.

Improve CPU performance, write faster code, design better algorithms, and reduce short-term survival objects

Improve memory performance: reduce long-term survival objects

Improve the performance of Icano: redesign the application to reduce the interaction of Icano

Cache is king: moderate cache to maximize the role of database cache, application-side cache and client-side cache.

Hierarchical optimization:

Client optimization

Server optimization

JVM optimization

Database optimization

Load balancing optimization

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