Performance Principles of Software Architecture

In this blog post, we will see Performance Principles of Software Architecture. We know how the performance problems happens in the first place, like Queue Building etc. Now we will see what are the principles of performance. If you missed about the performance issues, refer to this one for more information. In short, these are the problems associated with it. For queue Building issues, see below

1. Inefficient slow processing: algorithms which runs slowly that will bring down the performance of application.

2. Serial resource access: executing some processes on single thread and working on that thread

3. Limited resource capacity: Now, let’s assume that we are executing requests in parallel, but our CPU is not efficient (limited CPU resource) to perform

Also, we have seen the issue of Serial/Single Request Processing.

Performance Principles of Software Architecture

So basically we need High degree of efficiency 2. Concurrency and 3. Adequate Capacity

Let’s look at the key performance factors impacting the above 3 principles.

Algorithmic Efficiency

The effectiveness of any algorithm used to solve a problem impacts its performance, so programmers should select an efficient algorithm which effectively resolves their problem. Choosing proper algorithm is the key to get good performance.

Data Structures

Selecting an efficient data structure can have a lot of impact on performance. Programmers should select structures created specifically for solving their particular problem. Data structure is the most important factor that affects the performance of the system.

Memory Management:

Proper memory management is crucial to performance, so programmers must limit memory usage and utilize their allocated storage efficiently. We should always take the dump of threads and use various memory analyser tools to identify and fix the piece of code which is not good for memory consumption.

Parallelism:

Parallelism allows multiple tasks to be run concurrently, which can greatly enhance performance. Programmers should consider using parallelism when applicable as it will increase the performance by good margin since we are parallelly executing tasks or workloads.

I/O Input or Output Optimization:

Programmers should look to optimize I/O operations so as to minimize their effect on overall performance of the system. More Input output operations will impact performance.

Code Profiling

This is one of the principle which is used by many. Code profiling is the practice of examining the performance of a program in order to detect bottlenecks or opportunities for improvement, so programmers should regularly conduct this exercise to increase performance and enhance overall efficiency.

Coding Optimization

Programmers should look to make their code as fast and efficient as possible, including optimizing algorithms, data structures, and memory usage. Code optimization can be done by reviewing it properly and analysing the piece of code that is taking more time and resource than expected one.

Testing

Testing is key to ensuring a program satisfies its performance requirements, so programmers should conduct extensive tests in order to detect and fix performance issues as early as possible. Testing can be done from developers as well as testers side to identify the issues. Testing can be done with the help of proper test cases and its execution and using some of the automated tools (Jmeter) as well.

Platform Optimization

Programmers should ensure their code runs on the platform they intend for optimal performance. Programmers should write their code specifically to target platforms when writing code. Programmers should always keep the target system in mind so that we can write code that will run smoothly.

Caching

Caching can boost performance by temporarily storing frequently accessed information in memory, so programmers should use caching to boost performance. For improving performance, caching is widely used and a key factor of implementation system. We can use caching framework like redis to improve performance of the system.

Load Balancing

Load balancing can improve performance by spreading workloads among multiple servers. Programmers should consider using load balancing where it makes sense. In case of more traffic, these load balancers make it easy to run our application without impacting the performance of the system.

Resource Utilization

Optimizing system resources efficiently can significantly boost performance. We must strive to minimize resource use while employing them efficiently. Resources can cause a lot of IO operations and connectivity performance issues.

Concurrency

Concurrency allows multiple tasks to be executed simultaneously, which can increase performance. We should consider taking advantage of concurrency when applicable. Concurrency is probably the most important factor for improving performance of the system. We can use threads and related framework to implement concurrency in the application.

Scalability

Scalability refers to the ability of a program to handle increasing workloads. Programmers should design programs with this in mind in order to meet future performance requirements. Scalable applications are the must one whenever we are designing any of the system design.

Error Handling

Efficient error handling can prevent crashes and enhance performance, so programmers must implement robust error-handling mechanisms. Error handling not only saves performance, but also it can help us in identifying the scenarios and way to handle them gracefully.

Conclusion

In this blog post on Performance Principles of Software Architecture , we have seen that Programmers must adhere to key performance principles when writing code. Doing so can ensure their program performs optimally, uses resources efficiently, and meets its requirements and guarantees proper execution of all the system features in timely manner .

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