登录查看更多内容

What techniques can you use to optimize your application for a large number of users?

由人工智能和领英社区提供技术支持

If you are developing an application that needs to handle a large number of users, you might face some challenges in terms of scalability and performance. How can you ensure that your application can cope with high demand, deliver a fast and smooth user experience, and avoid crashing or slowing down? In this article, we will explore some techniques that you can use to optimize your application for a large number of users.

此文章中的业界达人

由社区从 6 条内容中精选。了解更多

Lutz Filor

System/SW Architect @ AMD | Hardware Design, Analog Semiconductors
Vivek R.

Diligent Staff Technologist Delivering High Impact Robust Scalable Solutions on Diverse Stack: With a Passion for…
Rafal Sojka

Experienced Software Engineer

1 Choose the right architecture

When developing an application, one of the first decisions you need to make is the architecture, or how you organize the components and interactions of your application. This choice can have a major effect on scalability and performance, as it determines how easy it is to add resources, distribute the workload, and manage complexity. There are several architectures you can use to optimize your application for a large number of users. Microservices divide your application into small, independent services that communicate through APIs, allowing you to scale each service independently and deploy them faster. Serverless lets you run your code without managing or provisioning servers, reducing operational costs and allowing you to pay only for resources used. Event-driven architecture relies on asynchronous communication between components triggered by events like user actions, messages, or data changes. This decouples your application logic and improves responsiveness while requiring more testing and monitoring tools. Ultimately, each architecture has its advantages and drawbacks, so it is important to consider all of them before making a decision.

添加您的观点

Lutz Filor

System/SW Architect @ AMD | Hardware Design, Analog Semiconductors
举报内容
Load testing, meaning create background load - to run individual test engineer transactions for QOS and measure latencies, and correctnes of responses. Increasing the number of background load, tests the upper limit of concurrent transactions at any moment of operation.

已翻译

赞
Jyotirmoy Nath
举报内容
I totally agree with this, methods like Horizontal Pod auto-scaler, cluster auto-scaler and KEDA can help engineer free themselves from constantly having to monitor and scale their environments. Organisations can then focus more on business requirements and customer features.

已翻译

赞
Vivek R.

Diligent Staff Technologist Delivering High Impact Robust Scalable Solutions on Diverse Stack: With a Passion for Technology, Innovation, and Growth.
举报内容
For any application to facilitate a large number of users to have a seamless experience one needs to factor in the below pointers whilst deciding on the architecture, 1. Horizontally scalable stateless application instances to handle the load 2. Layer 7 load balancer (NGINX) for content-based routing on the scaled instances (with caching) 3. Low latency and high throughput by distributed caching strategies (along with invalidation logic) 4. CQRS pattern - Read and Write database isolations 5. Choose the right DB with CAP requirements RDBMS - Partitioned, Sharded, Indexed tables, and NoSQL - key-value store, columnar storage, Document DB for scalability 6. Asynchronous processing with queue implementations 7. CDN to cache static pages

已翻译

赞

2 Optimize your code

When developing your application, the quality and efficiency of your code is an important factor that affects scalability and performance. Writing clean, readable, and maintainable code that follows best practices and standards is essential. To optimize your code for speed and resource consumption, you can apply techniques such as caching, compression, and parallelization. Caching involves storing frequently used or expensive data in a fast and accessible memory to reduce requests to the database or external services. Compression reduces the size of data sent or received over the network by encoding redundant or unnecessary information. Parallelization splits a large or complex task into smaller subtasks that can be executed simultaneously by multiple threads, processes, or machines. However, you must also manage cache size, expiration, invalidation policies, compression ratio/processing time balance, synchronization/communication/coordination issues, and avoid concurrency pitfalls. By doing so, you can improve performance and scalability of your application as well as enhance user experience.

添加您的观点

Vivek R.

Diligent Staff Technologist Delivering High Impact Robust Scalable Solutions on Diverse Stack: With a Passion for Technology, Innovation, and Growth.
举报内容
To enable a large number of concurrent users of the application, 1. Implement memcached/Redis caching solutions for read-intensive operations and asynchronous queuing mechanism for DB writes 2. The code should be nonblocking and synchronized to maintain data state consistency 3. Choosing the right data structure and algorithms based on the time complexity analysis of Big-O notation (constant, linear time is best, logarithmic is better) 4. Query caching to avoid excessive DB calls

已翻译

赞

3 Monitor and test your application

To optimize your application for a large number of users, you need to monitor and test it regularly and systematically. Collect and analyze data and metrics to measure and improve scalability and performance, such as load, capacity, and performance. For load, monitor patterns and trends, identify peak times, average values, and outliers. Test the application under different load scenarios and simulate expected or unexpected growth or spikes in demand using tools like load testing or stress testing. For capacity, monitor utilization and availability, identify bottlenecks, shortages, or waste. Test the application with different capacity configurations to optimize resource allocation and distribution using tools like capacity planning or auto-scaling. For performance, monitor indicators and benchmarks to identify factors that affect or degrade performance such as code, architecture, or environment. Test the application with different performance criteria and expectations to improve efficiency and reliability using tools like performance testing or profiling.

添加您的观点

Vivek R.

Diligent Staff Technologist Delivering High Impact Robust Scalable Solutions on Diverse Stack: With a Passion for Technology, Innovation, and Growth.
举报内容
The large application user base means one should be mindful of the metamorphosis directions of the application, 1. Integrate the application with APM tools like Datadog, NewRelic, and others capturing metrics such as latency, throughput, memory (heap) usage, and CPU usage and use this as feedback to optimize further 2. Execute performance testing on the application for every code commit (via Continuous integrations) ensuring that it is not degrading on the change 3. Set up monitoring alerts if there is a spike in the application resource utilization and instrument the hotspot for mitigation

已翻译

赞

4 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

添加您的观点

Rafal Sojka

Experienced Software Engineer
(已编辑)
举报内容
Do not forget about database scaling. Try to stay a step ahead of your user base size with this or you can get into serious trouble. Query optimisation and indexing are good ways to start. Also think about DB server size (vertical scaling). Command Query Responsibility Segregation (CQRS) is something to be familiar with and apply when needed. From there you should start thinking about horizontal scaling options - replication, partitioning, sharding.

已翻译

赞

Application Development

+ 关注

给文章评分

我们借助人工智能创建了此文章。您认为这篇文章怎么样？

很棒不太好

举报此文章

查看全部

What techniques can you use to optimize your application for a large number of users?

1

2

3

4

1 Choose the right architecture

2 Optimize your code

3 Monitor and test your application

4 Here’s what else to consider

Application Development

给文章评分

感谢您的反馈

更多Application Development相关文章

更多相关阅读内容