Your web application is facing performance bottlenecks. How will you handle the increasing user numbers?

Initially Identify Bottlenecks reasons and try resolving the issue. Generally increasing user numbers can be catered by 1: Optimization of code 2: DB Optimization could help (Query optimization and indexing) 3: Implement caching to reduce DB trips 4: Autoscaling of servers are very helpful in case of increasing user numbers. 5: Performance Testing and Continuous Monitoring also play a vital role in this type of issues.

There are quite a lot of free and commercial load test tools on the market. They can simulate multiple users generating heavy web traffic and help to identify the root cause of the performance degradation. For instance, CPU overload, memory leaking, unoptimized databases or load balancing could cause the performance issues. Effective utilization of the load test tools like JMeter, K6, Locust, LoadRunner is typically the fastest way to analyze the application performance and find relevant issues.

We have been in this situation multiple times. The best way to resolve finding out the exact reason for bottle neck. There could be multiple reasons for the same 1. Do we have scalable infrastructure? 2. Are we using best performance sever configuration like apache or nginx? 3. Check the MySQL thread 4. Check Query performance 5. Follow proper indexes in database in case if it MYSQL 6. Check application code if is there infinite loop which could be causing the bottle neck.

Switch to a scalable cloud platform like AWS or Azure ASAP! They automatically adjust to handle more traffic as your user base grows. Make sure your database is optimized: use indexing wisely, review execution plans, and analyze how your app interacts with external resources. Plus, focus on improving the user experience and adjust your business processes if they’re causing friction. This way, you’ll keep your app running smoothly and your users happy!

To handle performance bottlenecks due to increasing user numbers: Monitor and Optimize: Use monitoring tools and optimize code, database queries, and caching. Scalability: Implement horizontal scaling with more servers and vertical scaling by upgrading hardware. CDN and Asynchronous Processing: Use CDNs for static content and offload tasks to background processes. Regular Testing and Optimization: Conduct regular performance testing and optimize server configurations. Leverage Cloud Services: Utilize cloud services for auto-scaling and managed databases.

First and foremost, identify the bottleneck by using tools like New Relic, or browsers built in profiling tools to identify the reds in your application. If its a frontend performance issue, improve with best practices for frontend optimization such as code minification, image optimization, and lazy loading, among others. Implement caching strategies like in-memory caching, among others. If its a resource issue, scale vertically by introducing a faster server or upgrading the current one, and for scaling horizontally, adding more application servers supported by a load balance would be one way to handle this. Remember, the specific approach will depend on your architecture, technology stack and the nature of the performance bottleneck.

As a web application if frontend is the perspective it mainly depends on how light the data is rendered. That's how Angular was misinterpreted. In case of ng repeat users use to load whole data. what we can expect when we load a lot of data in mobile irrespective of algo used. Next best thing is we should introspect on design is it feasible. We should try to keep the design simple with less svgs and graphical interface unless until absolutely necessary. The basic the most important thing in web application is developers need to understand that the customer machine is highly dependent on the actual customer ram, processor most important internet speed which varies. Server capacity is definitely not in developer hands.

It is critical to find the root causes of the perform issue. Was it caused by external traffic increase or internal issues? Was the traffic increased by jacking activities or robot crawling? You can olny take correct actions after you find the root causes.

You may consider applying a load balancer in front of your web application and then containerize the server so that it handle parallel requests. This is in addition to optimize code, connection pooling etc.

The first and most important step in addressing performance issues, and resolving any problem in general, is to analyze traffic and other available data to find the root cause. Identifying the root cause will help us determine the next steps wisely. When we identify which part of the application is under the most pressure, we can determine where to look in our code. We might need to refactor our codebase to address these issues and use more optimal ways to handle requests. Reviewing the database structure and optimizing it, along with refactoring database queries, is inevitable to achieve better performance.

In my field, where applications perform complex graphics-related tasks beyond simple data manipulation, ensuring smooth operation even on machines with limited memory is critical. Use profiling tools to pinpoint areas of excessive CPU resources or causing memory leaks. Always prioritize memory efficiency. use lightweight data structures, minimize object creation, pay attention to garbage collection patterns. Avoid redundant calculations, optimizing loops for performance, and select algorithms best suited for the task. Thoroughly evaluate and integrate performant libraries in isolated environments. Integrate performance testing throughout the development cycle, utilizing tools for load testing and monitoring resource usage.

To add to this points; - Avoid unnecessary computations. - Move long-running processes to background jobs(Asynchronous operations).

Code optimization is a crucial step in tackling performance bottlenecks. Review your application's codebase for inefficient algorithms or unoptimized loops that could be consuming excessive resources. Refactoring code to be more efficient can lead to significant performance improvements. Additionally, ensure that your backend services are optimized for their specific tasks. Introducing or adjusting caching mechanisms can alleviate server strain and improve response times, providing a smoother user experience.

Sonarqube like other code analysis tools can do code analysis automatically and can avoid first code optimize issues. You need to be careful while optimize the code to perform efficiently, that code should not loose readability, also code should not be coupled to avoid maintainability. Sometimes it is a choice that high performing code versus maintainability and extendibility. Now a days infrastructure is cheaper better choice should be mostly good maintainable code.

Imagine a bakery u own becomes incredibly popular, with more customers than ever. To handle the demand, you make some smart changes. First, u hire more cashiers and set up multiple counters so no single cashier is overwhelmed. This is like adding load balancers to ur web app, distributing traffic evenly across servers. Next, u streamline ur baking process, make each step more efficient. Similarly, in ur web app, you optimize code & reduce unnecessary database queries to speed things up. Lastly, u divide ur bakery into sections, each focusing on specific items like bread, cakes, & pastries. This is like using microservices, where different parts of your app can be scaled and managed independently, improving performance & fault tolerance.

In modern web applications most of time is consumed by synchronous operations such as http call to remote service, query to DB, etc. Always pay attention to how you interact with remote services. Avoid N+1 problem, check that your connections are persistent, check that read/write/connect timeouts are actual and try to execute your requests in parallel (e.g. with multi curl) if possible.

Procure trabalhar com o conceito MACH! MACH é a sigla em Inglês para Microsservices, APIs, Cloud native and Headless. No e-commerce, trata-se de uma arquitetura modular que permite que empresas como a sua se adaptem de forma ágil às demandas de tecnologia do setor.

This is a necessary step for all custom application, using profiling tools like xhprof for php based applications can help identify this issues in the code and hence using and integrating them can be alot of help in analyzing and mitigating such issues.

Code optimization in small pockets is easy, but code optimization that spans multiple functions, multiple files is tricky. There is a risk that your performance optimization effort breaks the functionality. It's therefore worthwhile to plan the performance optimization carefully and discuss it. A visual representation of the process flow (in terms of X-flowcharts or activity diagrams) would serve well.

For unnecessary requests, needs analysing code optimization. If we can return one response instead multiple endpoint calling, this reduce unnecessary traffics, also we need optimize db queries,seperate logics in app, using distributed cache vs so many solution we can do

Think of our web app like a highway: when traffic gets heavy, we can just add more lanes. If those lanes get filled, we keep adding more. If we encounter trees, houses, bird sanctuaries, meadows, playgrounds, or even schools, hospitals, and places of worship, we simply buy and replace those things with more lanes of highway. Ensuring your user's access to the app is worth any cost. Fight to overcome any obstacle, be it divine, royal, or managerial. This insatiable appetite for expansion will, in time, devour our children's future, but hey, at least the app will run smoothly.

Scaling your resources is often necessary to handle increased user numbers. This might involve upgrading your server hardware, moving to a more robust hosting solution, or implementing auto-scaling cloud services that adjust resources based on demand. It's important to scale both vertically (adding more power to existing servers) and horizontally (adding more servers) to ensure redundancy and improve load distribution. This balanced approach helps maintain performance and reliability, even during peak traffic periods.

If your Web application is experiencing performance issues and there is increase in user base, that's the time to think of migrating over to the cloud like MS Azure where your infrastructure can auto-scale. However, if you are not ready to migrate to the cloud, you can tune your database, ensure you have a three tier architecture where majority of the interactions with the database are done with Stored Procedures. Stored Procedures run faster. You can also look at up scaling some of the hardware such as server memory (RAM) and processors.

Migrate to any public Cloud like AWS or Azure where auto scaling is enabled. This will ensure traffic is taken care of. Use ALB to share the loan Requests

Trabalhar com serviços especialistas auxilia para dimensionar corretamente, por exemplo, voce pode enviar uma mensagem de forma assíncrona para efetivar a compra (e não uma síncrona, que pode ficar segurando a tela do seu usuário)

Using technologies like docker and Kubernetes, we can use load-balancers to optimize this and enable auto scaling so that the application infrastructure is capable enough to mitigate such issue, horizontal scaling help automatically improve resource only for the required time. Though in monolithic application like Drupal and Wordpress this usually is little difficult to achieve due to vertical scaling of DB is needed as horizontal scaling of the db is quite a bit of a problem and difficult

One thing I've found helpful that you can move static files to CDN. (Like Amazon S3h) So in production pages will be open more faster.

At some point you will be in situation where you have optimised every query, created all necessary indexes, but throughput is still low You need to understand what operations are actually your bottleneck: 1) Read operations are relatively easy to scale by adding new replicas and routing read traffic between them (you can even create special replica with additional indexes for your data analyst team to enable them run complex queries without affecting prod) 2) Write operations is the most difficulat one: Consider vertical scaling as the easiest approach Next you can utilise CQRS and rely on eventual consistency for read presentation (but writes will be easier!) The last is the most undesirable approach is to implement sharding

Scaling resources is crucial for handling increased user numbers and ensuring your web application remains responsive and available. By implementing certain scaling strategies, you can ensure that your web application can handle increased user numbers effectively, maintaining performance and availability even under high load conditions.

CDN Usage: Use a CDN (like Cloudflare or AWS CloudFront) to quickly deliver static content (images, CSS, JavaScript) by caching it in servers near your users.

Database performance is frequently the bottleneck in web applications. Regularly tune your database by optimizing queries, indexing necessary columns, and adjusting configuration settings for better performance. Consider implementing replication or sharding if your database is under heavy load. These strategies can distribute the workload across multiple machines or database instances, reducing the pressure on any single point and enhancing overall performance and reliability.

There are few PAAS DB services provides auto tuning. meaning they have services which can automatically creates indexes and drops indexes based on the load at specific times. Also, Based on the requirement it is really important to select database types NoSql, Sql or graphDb etc. Sharding and replications are strictly based on special use cases.

Classifique seus dados em Quente, Morno e Frio, para saber o que realmente precisa estar disponível e por quanto tempo no seu banco de dados.

La elección del manejador de base de datos es clave, según el producto, puede inclinarse por una relacional o no relacional, o en caso de ser necesario usar una mixta, en cualquiera de los casos la optimización y el uso correcto de la misma nos ayudara a evitar cuellos de botella y retrasos en la entrega de la información.

You'd be surprised how much scale you can claw back by fine-tuning your queries. I recommend partitioning tables having >500,000 rows and converting most SQL queries to views and procedures.

A concise summary of strategies to improve database performance: Optimize Queries Normalization/Denormalization Connection Pooling Caching Load Distribution Database Configuration Efficient Data Access Regular Maintenance Monitoring and Alerting Database Design Scaling Partitioning These strategies can help alleviate database bottlenecks and improve overall performance.

indexing, query optimization, and database normalization/denormalization as needed. and Implement caching strategies (e.g., using Redis or Memcached) to reduce the load on your database by storing frequently accessed data in memory.

Caching strategies are essential for improving web application performance by reducing the load on the database and speeding up response times. Here are some common caching strategies: Client-Side Caching Service Workers Server-Side Caching Page Caching Fragment Caching Data Caching Query Caching Object Caching Reverse Proxy Caching CDNs (Content Delivery Networks) Reverse Proxy Servers In-Memory Caching Memcached Redis Database Caching Materialized Views Application-Level Caching Cache Libraries Annotations/Decorators Distributed Caching Clustered Caching Solution By implementing caching strategies, you can significantly reduce database load, decrease latency, and improve the overall performance and scalability of your web application.

So i works on Drupal alot and drupal has adopted an intelligent caching mechanism where cache tags are issue for any new updated content invalidating the caches, and adding caching mechanism in drupal help a lot in achieving performance improvements for sure.

Remember not to cache everything! If you are adding to much to your cache it will run out of space and be forced to evict data. Therefore, be selective about what you cache so that you can be more confident that what you need will remain in the cache.

Use AWS caching like CDN so multiple DB calls can be avoided for same request and these can be served via CDN. Make sure to have invalidate Cache strategy defined.

When using content managers like Drupal, Wordpress, etc. Almost everything is retrieved from the database, but is that necessary? In most cases no, it isn't. If you host blog contents, the blog entries aren't going to change very often, so caching them will improve performance. We were using Drupal as a CMS for hundreds of websites and each page hit required more than 200 database calls that returned the same results over time, activating caching on Drupal's core made a big positive impact. When using CMS look for their respective caching tools. If your contents don't change often, create compressed files and make Nginx serve them directly. Some CMS also provide options to export rendered pages that can be served through CDNs.

Para os dados quentes, pense sempre em uma estratégia de cache, com atualizações diárias e diminuindo conforme a necessidade dos dados quentes;

Remember that there are always several layers of cache: 1) You can cache data in-memory of http worker (to reuse data within request) 2) You can cache data in-memory of master process (to reuse data within any request of single http server) 3) You can cache data in separate key-value storage such as Redis (to reuse data across all of your instances) When using 1) and 2) don't forget to expire local cache to avoid memory leaks

Effective caching strategies dramatically improve performance by reducing the load on backend systems. Caching frequently accessed data reduces latency, lowers database load, and leads to cost efficiency by minimizing the need for complex computations. This approach enhances scalability, allowing your application to handle more users without a proportional increase in server resources.

Implement caching strategies (e.g., using Redis or Memcached) to reduce the load on your database by storing frequently accessed data in memory.

We should keep in mind not just to add everything to the cache but also have an effective retention mechanism, so that we utilize the resources optimally.

Continuous monitoring of the server performance parameters is crucial for keeping the application in a good health, proactive reaction on performance degradation, and analyzing the possible causes of application outages. Based on your needs and the required monitoring levels you can use tools like Zabbix, SolarWinds, Grafana/Loki, or more sophisticated AppDynamics or Dynatrace.

Benefits of Continuous Monitoring: - Proactive Issue Detection: Identify potential problems early. - Performance Optimization: Optimize based on real-time data. - Resource Allocation: Allocate resources efficiently. - Improved User Experience: Maintain a seamless experience by addressing bottlenecks quickly.

Microservices Architecture: Break down the application into smaller, independent services that can be developed, deployed, and scaled independently. Containerization: Use Docker and Kubernetes for containerization and orchestration, making it easier to scale and manage your services.

Monitoring and Alerting, Continues monitoring is helpful but an alert generated whenever a spike occurs can help narrow down the bottleneck and help mitigate the issue before it happens.

Here’s a structured approach to handle this - 1. Performance analysis and Bottleneck Identification. 2. Horizontal and Vertical scaling of instances as per deployment infrastructure. 3. Optimising application performance by database and code optimisation. 4. Implement CDN and load balancing. 5. Caching Strategies 6. Migrate Monolithic to Micro-service architecture. 7. Usage of Queueing and Message brokers. 8. Database Sharding. 9. Opt for Serverless Architectures.

There has to be a mix of the actions we need to do based on application's nature. Few more to add are - 1. Before start of performance , know the architecture of the application and the number of concurrent users it can handle 2. Indexing seem too obivious on DB but in case if too much insert / updates index is not of much help so before tuning categorise the DB operations in CRUD buckets, check executions plans and execution times and their dependenciies on external APIs / applications/ validations/ resources 3.users perspective vs business needs any times the applications do not meet exprience the user is looking for. So may need a change in business process as well along with the minor / major UI changes

In addition to all the great suggestions, it’s also worth to re-evaluate the utilization metrics of different section on the web by the users. Brainstorm the opportunity to modularize heavily used sections with separate micro-services/micro-frontends and remove unused, resource consuming modules will help to optimize the performance. Sometimes, It’s not what we add improves the performance, it’s also what we declutter will boost the performance!

To handle increasing user numbers and performance bottlenecks in our web application, I would start by optimizing our database queries and implementing caching strategies. Next, I'd consider scaling our infrastructure horizontally by adding more servers or using a cloud service for better load distribution. Finally, performing regular performance monitoring and stress testing will help us stay ahead of potential issues.

we also generally need to consider Load Testing: Regularly perform load testing to simulate high traffic and identify potential bottlenecks under stress conditions. User Experience (UX): Continuously gather user feedback to understand the impact of performance issues on user satisfaction and address concerns promptly. Security: Ensure that performance optimizations do not compromise the security of the application. Conduct security audits to verify this.

I would strongly recommend doing continuous load and performance testing for the applications regularly to monitor the impacts of the code changes on the performance and ensure the optimization of the code. There are plenty of tools that can be easily integrated with current CI-CD pipelines like locust, blazemeter, Jmeter etc.

Also, you need to follow this best practices: * Set Baselines: Establish normal performance baselines. * Automate Alerts: Configure alerts for critical metrics. * Regular Audits: Review and update monitoring configurations periodically. * Integrate with CI/CD: Catch performance issues early in the development cycle.

Most of the times we are using the tools we are used to, but sometimes they aren't the best suitable tools for our use case. We were running the usual Apache + mod_php in our environment, we had some performance issues and moving the stack to nginx + php-fpm gave us a performance boost.