Listen to Audio Every business wants its app to be the best. With this plan in mind, developers choose their framework, database, and architecture favorable to the performance and quality. Continue Reading

Listen to Audio

Every business wants its app to be the best. With this plan in mind, developers choose their framework, database, and architecture favorable to the performance and quality.

When the first beta versions are released, the most challenging part of the applications arrives. How does time going to affect my app? What are the possibilities for scalability? How is the app going to perform for more extensive databases?

Many such questions arise during the whole development process. If you face similar issues, this article will help you understand the parameters that must be determined before or during the development process.

The crux of this whole scalability process cannot be defined or generalized as it depends on the technology being used for the entire web development process. But still, many parts of scalability can be generalized as a part of many web development challenges.

Below are top tips for building a scalable web architecture:

Independent Components & Nodes Functionality

Let’s take an example of SOA (Service-oriented architecture). It’s a type of architecture that doesn’t have all its components in one place but is split into multiple smaller components.

In this type of architecture, each component’s functional context remains independent and doesn’t affect other application components. Each component is linked to the other very competently.

The most important part of this architecture is not about simplicity in development but rather the structural integrity, which cannot fall apart—providing it with an advantage in maintaining the structure for a longer duration.

Any problem that occurred can be isolated and dealt with separately without hampering the entire structure’s integrity. This gives an advantage for maintaining the whole application, and the same can be said for the nodes as well.

Load Balancing and Smart Distribution

Let’s take nodes from my last point into consideration; the load balancers are crucial when talking about scalable web applications. The load distribution is important and can be achieved by smartly distributing the load when the simultaneous process increases.

This is where the criteria set up for load balancing play a crucial role in creating an optimal result for the entire application.

A large number of load balancers can be used to tackle very complex systems. Load balancers, along with caches and cookies, can solve the requester’s routing problems and provide the application’s optimal experience.

The best way to apply load balancing to your application is by using Nginx.

Caches for Accelerated Request Retrieval

There are high numbers of queries performed which are repetitive and are useful for most of the users. There are several ways these issues can be resolved and reduce the time for request retrieval.

We will talk about caches because they don’t harm your application in any way and most optimal way to solve the issues. In the cache, we can create quick access to the repeated queries using remote repositories to shorten the waiting time.

It is used at different levels of the app, and below are some of the examples.

  • You can insert the cache in each of your nodes, and the more numbers of nodes your application has, the more cache you will have. This will be useful for immediate request retrieval.
  • The method mentioned above can be tedious, and there is another way to lower the number of missed requests. This can be done using a global cache. You can create a global cache for all the nodes.
  • Another method is distributed cache, it reduces the load on the server. You can store data pieces on the client-side, and distribute it across the nodes. Retrieving the data from the user is faster.

Proxy for Better Server Request Handling

When we talk about scalability, handling multiple server requests becomes more challenging for the server disc.

The main advantage of using the proxy is to mitigate this issue and optimize database performance.  The proxy can combine multiple similar requests in one and decrease the number of queries and increase the response time.

To further optimize this approach, you can use proxies and cache together to provide the best user experience.

Indexing Large Datasets

We talked about data retrieval throughout the article, and we will continue on this point. Indexing is closely related to this as well; your application could be spread out across many devices. Indexing helps to find data in vast datasets and retrieve the information quickly.

To implement it in a quick search, you can create data tables based on the data stored and segregate the data as per your need.  This will generate a faster response from the server due to organized data.

This is a great way to increase request retrieval, but the indexing is hard to handle larger data sets. Much care is required.

Queues

As the scale of web application development grows by the day, the process of handling requests could become slower if not cared for properly.

When clients request concurrent queries, it becomes tedious for the application to hand all of them at once. The Queues helps the application to queue the request and handle the same in an organized manner.

The process includes a request from the client, acknowledgment from the server. This gives the client something to work with rather than handling all the requests at once and increasing the duration to produce results.

You can use Queue.js to queue the tasks and help you achieve scalability.

Conclusion

There are many ways to tackle the scalability issue, and different applications require different approaches for that. We have talked about reducing server request time, decreasing load, and many other factors that may be blocking your scalability approach.

Scalability is an important criteria for building a successful application. If you are planning to develop an application that is going to tackle large scale datasets, I’d recommend investing in the scalability approach first.


Author Bio: Himanshu Singh is a Marketing consultant at Rapidops. He is a technology enthusiast and well versed in software development. He is also interested in domains like machine learning and data science. In his spare time, he enjoys guitar, badminton, and photography.

ASNF