Performance and scalabilities are achieved by application architecture, not by any particular choice of language or framework. We can use any programming language to make it scalable, like Java, PHP, C#, or Python, but Node.JS is an outstanding choice for a few reasons.
It’s important to consider the performance, scalability, and maintainability of the language or environment when making this decision. Generally, it’s a good practice to scale an application before it reaches its maximum capacity. This can help ensure that the application is able to handle the traffic and requests, and it can also help prevent performance issues and downtime.
Assume we have a monolithic e-commerce application built in Node.JS, which handles a certain amount of traffic daily. However, the application is growing fast now, and it has broken its threshold. It will reach its maximum capacity very soon. Everyone is panicked and asking – “What do we have to do?” We need to scale it.
Let’s see what we can do to resolve this situation.
Strategy and Techniqe to Scale the Application
Scaling an application can be a challenging task. Here are some strategies and techniques we can take into consideration:
Identify the bottlenecks:
Use a load balancer:
Use a caching solution:
Use a reverse proxy:
Use a reverse proxy:
Use a container orchestration system:
Scalability: Improve Node.Js Performance
Single Server Setup:
- Load balancer takes care of the requests and accomplishes two functions: static filers server and reverse proxy. It serves all static files (CSS, JS, Images) by itself without touching the web app. The request that the app needs to resolve is redirected to it, this is called a reverse proxy.
- Zero-downtime upgrades.
- Unable to access our application if the web server goes down.
- Many users access the web server simultaneously and it reaches the web server’s load limit.
- Users experience slower responses or fail to connect to the server.
- If server 1 goes offline, all the traffic will be routed to server 2. This prevents the application from going offline.
- If the application traffic grows rapidly, and two servers are not enough to handle the traffic, the load balancer can handle this problem gracefully (auto-scaling). Only need to add more servers to the web server pool, and the load balancer automatically starts to send requests to them.
- No failover issues.
- Handle more traffic.
- Availability of server.
- Better performance.
- High availability.
- Application and database don’t fight for the same resources.
- We can scale each (application, DB) independently too as many as we need.
Read More: Start Caching With Python
Content delivery network (CDN):
Logging, Metrics, and Automation:
- Easier to scale, scale only required services.
- Improved productivity.
- Improved fault isolation.
- Reusability of services.
- Simpler to deploy.
- Easier migration.
Scaling is an iterative process. What we have learned here so far can help us achieve scaling a NodeJS application. For more fine-tuning, we can make new strategies to scale it further. For example, we might need to deploy it in data centers depending on the number of geographic users.