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Scaling Tornado applications

Introduction​

Tornado is a powerful Python web framework and an asynchronous networking library which allows it to handle thousands of open connections. When it comes to deploying Tornado applications, one of the important aspects to consider is scaling. Scaling your application allows it to handle more requests per second and therefore, serve more users.

Understanding Scaling​

Scaling can be divided into two types: Horizontal scaling and Vertical scaling.

Horizontal Scaling refers to adding more machines to your pool of resources. It involves duplicating instances to share the workload and reduce the strain on a single instance.

Vertical Scaling refers to adding more power to your existing machine. In other words, you are increasing the capabilities of your server, such as adding more RAM or a more powerful CPU.

Scaling Tornado Applications​

Vertical Scaling​

Vertical scaling of Tornado applications involves increasing the resources of the server where the application is deployed. You can increase CPU power, RAM, and Disk space, among other things.

However, there are limits to how much you can scale vertically due to physical restrictions of the server and costs.

Horizontal Scaling​

Horizontal scaling, on the other hand, can be limitless, as you can always add more servers. Tornado, due to its asynchronous nature, allows you to handle thousands of connections, making it a good fit for horizontal scaling.

Load Balancing​

When you scale out your Tornado application across multiple servers, you'll need a load balancer to distribute incoming network traffic across these servers. Load balancing helps in achieving optimal resource utilization, maximizing throughput, and minimizing response time.

Session Management​

When you scale horizontally, handling sessions can become an issue as requests from the same user can land on different servers. To handle this, sessions need to be managed at a centralized place, which can be a database or an in-memory data store like Redis.

Scaling Database​

Scaling your Tornado application also involves scaling your database. Like applications, databases can also be scaled both vertically and horizontally.

Vertical scaling is achieved by increasing the resources of your database server. This includes adding more RAM, CPU, or disk space.

Horizontal scaling, also known as sharding, involves splitting your database across multiple servers. Each server acts as the source of truth for its slice of data.

Monitoring and Scaling​

Monitoring is an essential part of scaling. By monitoring, you can identify the bottlenecks in your Tornado application and scale appropriately. You can monitor various metrics like CPU usage, memory usage, disk I/O, and network traffic, among others.

Conclusion​

Scaling a Tornado application involves more than just throwing more resources at it. It requires careful planning, monitoring, and understanding of both the application and the underlying infrastructure. With the right strategy, you can ensure your Tornado application can handle an increasing amount of load and serve more users efficiently.