In this blog posts Rahul (rahulamodkar at gmail dot com) looks at key strategies to consider while building highly scalable application.
Introduction
Everyone want to build the next Unicorn whether it is a cab aggregating company like Uber or the room stay aggregating platform like Airbnb. The common thing among these is that these need to highly scalable web applications that are ready to serve millions of users.
We will look at some strategies that one needs to consider while designing such applications that are expected to scale.
High Scalability Strategies
Without going into too much details and also not talking about the specific tools, we will look at each of these strategies that can help one develop the scalable application.
1. Cloud
Consider deploying your application on the cloud. The cloud comes with the promise of limitless resources which can help you scale up or down in response to the traffic to your site. Theoretically the cloud can provide you as many resource as you request. The aspect of auto scaling also allows you to pay for only those resource that you end up using.
2. Load Balancing
One can deploy a load balancer that will help you distribute the load to your site into different servers thereby ensuring that not one server is overloaded which could result in it going down. Think of it as a traffic cop that will route the client requests across all servers such a way that no single server is overworked.
3. Content Delivery Network
Deploy the services of Content Delivery Network (CDN). A CDN (Content Delivery Network) is a global cluster of caches that can serve as local caches for static files (objects). The static content files are served from the CDN's caching-node closest to the visitor because the CDN takes the geo-location of the user in account.
4. Design for High Availability
It is very likely that the server on which your application is deployed may go down or in a extreme scenario the entire data centre may be down. To tackle this, think of deploying your application in a more than one geographical zone or data centre. This way when a server or an entire data centre goes down, your architecture be such that the application would simply stop routing traffic to the affected data centre. Also one needs to handle hardware and software failures by adding redundancy to the application design and eliminate any single point of failure.
5. Microservices Architecture
In micro-services based architecture, complex applications are composed of small, independent processes communicating with each other using language-agnostic APIs. These services are small, highly decoupled and focus on doing a small task. In a Microservices architecture the scaling of a particular micro service is far more easy when compared to a monolithic application . If a particular microservice in a application becomes a bottleneck due to slow execution, that particular Microservice can run multiple instances on different machines to process data in parallel. With the monolithic systems the scaling is difficult as you would have to run a copy of the complete system on a different machine.
6. Distributed Cache
A effective distributed caching strategy will improve performance in most of the scalable applications. Especially for read-intensive applications a caching implementation can boost the performance as application processing time and database access is reduced.
7. Database Master Slave
Deploy the Master Slave Database strategy where there is a dedicated powerful server for the writes and much lesser powerful database server dedicated to reads. Such a master-slave replication strategy when deployed in the right scenario lets an application distribute its queries efficiently.
8. NoSQL Databases
Consider using the NoSQL Databases. NoSQL databases have the ability to handle large volumes of structured, semi-structured, and unstructured data. They come with an inbuilt scale-out architecture would seamlessly work with your scalable application architecture.
9. Monitor
It is important that you monitor your application for various parameters so that you can either manually or in a automated way take a corrective action. The parameters that should typically be monitored could be applications, services, operating systems, network protocols, system metrics and infrastructure components. For e.g. monitoring will help you identify the health of server instances and automatically terminate & re-launch unhealthy instances. Monitors the application log files and put in place a process that make the engineers take action on issues identified.
10. Database Sharding
As the data grows one cannot keep on buying ever bigger, faster, and more expensive machines. Sharding as a strategy breaks the application database into smaller chunks called "shards" and spreads them across a number of distributed servers. The "Sharding" approach allows the application to scale linearly at a low cost as the data is distributed to multiple physical nodes and allows parallel data access.
11. Horizontal Scaling
In this Linear scalability approach the job of processing is spilt into multiple pieces and distributed among multiple compute nodes. More nodes can be added or removed in response to the surge or dip in traffic thus auto scaling the application to tackle the workload. If a node fails, the other nodes in the cluster take up the workload of the failed node thus adding fault tolerance to the application.
12. Stateless
It is important that the application is stateless for it to auto scale especially in a horizontal scaling approach. Being stateless, services can be easily scaled horizontally thus improving availability and tackle the surge in traffic by scaling automatically.
13. DNS Lookups
Reduce the number of DNS lookups needed to reach the application pages. This is especially true for those pages where the user expects the page to be high on performance. The less number of DNS lookups on the application pages the better your page download performance will be.
14. Commodity Systems
Use inexpensive commodity grade systems where possible so that if one of the systems goes down it is easy to replace it with another. This approach goes hand in hand with the scale out or the horizontal scaling approach and is more effective in a environment where there is hyper growth in the number of users of the system.
15. Asynchronous Communication
Asynchronous Communication is an integral ingredient in the recipe for scalable applications. In addition to asynchronous communication the application also needs to be developed such that it is asynchronous in behaviour. The problem with synchronous communication is that they stall the entire application’s execution as they wait for a response, which binds all the services and tiers together
resulting in cascading failures.
16. Containers
Running containers is less resource intensive then running Virtual Machines thus allowing you to add more computing workload onto the same server. Provisioning of new containers take a few seconds or less, thus the data center can react quickly in response to a spike in user activity. Containers are a cost effective solution. They can potentially help you to decrease your operating cost (less servers, less staff) and your development cost (develop for one consistent run-time environment) which could be a big factor when it comes to scalable applications.
