Best Practices for Building Scalable Applications

6 min read time
Best Practices for Building Scalable Applications

TLDR;

The Internet and web applications have enabled businesses to scale like never before. Previously, a business’s physical footprint restricted it to a particular market, and simple logistics limited the number of transactions per day. A similar company can now create web applications that serve a global audience and process thousands of concurrent transactions. But is this scale available to every business?

It’s easy to see the opportunity to access new global markets, but to take advantage of it, you need the right skills, resources, and methodology. If your business wants to scale up today, you must be able to build scalable applications. Scalable applications generally have three attributes.

  • They can scale to different servers worldwide to provide more capacity, lower latency, and resilience. 
  • They can scale in response to demand as traffic goes up or down. 
  • They can scale granularly based on specific needs, for example, at certain times of the day or year, in certain locations, or certain parts of the application that are in demand.

It is easier than ever to build and deploy scalable applications using cloud service providers. These enable application teams to scale data centers, platforms, and services globally using third-party infrastructure as a service. However, you cannot rely on scalable infrastructure to scale your business without first building scalable applications.

To start building scalable applications now, follow these best practices. 

Choose the right technology

Scalability must not be an afterthought. You need to consider scalability from the beginning when planning and designing your application.

The first step to a scalable application is to use the right technology. There are four essential components.

System Architecture 

Choose a system architecture that provides the simplest way to solve your scaling problems. If you need to use a mix of different architectures, explore and identify the issues and solutions for each system.

Many companies are busy migrating from monolithic architectures to microservices and serverless functions. Applications built from smaller disaggregated parts can scale efficiently, only scaling up the parts that are needed. 

However, it’s always important to choose the right system for you. Don’t assume that microservices and serverless functions are the best solutions to your problems. 

  1. Identify and understand the problems you need to solve.
  2. Identify the possible systems architectures.
  3. Identify and grade the different ways each architecture would address or affect the problem.
  4. Identify the costs, complexity, and internal knowledge of each architecture.
  5. Choose the architecture(s) with the best balance between effectiveness, cost, and simplicity.

Programming Languages 

Choose a programming language that supports your system architecture and enables high performance.

  1. Make a shortlist of possible programming languages.
  2. Grade how each language affects your system’s performance at scale.
  3. Grade how well each language interoperates with your other core services.
  4. Grade the library support for each language.
  5. Identify the costs, complexities, and internal knowledge/familiarity with each language.
  6. Choose the programming language with the best balance between effectiveness, cost, and ease of use.

Database

Choose a database that supports your scalability goals with the ability to handle communications, logging, and monitoring at scale.

Data is an often undervalued component in scalable applications. Not only do all systems rely on data for operation and processing, but the communication between systems, logging, and monitoring at scale generates unique data types that you need to consider. 

  1. Identify and understand your data needs and how they will change at a high scale.
  2. Identify the possible data technologies such as RDS, SQL, and NoSQL.
  3. Grade how well each data technology meets your data needs at scale.
  4. Identify the costs, complexities, interoperability, and internal knowledge of each data technology.
  5. Choose the data technology with the best balance between effectiveness, cost, and ease of implementation.

Communication

Choose communication systems that can scale with the rest of your application.

As systems scale, communication between systems scales too. Microservices architectures are especially problematic because they produce a massive increase in systems communication as they scale up. You must ensure that these communications channels are scalable.

You might have to use a loosely coupled system that will allow you to scale your services independently as and when the demand arises.

  1. Identify and understand your communication channels.
  2. Identify and understand how your system communication needs will change at a high scale.
  3. Identify any bottlenecks in your communication channels.
  4. Identify and implement solutions to those bottlenecks, considering scalable infrastructure such as load balancing.

Avoid single points of failure

Audit your entire system to identify any dependencies whose failure could affect the performance, reliability, or security of your application.

No application can scale reliably if it is dependent on other components or applications that cannot scale. These non-scaling dependencies can affect the scalability of your application. 

If one dependency can cause your application performance to drop or even go offline then it is a single point of failure. You must avoid this in your system architecture.

To find single points of failure, investigate each component in your application and broader system (including servers, databases, routers, and other network infrastructure) and determine how its failure affects your application. 

To correct single points of failure, replicate everything. 

  1. Add redundancy for every resource, every interface, every network path, and every power supply. 
  2. Run your database on multiple servers (preferably in different data centers and regions) so that even if one backend code backfires, the others can balance the load.
  3. Consider running your application in a multi-cloud deployment so that if one cloud suffers downtime you can shift application traffic to an available cloud.
  4. Deploy global server load balancing (GSLB) to distribute traffic to the healthiest locations with the best performance, lowest latency, and fewest errors. Ideally, your GSLB function will be capable of multi-cloud integration, traffic monitoring, and autoscaling.

You should also consider single points of failure in your team. If you only have one qualified SecOps team member, can you handle security incidents when they are on leave?

Implement security best practices

Follow best practices for application security at scale.

Security is essential in any software system. Scaling up will magnify any security flaws in your system.

However, maintaining security in applications that scale across many servers is complex. The complexity comes from the varying capabilities and vulnerabilities of the clouds and platforms you use, the growth in systems communication and the challenge of monitoring them, the difficulty of balancing strict access control with agility, and the increasing exposure to external threats.

  1. Design secure applications.
  2. Follow secure coding practices.
  3. Test your application security.
  4. Follow governance, risk, and compliance standards for your organization.
  5. Audit your clouds and platforms for security and identify vulnerabilities.
  6. Implement role-based access control and follow the least-privilege design principle.
  7. Deploy a scalable web application and API protection (WAAP) function to protect against external threats and monitor traffic and communications.

Offload functions from your application servers

Deploy additional infrastructure to handle loads that would otherwise run on your application servers, leaving your servers with more capacity to handle additional requests.

Application servers often handle loads that they don’t have to, including SSL/TLS termination, serving static content, and server-side rendering. You can offload these functions to other infrastructure or to edge/client devices.

  1. Offload SSL/TLS termination for HTTPS traffic to a load balancer or web accelerator.
  2. Cache static content on a web accelerator or in a content delivery network (CDN).
  3. Shift application processing to edge resources using an edge network, for example, an Edge-as-a-Service / hosted edge vendor. 
  4. Switch as much server-side logic or rendering as possible to client-side. To maintain security, only port the logic that is required to operate at a client level.
  5. Deploy a web application firewall (WAF) to secure traffic flows and prevent vulnerabilities from client-side processing.

Optimize your network architecture for performance

Identify and address performance bottlenecks in your network layer that could restrict your application delivery at scale.

Many application teams ignore the network layer when focusing on scalable app development. You should focus on optimizing network performance because communication needs for an application deployed at a large scale tend to be higher and more complex than internal systems.

  1. Monitor east-west traffic flows across system components and north-south traffic between your internal systems and external clients.
  2. Implement efficient routing patterns.
  3. Customize routing for localized needs and data protection regulations in different countries and regions.
  4. Optimize the network settings for your application environments for top-level performance.
  5. Cache data in between servers. Tune your cache systems to keep track of stale data and prevent bottlenecks when moving data around the caches.
  6. Deploy web acceleration to reduce bandwidth consumption, network requests, and latency.

Test for performance and scalability

Test your applications to see how well they perform under high-traffic conditions.

Even after you have designed and built your application, you must continually test its ability to handle load and scale. You need to make sure that your application provides a responsive user experience at scale, with no downtime.

  1. Run load testing to simulate high-scale traffic loads on your application. 
  2. Simulate realistic virtual users so that your application is put under a realistic load.
  3. Load test different parts of your application.
  4. Simulate different traffic scenarios including common and extreme scenarios.
  5. Identify your application’s capacity limits and bottlenecks.
  6. Fix as many bottlenecks as you can with your application architecture and code.
  7. Fix as many bottlenecks as you can in your network configuration.
  8. Deploy scalable load balancing to autoscale on-demand and manage the distribution of traffic loads as they scale up and down.

Conclusion

Building scalable applications requires more than technical know-how. Every member of your development and operations teams needs to adopt the right culture and mindset. 

These best practices should help everyone to embrace what it takes to build scalable applications that will help your business take full advantage of the opportunities now available.

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