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Designing and Developing Hyper-Scalable Software Applications from the Ground Up

About Author: Anchal Katyal has more than ten years of experience in software engineering. She specializes in developing large-scale software applications and is known for her leadership in technology with a startup mentality and strong organizational management skills. Anchal has led and developed significant software projects from conception to completion.

In today’s rapidly evolving digital landscape, building scalable services is imperative for businesses to thrive and maintain a competitive edge. With the global internet user base projected to reach a staggering 6.13 billion by 2028[1], and internet traffic anticipated to grow at a compound annual growth rate of 19-23%, enterprises must be prepared to accommodate this exponential growth seamlessly.

Scalability is no longer a mere buzzword but a strategic necessity that can make or break a business’s success in this dynamic market. The importance of scalable software applications was particularly evident during the COVID-19 pandemic, when businesses and individuals were forced to shift their operations and activities online overnight. This sudden and unprecedented surge in digital demand had immense pressure on existing systems and infrastructure. Companies with scalable services were able to rapidly adapt and accommodate the influx of users, ensuring continuity or at least minimized disruptions.

A well-designed software application delivers on exceptional functionality, seamless user interface and can handle increasing number of users and traffic efficiently. Even if an application’s initial user base is modest, the fundamental architectural and design choices made during development can future-proof an application, enabling scalability to support millions and billions of users and minimizing need for costly and disruptive ground up re-designs. Prior to delving into the intricacies of developing hyper-scalable applications, it is imperative that we first comprehend the fundamental concept of application scalability and the significance of adopting ‘working backwards from the objective’ mindset.

What is scalability for applications?

An application’s scalability refers to its capability to gracefully handle and adapt to growing user traffic and increased concurrent load, ensuring consistent performance and responsiveness without experiencing slowdowns, delays and interruptions. Scalability is an application’s ability to handle workload variation while adding or removing users with minimal costs. So, a scalable solution is expected to remain stable and maintain its performance after a steep workload increase, whether expected or spontaneous.[2]

Working backwards from the objective

Instead of being focused on just building features and application to meet short-term functional needs, it is crucial to thing backwards from desired end result or ultimate outcome and vision of business. Envision scenarios like “3 years from now, I want my application to handle 10M+ daily users” or “Business demands my application to gracefully handle spiky user traffic.” Keeping these end goals in perspective will enable you to make informed trade-offs during the design phase to choose technologies and lay out architecture which can be extended to support increased scale. This ‘working backward & thinking forward’ mindset may require initial time investment, but will pay dividends in the long run by ensuring your application can gracefully handle user growth and traffic spikes without compromising performance or creating outages, and no to less engineering investment to redesign and rebuilt application as usage increases.

Best Practices for building hyper-scale applications

  1. Design with Fault Tolerance: Assume that failures or faults will happen and design your applications to be resilient. Leverage Auto Scaling, Elastic compute and load balancers for high availability.[3][4]
  2. Event-Driven Architecture: Using services like SQS (Simple Queue Service) or other message queuing services can enable individual components to scale independently. For example: If the website hits sudden traffic, one can add parallel queues to process messages in a gracefully and timely manner.[5]
  3. Modularize application: Breaking down application business logic processing into subcomponents is key. Use services like Lambda to process small sub-problem of business logic, use cache store or database to store intermediate results and tie the complete logic processing using step functions. This model work great when you want to change core business logic to support scale without the need of redesign.
  4. Utilizing managed services: Using services like DynamoDB, Redshift CloudWatch logs, S3 and Content Delivery Network (CDN)[6] to offload operations and focus on building core components of your application. By leveraging such services, you can have a head-start in building applications and later enable them with auto-scaling to support increased scale.
  5. Enable Caching: One of the most expensive operations within any application is read & writes to databases, as the data needs to be consistent. Using mechanisms like ElasticCache[7] to store intermediate steps can reduce the overall load on your database and improve application performance.
  6. Monitoring and Alarming: Continuously monitoring application performance can help drive improvement and optimization. Use technologies like CloudWatch[8] or other Application Performance Monitoring (APM) tools and enable alarm threshold to alert when breached. In doing so, you can determine a baseline for you application performance and invest on optimizations when thresholds are breached.
  7. Optimize where necessary: During development it’s easy to prioritize feature enhancement over scalable optimizations, but when the foundational technologies and practices are implemented accurately, it becomes easy identify bottlenecks in your application and scale those components as need arises.

Conclusion

Determining the scalability strategy for your software application should be a proactive decision, made well ahead of time as it’s impossible to predict when your application might face a surge in traffic or demand that necessitates scaling up.
Often the time to react or adapt to sudden traffic increase is very short and failure to do so can result in outages, impacting customer trust and business success & objectives. Designing scalable applications onset involves vision, time, effort and investment. Implementing these best practices will help avoid expensive re-architecture & rebuild at later stages, enabling your application to handle growth while ensuring reliability resulting into compelling customer experience.

References

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  1. https://www.dailyhostnews.com/internet-users-worldwide-will-exceed-6-billion-in-the-next-five-years
  2. https://itrexgroup.com/blog/what-is-software-scalability/
  3. https://docs.huihoo.com/amazon/aws/whitepapers/AWS-Cloud-Best-Practices-January-2011.pdf
  4. https://www.simform.com/blog/building-scalable-application-aws-platform/
  5. https://zeet.co/blog/how-event-driven-architecture-enables-horizontally-scaling-systems
  6. https://www.wearediagram.com/blog/how-to-infinitely-scale-your-website-using-a-cdn
  7. https://www.gomomento.com/blog/best-practices-for-elasticache-redis-autoscaling-and-how-to-do-better/
  8. https://bluexp.netapp.com/blog/aws-blg-aws-monitoring-tools-and-best-practices-monitor-what-matters
  9. https://learn.saylor.org/mod/page/view.php?id=61349

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