Fact: The average mobile app loses 77% of daily active users within the first three days of installation. The reasons are many, but one is quite simple: flaky app performance at high traffic loads. In other words, the developer failed to use application scalability to take their app from MVP to industry success.
When an app’s workload is light, the demand on its backend is low and performance is stable. But as the number of concurrent users grows, so does the strain on the software architecture. If you don’t prepare your app for this through scalability, performance degrades, leading to user abandonment.
In this article, we’ll share the main app scaling strategies, their benefits, and tips to help you prepare for app development growth.
But first, let’s look at what scaling and application scalability mean in practice.
What Is Application Scaling?
Scalability is an application's ability to handle increased workload or user demand—i.e., higher traffic, more data storage, or greater computation requirements—without compromising performance. Simply put, when an app has good application scalability, it can grow when needed.
Here are some common signs that it’s time to consider scaling your app.
- Performance issues are on the rise. Slow load times, frequent timeouts, or system errors are all indications that your app is struggling with workload.
- Your resources are regularly working at peak (or near-peak) capacity. An infrastructure operating at its limits (for example, at maximum CPU, memory, storage, or network usage) can lead to more frequent downtime and sluggish performance.
- You have higher traffic peaks and/or network latency. Higher latency at higher user loads may signify that your application has outgrown your infrastructure capabilities, leading to service degradation.
- You’re scaling overall. If you plan to introduce new features or enter new markets, app scaling is essential for meeting increased demand and supporting business growth.
Even if you’re not in these situations yet, you still risk running short of request processing capacity as your user base grows. Performance and scalability testing will help you identify the maximum load your current application can handle and its scaling potential.
Once you've done that, it’s time to decide how to scale your application. And that’s where adopting one or a combination of scaling technics can come in handy.
Application Scaling Techniques and Strategies
Scaling applications primarily focuses on changing backend infrastructure. There are two main approaches.
- Vertical scaling (scaling up). As the name suggests, this involves increasing the capacity of the individual servers or machines that host the application, for example, by adding more powerful CPUs, increasing RAM, or expanding storage.
- Horizontal scaling (scaling out). With this approach, the application is deployed on multiple servers behind a load balancer that evenly distributes concurrent incoming requests. This allows for better resource utilization and improves fault tolerance.
The advantage of vertical scaling is that it doesn’t require changes to the application code—the same code just runs on a more powerful server. This works well when you need to scale fast to cope with traffic spikes. However, in the long run, vertical scaling can paint you into a corner when you hit a limit and can’t scale up anymore.
Conversely, horizontal scaling is ultimately more flexible, but it implies higher development costs and often more work to ensure data consistency.
Choosing the right application scalability approach is key to protecting both your budget and growth potential. A poor choice can lead to overspending—or worse, losing your users because of poor performance.
The solution to this problem is elastic scaling. It allows the application to automatically adjust its resource usage based on real-time demand. By leveraging cloud-based infrastructure, elastic scaling lets you dynamically add or remove resources in response to traffic fluctuations. This ensures optimal performance and cost efficiency.
Once your strategy is clear, you need to choose the techniques to implement it. Here are the main options.
Caching improves application performance by delivering content to clients faster. It involves storing frequently accessed data directly in RAM instead of fetching it from the server whenever needed.
Depending on your app specifics, you have two options:
- Static caching of fixed content
- Dynamic caching of generated or personalized content based on user interactions or specific requests (e.g., a social media feed)
Caching can significantly improve application performance by reducing the need for repetitive data retrieval or computation, especially for read-heavy workloads.
Another way to improve scalability is with container orchestration platforms such as Docker, Kubernetes, or Apache Mesos. They allow applications to be packaged with their dependencies and run consistently across different environments.
Container orchestration platforms can monitor application performance metrics such as CPU, memory usage, and network traffic and automatically adjust the number of running containers or instances to meet demand. This ensures the application can handle varying workloads efficiently, which contributes to optimal performance.
Many container orchestration platforms also have built-in load-balancing mechanisms that evenly distribute incoming traffic across multiple containers or application instances. This helps prevent the overloading of specific containers or nodes.
Sharding is a database optimization strategy that splits a database into smaller parts (shards) containing a portion of the data. Each shard can handle data queries, enabling faster and more efficient access and storage. What’s more, each shard can be independently scaled to accommodate additional data or traffic.
As a result, sharding helps you distribute workload across multiple machines and improves database performance and scalability.
At a basic level, you can scale manually by adding or removing resources such as CPU, memory, or storage based on current or anticipated traffic. Manual application scaling relies on system administrators who constantly monitor application performance and make adjustments to ensure optimal resource utilization.
Auto-scaling doesn’t require human intervention. It dynamically adjusts resource capacity based on predefined rules or thresholds such as CPU utilization, memory usage, or network traffic. This makes applications more responsive to changing conditions and can help ensure optimal performance and cost efficiency.
Content Delivery Network (CDN) implementation
CDNs play a crucial role in scaling applications by offloading the burden from the origin server. CDNs are geographically dispersed servers that cache API requests and content to reduce network latency and the distance between client requests and servers. As a result, apps enjoy higher performance and improved availability.
During traffic spikes, a CDN automatically scales to handle increased demand. The network’s distributed nature allows it to control sudden surges in user traffic by dynamically adding more edge servers or increasing server resources. Thanks to CDN implementation, you can optimize an app's performance and efficiently handle growing user demands without significant infrastructure upgrades.
Now that we’ve seen how app scaling works, let’s uncover the benefits it can bring to your business.
What Are the Advantages of Scaling Applications?
Here are some benefits of ensuring application scalability.
A better user experience
If your backend lacks server power to handle the app demands, the app may become unresponsive or fail to deliver content efficiently. This leads to service unavailability, slow performance, downtime, and poor user experience.
Scaling mobile apps lets you deliver a smooth and responsive user experience even during peak usage periods. With improved performance and quick response times, users are more likely to stay engaged and enjoy using the application.
It makes sense to start with a small infrastructure for your MVP launch. But building it with scalability in mind lets you allocate more resources easily as your app matures. Without this, you’ll face the costs of restructuring your code and architecture further down the line.
Scaling application resources improves overall stability by distributing workloads across multiple servers or instances. With a distributed architecture, if one server fails, other instances can handle the workload, thus reducing the risk of application downtime.
Scaling often involves adopting a service-based architecture where features are delivered as independent services (microservices). These services can be developed and updated separately, which makes it easier to customize or add new features without disrupting the entire application.
Better app performance
In a scalable and distributed environment, an application can process multiple requests in parallel across servers. This increases the throughput and reduces the time taken to complete tasks. Scaling minimizes bottlenecks and ensures faster response times, improved load times, and better performance. As a result, applications can handle increased workloads and surges more efficiently.
A scalable application infrastructure ensures that your organization will continue to meet the demands of its customer base. Scalability also gives you a safety net for unforeseen circumstances like a change of business direction, as an app can more easily adapt to new requirements.
All these benefits make a compelling case for including application scaling in your development plan. Yet, integrating scalability also has its challenges. Understanding the possible roadblocks will help you effectively address them.
App Scalability Challenges
Here are some challenges you may encounter when planning to scale an application.
Unscalability of existing architecture
Applications with monolithic or poorly designed architecture, reliance on legacy technologies, and tight coupling of components can be challenging to scale without significant rework or performance degradation.
The typical solution is migrating to microservices or a service-oriented architecture, which allows you to deploy, scale, and manage all application components independently.
As an application processes more data, ensuring consistency becomes more challenging. This is especially true for distributed systems, where different versions of the same information can end up being stored on different servers. This results in outdated information and conflicting values.
To tackle this, it’s essential to implement effective data synchronization. Adopting suitable database architectures, implementing distributed consensus protocols, and employing conflict resolution mechanisms can all help ensure data consistency across application components.
Limitations in computing power, memory, storage, or network bandwidth can all affect an application’s scalability. For instance, insufficient resources can cause degradation in application performance during peak usage periods.
To avoid problems, you need to continuously monitor resource usage and be ready to optimize it according to demand. Investing in a scalable and well-provisioned cloud infrastructure can offer you more flexibility in resource allocation.
As an application scales, it exposes a larger attack surface, increasing the risk of security breaches. Malicious actors can attempt to exploit weaknesses in the application's code, infrastructure, or data handling processes.
To enhance security, it’s essential to:
- Follow secure coding practices
- Make regular security assessments
- Conduct strict penetration testing
- Implement strong authentication and authorization mechanisms
- Ensure all third-party software is up-to-date to patch known vulnerabilities
These steps help to protect an application and its users from potential cyber threats.
Adopting one or several scaling methods will inevitably incur additional licensing or subscription costs. However the costs of ignoring a scaling strategy are generally higher, as you risk over-provisioning resources and unnecessary expenses—or worse, under-provisioning and performance issues.
To manage costs effectively, your company should carefully plan its scaling strategy based on actual usage patterns and adjust it to balance performance and cost efficiency.
Successfully addressing all of these scalability challenges requires a comprehensive understanding of application architecture and requirements, proactive planning, and ongoing monitoring as a product grows. This is where partnering with a reliable software development company can make a difference.
Let’s see how it works with an example of scalability implementation at Techstack.
A US startup approached Techstack with the idea of developing web and mobile applications for virtual fundraising. They wanted to use our mobile app development services to create an MVP and drive continuous growth through hypothesis testing. For this, the company needed a scalable and resilient architecture capable of handling high traffic loads. Our experts developed an MVP within two weeks using React Native and Storybook. When the application started to gain user traction, Techstack transitioned the entire backend to React, allowing for code sharing between the website and the application. The scalable architecture developed by Techstack has continued to support the product for over seven years during its transition from MVP to exponential growth. The mobile app now has over 1,000,000 downloads, indicating its popularity among users.
Scaling becomes necessary as your mobile app gains popularity. While a strong concept captures user attention, scalability keeps them with you in a highly competitive market. Building your MVP with scalability in mind is key for future-proofing your application and preparing it to grow seamlessly with your user base.
Scaling applications brings cost optimization, improved performance, and long-term growth prospects, but it takes technical expertise to overcome the challenges. At Techstack, we have your back. Contact us to discuss how we can help scale your product starting today.