Whether your business is e-commerce or a local coffee shop, you probably know that consumer expectations have never been higher. As a result, business owners are under immense pressure to align their services with the changing world and deliver a high-quality customer experience across in-person and digital platforms. Scaling software is absolutely essential to these efforts.
Unfortunately, businesses often encounter poor scalability when trying to improve critical applications, which decreases performance and hurts the user experience. How can you avoid this pitfall and efficiently scale your software to benefit your business operations while meeting customer demands?
Below we’ll give you the answers to effective software scalability and offer some best practices to get the most out of your software solutions.
What is software scalability?
Scalability involves a system’s ability to handle increased data loads without interruptions or reduced performance.
Scalability and elasticity are often used interchangeably in cloud computing, but the two terms mean very different things. While elasticity refers to a system’s ability to handle unexpected change in the short term, scalability is a long-term solution that helps your tech grow with the business.
Some scalability examples include:
- Increasing capacity
- Increasing functionality
- Better usability
- Adaptability
- Resource reduction
To fully understand software scalability, let’s discuss the principles that make scalability what it is.
- Maximum stored data: Does your platform include large amounts of unstructured data, like site reports, content, and marketing data? Data levels often rise unexpectedly as more users connect to your software, meaning your data capacity must be able to scale quickly.
- Code: Businesses are more than willing to pay big money for experienced developers, and for good reason. More inexperienced developers tend to overlook the quality of their coding, which results in inferior software scalability.
When developers code, they should keep scalability in mind because code should be deployed to enable it to be added to or changed without altering the original code. In other words, scaling software will involve reducing the size and complexity of the code involved. Keep it clean, and your software will be simpler to scale.
Bitly is a perfect example of scalable software. We provide businesses with link management solutions at scale. You can quickly and easily generate and customize all of the URLs you need.
Having software that allows your company to scale like ours ensures you can automate workflows via efficient APIs. Plus, our URL shortener is compatible with 700+ integrations!
Why is scalability important for businesses?
Scalability is important for both short- and long-term issues. Confronting scalability in issues that arise will empower your company to meet the needs and expectations of its paying customers over time. When getting a product to market, scaling allows companies to create what they need at that moment rather than including lots of irrelevant features and slowing production time.
Since the software is scalable, new features and functionality can be added as companies grow and customer needs change. This allows for a faster time to market and a smaller investment to get started.
Plus, scalability is all about relevance. With so much competition, staying alert and flexible in an evolving marketplace is crucial. Choosing scaling software as your solution will keep your brand in the game and ensure you can pivot and move as your customers do.
Opportunity cost is an important consideration in scalability. It’s defined as the loss of an opportunity when an alternative is chosen. In many ways, scalable products have a lower opportunity cost simply because of their close relationship with economies of scale.
By creating a more efficient software development process, your production costs will decrease as you continue to expand. Switching to more scalable development processes will also allow you to take advantage of economies of scale and reduce your opportunity costs, which ultimately improves your bottom line.
Types of scalability
Mobile app developers can scale their applications in multiple ways based on how they manage their resources. The two most common types of scaling in software development are vertical and horizontal.
Vertical scaling (scaling up)
Vertical scaling aims to increase the capacity of your existing systems to handle increased workloads efficiently. For example, you may add more power to your server by adding CPU, memory, or storage. Or you might replace an outdated server with a more powerful and sophisticated one.
Vertical scaling is beneficial because:
- It’s simple to implement.
- You don’t need extra components like switches, routers, or load balancing to scale up your solutions.
- It’s less expensive to upgrade your existing software systems than to add another machine.
- Inter-process communication is efficient and quick as there’s only one system.
Vertical scaling is a good option for small and medium-sized businesses with moderate plans for growth as it is less complex, but it may not be suitable for businesses with larger growth plans.
Horizontal Scaling (scaling out)
Horizontal scaling involves adding more machines and instances to your existing systems to ensure user demands are distributed and processed effectively. For example, you may consider scaling out a slow system by introducing a new, faster server.
Scaling out is advantageous because:
- It’s resilient to failure because the new nodes can pick up the slack if others fail.
- You can share workloads by implementing independent servers.
- It has less downtime period because you don’t have to deactivate a single node when scaling your solutions.
- It allows unlimited scaling of your systems.
Horizontal scaling is a go-to option when you can’t approximate the workload your software will need to handle in the future. It can also be considered if you have an application that requires quick scaling with no downtime.
Challenges in software scalability
It’s important to consider the consequences of failing to invest in scalable software solutions. At first glance, the weaknesses aren’t always obvious. In the early stages of your products, the workload is light, and the pressure on the system is negligible.
When only a few people are using a program or app simultaneously, you don’t immediately notice the workload issues.
As the strain builds up, the only solution becomes patches that add complexity and generally make diagnosing problems more difficult. While it can be done, it’s tedious, expensive, and ultimately less effective. Starting on the right foot is key to tackling scalability problems further down the line.
The following are common challenges you may face when scaling your software.
Data inconsistency
Data inconsistency can lead to variations in your application’s functionality or data presentation, affecting the user experience.
Data consistency becomes more vital as an application’s user base and transactions increase, so ensuring no data conflict across all nodes is important. But how do you prevent data inconsistencies in distributed systems? You can employ two common models: Eventual consistency and the CAP theorem.
Eventual consistency helps you to achieve scalability while upholding data integrity. This concept suggests that as long as no new updates exist on an entity, all accesses to that data item will retreat to the last updated version. With eventual consistency, you can scale out your systems by introducing more replicas and distributing the workload, as all updates will be processed separately on each replica.
Also known as Brewer’s Theorem, the CAP theorem suggests that distributed database systems can achieve only two desirable outcomes. That is:
- Consistency: Where users will access the same data simultaneously despite the nodes they connect to. To achieve this, you’ll need to replicate data written in a single node to all other nodes in the system.
- Availability: This means users will get a valid response to their requests from all functioning nodes in the distributed systems.
- Partition tolerance: A system must continue to work even if communication between the system nodes breaks down.
Database performance
Database performance focuses on a system’s effectiveness in responding to queries and transactions and is a major challenge in software scalability. For instance, read and write limits, indexing, and poor query performance may affect the entire system, limiting its ability to scale effectively.
Fortunately, you can improve database performance using methods such as:
- Database sharding: A horizontal scaling technique that allocates additional systems or nodes to share your application’s workload. Distributing data across shards improves query performance, increases availability, and enhances efficient utilization of resources.
- Replication: Data replication involves distributing data across multiple nodes to increase a system’s processing power and server performance.
- Using NoSQL Databases: Also known as non-SQL or not only SQL, this involves copying and storing data on different servers to improve availability and reliability. With the NoSQL database, data continues to run even if the others go offline.
Network issues
Network latency—the delay in data communication between a user’s device and your server—and bandwidth limitations can affect your scalability efforts. High latency means the transfer of data from its source to a desired destination will take longer.
This delay can affect the effectiveness of data-dependent software in real-time services like online gaming and VOIP. In addition, network latency can reduce the availability and reliability of network services that your operating systems depend on.
Bandwidth—the amount of data transferred over a network path in a certain time—can also affect software scalability. If limited, it can cause network congestion, especially when the user base increases, as your systems try to traverse the network they can handle. This may increase latency, leading to a slow response time and increased buffering.
There are several strategies you can employ to reduce latency:
- Content Delivery Networks (CDNs): CDNs store web content on diverse servers across multiple locations. When users send a request, they get content from the server near them, reducing latency rates.
- Microservices architecture: This strategy involves breaking applications into smaller, independent services so that each can perform a specified task. This means they can scale separately, allowing you to add or remove resources without interfering with the software application.
Best practices for implementing software scalability
As your business grows and your user base increases, it is important to ensure your software has the power to handle increased traffic. Its computing power should also align with your needs and customers’ demands.
So, how do you achieve this? Here are tips and best practices for scaling your software application.
Consider the architecture
Before you begin your scaling efforts, it’s vital to understand your software architecture. Figure out how components like microservices, serverless architecture, and event-driven models interact and identify possible bottlenecks.
Understanding these designs can help you choose the right scaling techniques to improve maintenance practices.
Focus on load balancing
Load balancing involves distributing the network across multiple servers that can handle the application to improve availability and ensure no single server is overwhelmed. If a server shuts down, a load balancer redirects its traffic to other nodes that can support these requests. The new system becomes part of the setup and begins to receive the requests.
There are two major types of load balancing you can consider, namely:
- Hardware load balancers require rack-and-stack hardware appliances to process and redirect traffic to multiple servers.
- Software load balancers: You can access these servers on managed third-party services or install them across different servers.
Cache efficiently
Caching helps reduce database load and improves your servers’ response time. For example, caching your frequently accessed data in a disk can reduce the number of requests processed by the server. This improves the server’s response time and increases scalability effectiveness.
Resource management
Managing computing resources is essential for dynamically allocating and reallocating resources based on current demand. Proper management also allows software applications to easily respond to changing workloads, preventing downtime while improving scalability.
You can also use orchestration tools to manage and scale containerized applications. Tools like Kubernetes allow you to distribute and run containerized apps across multiple servers easily. You simply identify the containers you want to run, and the tool will start and monitor them.
Monitor the metrics
Comprehensive monitoring and the use of metrics to track the performance and health of your applications as they scale are important. They help ensure that the software is responsive and its functionality is at its best, even as the user base increases.
Application performance monitoring tools like Prometheus and Grafana can help identify bottlenecks affecting your scalability efforts and guide your scaling decisions.
Scale successfully with strategic insights with Bitly
Since scalable systems will still be relevant and cutting-edge years down the line, you need to make your products compatible with the changing world. Understanding the challenges and best practices for software scalability can increase the effectiveness of your efforts.
Bitly can help with your scaling challenges. Our services allow you to manage large volumes of data and links directly from the platform, making your scalability strategies less overwhelming.
Ready to explore our services and how to integrate them into your scalability planning? Get started with Bitly today!
