In the early development stages, software product scalability isn’t usually a top priority for developers—in the beginning, they focus on the software’s ability to solve tasks fast. But after it gets tested by real users and becomes successful, it’s time for developers to shift their efforts toward scaling the software product—a process much needed to secure one’s place in the market and grow even further. The question is: how to do it effectively?
At Acropolium, scaling is one of the solutions we offer as a part of the development package or a standalone service. While it’s generally a necessary step for the product after its validation, the scaling strategy and process will vary based on the given product type, your business needs, budget, and other factors.
Yes, we know a thing or two about software product scalability, and that’s why in this article, we’ll review what scalability is, why it matters in the highly-digitilized world, and what to consider when starting with your scaling strategy.
What does software product scaling mean?
Software product scalability is the quality of the product to manage the growing requests and demands from any given number of users flexibly. Simply put, it’s the ability of software to respond to changing needs whenever they occur, regardless of their volume.
Take a scuba diving application as an example.
You’ve hired the best team that built the app, tested all the features with real users, and launched it. Since the software is user-friendly and solves scuba divers’ problems fast, it attracts new users and, as a result, receives more data to operate.
Meanwhile, your system was designed to serve a certain amount of requests and process a particular amount of data. Once these limitations are reached, the whole system’s performance will be compromised unless you scale your software product.
In this scenario, scaling your product may mean adding more storage, improving data transmission, or introducing new features, so the app works efficiently under the new market conditions. In general, it means creating a flexible architecture that is ready to cover the anticipated demands and adapt quickly to the unexpected ones.
But how can you do that? How do you scale a digital product? There are several ways to approach scaling.
Read also: 10 Strategies to Scale your SaaS.
Main types of software product scaling
Widening the product’s target audience inevitably incurs more software users and, consequently, the need for more resources to maintain swift system performance. There are two main types of software scaling: vertical (or scale-up) and horizontal (or scale-out). Here’s how they work and differ.
When you opt for vertical scaling, you add more potent hardware to ensure the system’s ability to holp up. It usually means increasing CPU or RAM to cope with the workload.
There are several factors to consider before choosing this approach:
- Hardware usually has limitations that can’t be reconfigured
- Adding more potent hardware requires huge costs upfront
- Connecting the system with a new server takes time and may need the system to shut down
- Higher risk of a single point of failure (SPOF): if the machinery is out of order, nothing will work
- If the volume is miscalculated, the money spent on such scaling will be spent in vain
Vertical scaling might be useful if you know the volume of tasks the system should take care of. Unfortunately, this might not always be the case in a fast-changing market. That’s why there’s another approach.
Scaling digital products horizontally means creating an architecture where the workload will be evenly distributed among the existing servers by the load balancer. So if we switch to a more powerful machine in vertical scaling, in the horizontal one, we add more machines to do the work.
Here’s what you need to know about this approach.
- Horizontal product scaling is more flexible as it allows to scale in and out with technologies like Kubernetes, OpenShift, Docker, etc.
- With more machines, it’s possible to configure a backup and prevent SPOF (if one server dies, the workload will be distributed among others, and the system will remain available to the users)
- Horizontal scaling requires robust and well-managed computer infrastructure with load balancers, sharding plugins, etc.
- The cost of the load balancer will grow proportionally to the request load and data to be processed.
- It’s easier to introduce new features to the systems as it’s possible to change a part of the software while keeping others up and running with minimal downtime, bottlenecks, and latencies.
Whichever approach you choose for creating a scalable software product, you need to align it with your long-term scaling strategy and consider market conditions and users’ expectations beforehand.
Read also: How to build and scale multitenant SaaS
Why is it important to scale software products?
The benefits of product scaling are plenty: from cutting expenses on maintenance to ensuring the software‘s ability to serve growing demands. But that’s just a part of the story. Here are a few more things about the importance of scalability for the product and business success.
- Scalability is essential for market expansion. If you want your product to be popular with more users in the long-term perspective, you need to make it better than your competitors’ and foresee the user’s pains and needs. As these problems and requirements evolve, you’ll need to adjust your product accordingly, introduce new features, and optimize the performance. All that is hard to do with a monolithic, inflexible architecture.
- It saves money. No business owner wants to pay for idle resources. Scaling allows creating an easily manageable architecture that can switch resources on and off on demand.
- Software scalability ensures a better user experience. Aligning the product’s performance and functionality with the user’s needs is a step zero for winning clients fast. Continuous software improvement does even more: it creates a positive user experience, sets a high bar for the competition, and gives the clients confidence. Scalability secures the ability to adjust the product with little to no performance interruption.
- It’s a working strategy to manage bottlenecks and avoid cascading failure. The road to software hell is paved with bottlenecks, which cause downtimes, latencies, and even system crash. For example, overwhelming a database with the number of requests it wasn’t designed for slows down or even disables other database-dependent processes. With a scalable product, you can manage the system’s capacity fast to ensure even workload distribution and proper functioning of the dependent processes. The result? Fewer bottlenecks.
So, is there a point when you need to focus on the scaling strategy? Yes, and it has something to do with your business perspective, too.
When to scale your software product?
Building scalable systems runs in the back of every experienced developer’s head because they know no business owner wants to remain a startup forever. That’s why they will offer scaling-friendly solutions to save time and money. But the need for product scaling isn’t only a matter of growth—it’s a matter of keeping the system flexible and easily adjustable.
Here are some typical cases when it’s time to scale:
- You expect more users. When you plan any marketing campaign, you anticipate an influx of clients, and you need your software to hold up the new volume of visitors. It won’t be a problem for a scalable system to increase capacity based on the new workload, whereas the unscalable one will cause performance inefficiencies.
- You want to add resource-consuming features. Resources operate within their limits. If you add features that require, for example, more CPU, the performance of the reliant ones will be influenced. It may cause delays, buffering, and various response failures.
- You need to improve the user experience. And this is usually done by introducing new features and optimizing memory and data usage so that the clients would enjoy a swift performance. Their fast and successful integration is possible with flexible system architecture.
- The system has bottlenecks. They indicate that the workload isn’t evenly distributed, or some centers need more resources to process requests. In this case, scaling is necessary to balance the workload distribution and track the downstream processes to avoid further bottlenecks.
- The services become slow. There can be plenty of reasons for slow performance: memory issues, irresponsive database, poorly configured or integrated technologies, more workload that the system is capable of processing, and so on. Scaling your product will help distribute the workload evenly and point at the weak spots in the architecture that need to be solved.
- You want to optimize the data layer and manage the load on your database. Since the data layer lies at the heart of any operation, its distribution can make the processes faster or cause temporary system unavailability. Scaling involves the distribution and partition of data, making it easier to organize and optimize data use and storage.
When you see it’s time to scale, you need to understand what can be scaled and how to prepare the software architecture for the process. This will be helpful for assessing the scaling priorities and results.
What are software scalability measurements?
Four major aspects should be considered during the development of a scalable system.
- Scalability of performance. More users require better performance of the system, so adding more capacity will make the software more potent. On the one hand, it will enable the introduction of new features. On the other hand, it may entail additional resources on the users’ end (system performance, memory/battery usage, etc.). Balancing these issues should be a part of your scalability plan.
- Scalability of availability. The strong performance of one feature often comes at the expense of the other. You need to choose the priority between consistency, availability, and partition tolerance. For instance, would you prefer your users to see some updates immediately or the full set over time?
- Scalability of maintenance. Scaling implies the use of more resources and technologies that will need more maintenance. When scaling your software, you should prepare a new maintenance plan and budget so you will be able to address a larger volume of possible issues.
- Scalability of expenditure. Scaling your digital product may include development from scratch or the use of pre-built solutions that are easy to configure and maintain. In the first case, you’ll have more customization freedom at higher costs, while in the second, you will save money and time for somewhat standardized solutions.
Now you know what scalability is and the many aspects to consider when creating a working scaling strategy. Now, it’s time to learn how to make software scalable.
How to scale your software product: 9 working tips
While the final choice of steps will depend heavily on specific product types, existing architecture, and business objectives, there are general tips to consider. Some represent the developing point of view (technology choice, patterns, etc.), while others represent operations (caching, choice of horizontal or vertical scaling, etc.).
Avoid a single point of failure
A single point of failure (SPOF) is the first thing to avoid during scaling, as the dysfunction of one such component stops the entire system. It’s important to eliminate such weak spots to ensure consistency and continuity of service delivery. To achieve the latter, you should split the architecture into smaller, manageable, and more independent parts. Luckily, this approach lies at the core of software program scaling.
Scale out instead of scaling up
While horizontal scaling has its benefits (greater compliance, on-premise control), the capacity of scaling up is limited. We suggest going with the scale-out approach, where you can start small and gradually build up your system. This is particularly useful if you deal with cloud-based SaaS products or want to move your product to the cloud. Here’s why:
- Cloud allows for smooth microservice organization, where you can localize and fix issues independently while having the other functions available for the users
- It prevents overspending on unused resources
- There are plenty of tools that estimate the use of each service, so it makes optimization transparent and easy.
Opting for cloud solutions while scaling will help you organize and modernize your solution and secure its market vitality as the cloud becomes more popular and affordable.
Use the right architecture pattern
The architecture pattern of your product will dictate a lot of scaling solutions. Here’s the list of popular patterns based on the operational logic.
- Layered (n-tier): the data flows from the innermost layer (database) to the topmost (data task).
- Event-driven: one agent distributes the input data to different modules for them to perform specific tasks.
- Microservice: a set of services that run independently of each other on different servers.
- Microkernel: a pattern that is best fit for repetitive operations that are stored in the microkernel and are executed repeatedly.
- Space-based: pattern in which processing logic focuses on reaching the shards of databases stored on various servers.
The choice of architecture pattern depends on the product type and what will have the most workload in the process.
Identify the metrics to track scalability
Since scalability has various aspects, you need to decide how you will track and measure the changes that occur due to scaling. You can measure the CPU and memory usage, network and disc inputs and outputs, latency duration, etc. Plenty of monitoring tools for application performance (APM tools like Traceview, NewRelic, and others) will power you with these insights.
Choose the necessary cloud computing type and APIs
Depending on the product needs, there are several models of adding computing capacity: Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), or Mobile-Backend-as-a-Service (MBaaS).
- IaaS. This computing infrastructure offers cloud-based servers, networking, operating systems, and storage. You can buy it on-demand and as-needed instead of spending outright on the hardware.
- PaaS. In this case, you get a developing platform for creating software (including framework and runtime environments). This is useful when you want to customize your product and plan on using APIs.
- MBaaS. This is an option for managing the mobile backend and enabling certain features without their development. It’s widely used for mobile application development based on the website infrastructure.
The choice of mBaaS will be based on how you plan to approach automation and whether you need to integrate custom solutions. APIs will help you configure and connect the already developed parts, so you don’t have to spend time and budget on reinventing the wheel.
Go with client-side sessions rather than server-side ones
Pushing the work to the clients means sending fewer requests to the servers. For example, instead of starting server-side sessions for authentications, you can use client cookies and JSON Web Token (JWT).
Use caching to improve scalability
The caching technique works perfectly when the task is to prevent bottlenecks during expensive or repetitive database queries, or page renders. Switching the processing logic from searching in the database to searching in the cache first will buy the capacity of the database as it won’t be involved in handling every data request. Plus, searching in cache takes less time, and speed is something all users like in software.
Use the right databases to achieve scalability
There are two main types of databases: relational database management systems (RDBMS or SQL) and non-relational (NoSQL). The difference is that in relational DBs, data is connected, so every search query happens to be a complex task. In NoSQL, however, data is disconnected, and searching takes less time. Monolithic applications tend to choose RDBMS to make one-point access to the data, but in terms of scaling, NoSQL databases are more useful as they allow data sharding for faster query response.
Make the right choice of technologies
If you want to build a scalable product, you should go with the technologies that support scalability approaches from scratch. It includes choosing popular libraries, apt search algorithms, asynchronous codes that push non-critical tasks to the background, and so on.
What questions should you ask before scaling? [Bonus List]
To create an effective scaling strategy, you need to consider a lot of factors to collect a full picture. Answering specific questions will help you see the proper perspective on your scaling journey.
- What is the expected volume of users to access the system simultaneously for online and batch transactions now, in one year, and in three years?
- What is the peak concurrency access to the system?
- How much data should your system be able to manage?
- What is the number of reads and writes per second?
- What data can be cached?
- In what cases will data synchronization and asynchronization be most helpful?
- What operations will be CPU-intensive?
- What tools will be used to measure the system performance?
- Is there a need and opportunity to run batch operations at non-peak times?
- Is there an option to auto-provision additional servers on-demand?
Answering these questions will help you create an architecture that will be easily manageable and monitored.
At Acropolium, scalability and modernization approaches go hand in hand, and the cases below exemplify it.
One of our clients, a building and construction enterprise, contacted us regarding their construction management platform. They needed us to enable cooperation with the remote tech vendor despite the time zone difference and prepare the platform for new features development. To remove miscommunication, we had to migrate several modules to new technologies and optimize the current software parts. As a result, the development efficiency of the distributed team increased by 73%, and the influx of new clients by 22%.
In the case of a biotech client, we needed to adjust the SaaS architecture to make the workflows more manageable and distribute the workload to avoid bottlenecks. As a result of the architecture changes, client-to-client and client-to-vendor communication was streamlined, which attracted 30% of new clients. In addition to that, the system’s heavy load capacity increased by 57%.
Scaling a software product ensures growth and success, creating conditions for tapping into other markets and reaching new audiences. But it’s not an easy task. With many peculiarities and factors to consider, you need skilled and reliable tech experts to ensure consistency and prevent downstream bottlenecks. Acropolium can help.
We know how to deploy technologies and techniques that are used during the scaling process, such as cloud computing, DevOps, software modernization services, and others. Additionally, working with various industries gave us a lot of valuable insights into their needs, requirements, and user expectations. And we’re happy to use this knowledge and expertise while scaling your products. Contact our team, and let’s talk about the bright future of your software!