People aren’t as patient as they once were. Back in the day, waiting 10 seconds for a website to load wasn’t particularly unusual. Nowadays, though, anything less than an instant response may push users—and I include both customers and employees in that category—to rage and quit your solution.
So, applications must handle whatever users throw, especially peak loads. After all, by definition, this is the point at which your system is exposed to the most users, and you have the most to lose.
Different Businesses Experience Different Peaks
Often, when non-techies think about peak periods, it’s with a retail focus. However, as we all know, it’s not just ticket sellers or Black Friday retailers who need to worry about usage spikes.
- Operational surges (e.g. submitting timesheets or cashing up)
- High-volume periods (e.g. university results or clearing processes)
- Simultaneous login events (e.g. start of the day or after service interruptions)
In fact, most businesses experience periods when their solutions experience higher-than-average volumes, and a solution failure or even a slowdown at this time is bad news for sales, customer experience or employee productivity.
Obviously, this isn’t exactly breaking news; every business knows when its peak volumes are coming and roughly what its systems need to handle. So, what can they do to help scalability?
A Common Approach Is To Bulk Up Your Tin
A common approach is to throw more tin (or cloud) at your solution. The high-level process goes something like this… do some math, factor in some scalability, beef up your system where required, and keep your fingers crossed.
And you know what? This can work. But it leaves a hell of a lot to chance, and no amount of computing power can remedy defective code. It may have worked before, but that does not mean it will work every time because you can bet that something will have changed, and the tiniest something might prove to be the limiting factor.
It’s a bit like playing Russian roulette. You might get away with it a few times, but eventually, something will go bang, and it won’t end well.
Plus, I have seen applications degrade significantly at 40% CPU utilisation, as CPU is not the only hardware constraint. Also, how do you know what will happen when extra hardware is thrown at the problem without testing?
To handle the extra load, do you need the high-performance engine from an Aston Martin to drive the application faster or the brute force of a JCB? In other words:
- Vertical Scaling: Will the application respond to more advanced and faster processors?
- Horizontal Scaling: Does it need multiple computers with load balancing?
Think of a supermarket checkout. Do you to increase the speed that items can go through the checkout or open more checkouts? Increasing speed works for low volume but doesn’t work when volumes are high; it just creates a bottleneck.
Or You Could Scale Effectively with Performance Testing and Analysis
Performance testing is a much better, albeit less Hollywood, way to prepare for peak load conditions.
By performance testing, I don’t mean just throwing load at a system to see what it can handle.
I mean:
- Using sophisticated tooling to replicate high volumes of user activity
- Understanding how the hardware and application perform under normal and increasing load
- Actively monitoring the in-flight behaviour of the individual process steps
- Analysing comprehensive post-execution results
- Assessing if and where there are bottlenecks
- Implementing remedial measures
- Testing again to prove it has resolved the problems
Performance Testing is Much Easier Than It Used to Be
I’ve been in software development for over three decades, and I appreciate that running a performance test isn’t trivial.
However, while it still requires planning and collaboration, it is nowhere near as arduous as it once was. A big reason is that you no longer need to invest time and effort in acquiring and setting performance lab hardware as it used to, proving that you chose the right tool.
Why Open-Source Performance Testing Tools Are Not The Answer
While potentially useful (and that is me being incredibly kind) for smaller-scale testing, most popular open-source tools like JMeter fall short when dealing with enterprise-level load requirements, never mind high-volume tests. It’s not impossible, but it’s not exactly straightforward or robust.
- Hardware Requirements: These tools often demand substantial hardware resources to generate high loads, requiring organisations to invest in and maintain expensive infrastructure.
- Manual Configuration: Setting up and configuring open-source tools can be time-consuming and complex, often requiring specialised expertise.
- Scalability Challenges: Generating truly high volumes of load is difficult or impractical with open-source solutions, limiting the scope of scalability testing.
- Analysis and reporting is poor
Set Up Performance Testing Quickly and Easily with LoadRunner Cloud
LoadRunner Cloud remains the tool of choice for medium to large enterprises that need to scale significantly.
As a cloud-based service, LoadRunner Cloud removes the need for on-premises infrastructure and utilises cloud-based load generators. You can scale to your heart’s content without troubling your IT team or worrying about SLAs.
Teams can access the platform from anywhere, enhancing collaboration and flexibility and it is ready for almost immediate use.
Also, the Virtual User Hours (VUH) licensing model in LoadRunner Cloud offers significant advantages:
- Cost-Effective High-Volume Testing: Organisations can run large-scale tests without permanent investment in high numbers of virtual users.
- On-Demand Scaling: Easily increase test capacity for peak periods or specific high-load scenarios.
- Budget Optimisation: Only pay for the actual testing time needed.
It offers several other key advantages, including:
- Enterprise-Grade Scalability: LoadRunner will easily handle a few thousand users as its nominal limit is 5,000,000 concurrent users, which is truly staggering.
- Comprehensive Analysis Tools: In-depth performance metrics and analytics for real-time on-the-fly analysis and post-test examinations.
- Cross-System Testing: It supports more protocols and applications than any other test tool, allowing scalability testing across complex, interconnected systems.
- Realistic User Simulation: Network Virtualization emulates real-world network behaviour.
If you haven’t seen LoadRunner Cloud in action or haven’t for some time, it’s worth seeing how easy to use and powerful it is. Use the buttons below to get in touch and ask questions, arrange a demo, or get a quote.
