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Modern business systems – CRM, ERP, SaaS platforms, corporate websites, and mobile applications – process huge volumes of data every day and serve thousands of users simultaneously. As load grows, any flaw in architecture or code can lead not just to slowdowns but to complete service outage, lost sales, and reputational damage.
Our experience shows that high-quality software testing is exactly what enables companies to scale confidently and maintain a high level of service.
In this article, we explain how testing high-load projects helps ensure system stability and performance, and we share the practical approaches we use when working with high-load software.
What Are High-Load Systems and How Do They Differ from Typical Ones
High-load projects are digital systems that operate under sustained heavy load:
- thousands of concurrent users,
- millions of requests to the server,
- a continuous stream of transactions and data.
Their key properties are scalability, fault tolerance, and response speed. Unlike “typical” applications, such systems must be ready for sharp traffic spikes without degradation in quality of service.
Specifics of High-Load CRM and ERP Systems
CRM and ERP solutions directly impact a company’s core business processes: customer management, document flow, logistics, finance. Delays or failures are unacceptable-every lost second leads to missed deals and higher costs. That’s why high-load CRM and ERP require a special approach to architecture and testing: load balancing, clustering, and real-time monitoring.
High Load in Web Applications and Websites
E-commerce platforms, SaaS services, and online applications face load tests every day.
- For online stores, peak traffic during promotions is critical.
- For SaaS, consistent operation as the subscriber base grows.
- For service platforms, fast responses amid millions of API calls.
This also includes testing mobile applications, where it’s important to consider not only server-side load but also client-side behavior – operation across different devices and networks. In practice, high-load tests focus primarily on the server side, while client-side load is validated separately – via UI tests, emulators, or real devices. In short, projects must not only withstand traffic but also deliver a high standard of user experience – and that is possible only with systematic control.
Types of High-Load Testing
Testing is not a one-off check but a set of approaches that reveal how the product behaves under load. High-load systems are examined from multiple angles, and each test has its own purpose. Below is a brief summary:
| Test Type | What It Verifies |
|---|---|
| Load Testing | Whether the system handles typical/expected load |
| Stress Testing | Behavior under overload and recovery after failures |
| Soak / Endurance Testing | Memory leaks and performance degradation over time |
| Scalability Testing | System response to growth in users and data volume |
Load Testing
This type of testing shows where the real performance limits are. We simulate a typical workload – the number of users, operations, and requests – and assess whether the infrastructure copes without dips in speed and stability. It’s important to measure:
- Response Time (average response latency),
- RPS (Requests Per Second),
- TPS (Transactions Per Second),
- Error Rate.
For example, it’s crucial that at 5,000 RPS the average response time remains within 200-300 ms.
This approach helps identify critical bottlenecks before launch and optimize them prior to going to production.
Stress Tests
While load tests validate “normal” scenarios, stress tests push the system into extreme operating conditions. We deliberately overload a CRM, ERP, or web app beyond planned thresholds, record the moment when CPU or memory utilization reaches 90-95%, and evaluate how quickly the system recovers after the load is removed.
Stability (Soak/Endurance) Testing
The goal here is to understand how the system behaves during prolonged operation. Even if an application handles thousands of users at a point in time, we must ensure that after several days no memory leaks appear, latency doesn’t creep up, and throughput (operations per unit time) doesn’t drop. We verify that SLA (Service Level Agreement) targets for response time are maintained throughout the entire test run.
Scalability Testing
High-load projects must be ready for growth: more customers, more transactions, larger data volumes. Scalability testing shows how the system reacts to incremental load increases. We track:
- the effectiveness of horizontal and vertical scaling,
- stable response times as RPS grows,
- even distribution of requests across nodes.
This analysis reveals where the system “breaks” and what needs improvement to withstand future loads.
Approaches and Tools for High-Load Testing
The key to successful validation of high-load systems is realistic scenarios. We model real processes rather than abstract “virtual clicks”: testing a website under heavy traffic, as well as user actions such as:
- logging into a CRM,
- bulk API requests to an ERP,
- placing orders in an online store,
- processing payment transactions.
This approach helps uncover issues that can actually occur in production-not just in a test lab.
Tools and Technologies
We use proven solutions for simulating high load. Each is better suited to particular tasks:
- Apache JMeter – a flexible tool for complex scenarios;
- Gatling – a powerful tool for stress tests and response analysis;
- Locust – a Python-oriented platform convenient for custom test logic;
- k6 – a modern tool with DevOps pipeline integration and cloud execution.
We choose each tool for the specific job: from bulk API calls to validating payment gateways and ERP integrations.
Automating High-Load Tests
Embedding load testing into CI/CD processes (Continuous Integration / Continuous Delivery) enables performance checks not as a one-off, but regularly, with every release.
This helps to:
- catch performance regressions early,
- validate code and infrastructure after changes,
- keep the product stable throughout its lifecycle.
As a result, high-load tests become part of the engineering culture, ensuring product stability at every stage of its lifecycle.
Practical Cases: High-Load CRM, ERP, and Websites
Example of a CRM System
Under heavy load, CRM stability directly affects manager productivity. If the system “lags” during deals or client communication, the company loses money instantly.
In the AVA CRM project, we tested scenarios of massive parallel usage: dozens of managers simultaneously running chats, updating deal statuses, and exporting reports. Testing helped identify bottlenecks in advance and ensured stable operation even during sharp increases in user numbers.
ERP System for Large Enterprises
In big companies, ERP is the beating heart of operations: accounting, warehousing, logistics, finance. Any delay can paralyze an entire department.
For Sage 300, we tested the processing of thousands of transactions across accounting and logistics modules. For InteGen, a client implementing Sage 300, our AvadaCRM team developed separate modules and ensured their fault tolerance under heavy load. This approach guaranteed that the ERP system would work correctly even during peak loads.
E-commerce and SaaS Projects
Online stores and SaaS platforms serve thousands of users every day: placing orders, processing online payments, making API calls. Here, not only speed but also fault tolerance is critical.
In the HELPER project – a SaaS CRM for the beauty industry – we simulated scenarios of peak sales and mass customer interactions. High-load testing allowed us to configure the system to work equally reliably with hundreds or even thousands of active users online.
Common Issues and Solutions in High-Load Testing
Even the most robust-looking systems can fail when transaction volumes rise. The cause is often not developer mistakes, but architectural limitations or poorly designed testing scenarios. That’s why it’s essential to understand the most frequent issues and how to address them.
Architectural Bottlenecks
Most failures in high-load systems are not code-related but architecture-related:
- the database cannot handle peak transaction counts,
- cache becomes inefficient under growing requests,
- integrations with external services turn into bottlenecks.
Load tests help detect such weaknesses early and optimize the system before it reaches production.
Mistakes in Load Test Planning
Two of the most common pitfalls are:
- Insufficient scenario coverage – for example, testing only login functionality but not mass report exports or concurrent transactions;
- Oversimplified load models that don’t reflect actual user behavior.
As a result, software might pass testing but fail in production.
Recommendations for Mitigation
To minimize risks, we apply a comprehensive approach:
- Architectural optimizations: database replication and sharding, efficient cache usage;
- Scalable solutions: both horizontal and vertical scaling;
- Distributed systems: load evenly spread across nodes.
Combined with regular monitoring, these measures allow us to build resilient CRM, ERP, and e-commerce systems ready for business growth. Crucially, such solutions are most effective in the context of custom development: tailored systems allow the right architecture to be designed from the ground up, taking into account the specific needs of a business, instead of being limited by off-the-shelf software.
Conclusion
High-load testing is not a formality but a strategic tool. It ensures:
- reliability of digital systems,
- predictable behavior under peak loads,
- readiness for scaling.
With this, companies maintain professional service, avoid losing customers, and confidently plan for growth.
Entrust us with custom software development – we’ll make sure every system is tested against real-world loads and operates seamlessly in the future.
FAQ
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What is the difference between load testing and production monitoring?
Load tests are conducted in a controlled environment: we simulate real scenarios to identify bottlenecks before release. Monitoring, on the other hand, tracks metrics in production and helps respond to issues in real time. Together, the two approaches provide the fullest picture of system stability.
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Can a high-load system be tested before project launch?
Yes. Through scenarios, API request simulation, and transaction emulation, we can test architecture during development. This ensures the system will withstand real-world load and be production-ready without surprises.
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How often should high-load testing be performed?
It depends on business dynamics. For rapidly growing projects – at least once per quarter or before major releases. For stable systems – scheduled checks once or twice a year, but always after architectural or functional changes.
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Can microservices and monoliths be tested the same way?
No. In monoliths, load usually concentrates on central nodes (e.g., the database). In microservice architectures, it’s crucial to test load distribution across services and resilience to component failures.
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How much more complex is testing custom high-load CRMs compared to off-the-shelf ones?
It requires greater effort because every architecture and business logic is unique. With custom CRM development, standard load-testing templates must be adapted – or fully replaced – with tailored scenarios that reflect real processes and integrations. This adds complexity and cost but guarantees reliability and predictable behavior under heavy load.
