Load Testing What is Design Load?

A decade ago, “Design Load” was a concept from classical engineering transferred to web performance. It is still a primary metric today, although our approach has significantly changed. Design Load indicates the upper limit of traffic or load a system is built to manage, thus describing its scope and matching it with performance parameters. Nevertheless, the evolution of cloud architecture, microservices, and advanced load testing tools has dramatically increased our ability to define and verify Design Load.

Critical Benefits and Data:

Prevention of Downtime and Service Interruptions:

• Downtime can be expensive. Even short downtime can cause revenue loss and damage a company's reputation. Load testing seeks to find weaknesses that can result in crashes during peak traffic times.

• Simulating traffic spikes helps prevent bottlenecks and assures the system can handle surges.

Ensuring Optimum User Experience:

• People have higher expectations of a website's and an application's performance. Slow and unresponsive applications can frustrate users.

• Load testing assists in locating performance concerns, such as the speed of loading pages or API, making it possible to modify the system to guarantee a smooth user experience. Increased user satisfaction and retention directly relate to the mitigation of the issues.

Improving Scalability:

• The infrastructure should improve along with the business's growth. Load testing enables the assessment of increased traffic and usage.

• Recognizing scalability limits, infrastructure upgrades, and resource allocation decisions can be made. This prevents unnecessary spending and helps optimize costs.

Identifying Performance Bottlenecks:

• Load testing marks performance bottlenecks that would otherwise go unnoticed during normal usage. Proficient programmers can implement continuous load testing to ascertain whether forceful slowing is being caused by defective programming, a problematic database, or even a restrictive network.

• Knowing the problems, any system can be fastened and fine-tuned for maximum performance and efficiency.

Minimizing costs:

• Fixing problems during the testing phase is much cheaper than debugging or shutting a system down due to problems.

• Load testing allows for the prevention of expensive halting, as well as cascading failures of needed services.

Satisfying SLA and compliance:

• With load testing, systems in many industries can prepare for the rigorous performance and availability check requirements. A load test enables compliance to be demonstrated through thorough checks.

• Load testing exercises also validate SLAs.

• Testing under normal operating conditions increases confidence in development's operations and accuracy in performing the proper tests during deployment and refining release cycles.

Regular load testing is not just a technical exercise; it's a strategic investment that protects your business from costly disruptions, enhances user satisfaction, and ensures long-term scalability.

Modernizing Design Load: Moving Beyond Basic Traffic Estimates

Previously, Design Load resulted from traffic analysis, estimated growth, and expected influence from new features. While these components still stand, we now utilize lower-level information with forecasted analytics.

• Advanced Analysis and Supervision: To analyze the application's performance (in terms of latency, throughput, error rate, etc.), we monitor all layers of the application stack using modern and advanced tools and collect data.

• Session Modeling: We construct user behavior models by analyzing user session interaction and simulating various traffic and usage scenarios.

• Microservices Architecture: It is essential to know each microservice's performance attributes. We evaluate the scalability and durability of individual components to ensure they and their loads are manageable.

• Cloud-Native Considerations: Cloud infrastructure is associated with responsive provisioning. We include automated scaling, ‘resource’ expandability, and potential cloud services ‘bottlenecks.’

The Importance of Maintaining a High Factor of Safety

The "Factor of Safety" is still relevant today; however, its implementation has changed. Factors like traffic spikes resulting from viral campaigns, media mentions, or DoS attacks still need to be considered. In addition, we put more emphasis on:

• Predictive Analytics: We apply machine learning technology to predict traffic spikes that historical events or other external elements could cause.

• Chaos Engineering: We perform proactive backend failures to determine how the system withstands pressure and which areas are vulnerable.

• Security Considerations: We think of possible security risks and the performance impact of mitigating security risks.

Modifying the Design Load Formula

Even if the core principles are still present, the formula can be modified to align with contemporary practices:

DL=FS×(Current+Projected_Growth+New_Features+Security_Overhead)×Peak_Factor

Where:

• DL = Design Load

• FS = Factor of Safety (now includes risk and predictive analytics)

• Current = traffic and resource consumption currently in use

• Projected_Growth = Expected growth based on analysis and market activity

• New_Features = anticipated influence of additional features

• Security_Overhead = expenditure of resources as a result of security protocols

• Peak_Factor = modification due to maximum traffic periods.

Specifying Design Load: Usage Metrics

The Page Views per Second metric is still relevant, but we have expanded the scope of our metrics to include:

• Requests Per Second (RPS): It provides more detail in imagery and measurement of API and microservices activity.

• Latency (milliseconds): This is significant to the end user, particularly for real-time applications.

• Throughput (MB/s or GB/s): Very relevant for media-oriented applications and data-heavy services.

• Concurrent Users/Sessions: A relevant metric with a correct definition of “think time” and behavioral models.

• Error Rates: Fundamental indicators in observing system stability under load.

Load Testing with New Tools

At Oshyn, we have a full suite of load-testing tools. This gives us the ability to create any load scenario:

• Realistic load tests: Complex user behavior and traffic generation SMOs.

• Bottleneck: Performance window issue over the entire infrastructure.

• Performance optimization: Configuration changes to resource spending.

• Scalability validation: Check if the system can grow.

• Soak Tests: How long can the system function under a given load?

• Stress Tests: When does the system collapse?

Oshyn’s Proactive Approach to Infrastructure Health

Here at Oshyn, we appreciate that infrastructure health is critical to our clients. Our approach goes beyond troubleshooting; we spend considerable funds on infrastructure health. Through our powerful load testing tools and deep expertise, we analyze for bottlenecks and performance-degrading issues that might impact our clients before end-users experience them. Much time is spent on proactive measures to ensure clients’ infrastructure is performant, scalable, and aligned with their digital objectives. We work with clients to understand their business goals and ensure that they achieve technical and digital success. We do not just solve problems; we construct strong systems and network infrastructures that yield business success.