SCPERF01-BP02 Factor in rate of increase in load, traffic, and scale-out intervals - Supply Chain Lens
Implementation guidance

SCPERF01-BP02 Factor in rate of increase in load, traffic, and scale-out intervals

Identify the upper bounds of the peak load against a system, as well as the amount of time needed to reach peak load. Load tests often overlook the rate of increase in traffic and create tests that scale up too quickly or too slowly.

Desired outcome: You mimic the traffic and load situation of the system and see how the user experience in such situations, this will help to fine-tune the underlying resources of the architecture to achieve better results.

Benefits of establishing this best practice: System resiliency prediction, and system behavior during peak hours/loads.

Level of risk exposed if this best practice is not established: High

Implementation guidance

Identify the upper bounds of the peak load against a system, as well as the amount of time needed to reach peak load. Load tests often overlook the rate of increase in traffic and create tests that scale up too quickly or too slowly. If the load test ramps up too quickly, the system may not be able to add capacity rapidly enough to meet the demand, which degrades performance and introduces errors. Load tests need to be run periodically and with every major release of the system or when new systems or architecture is introduced in the supply chain eco-system.

Implementation steps

  1. Analyze historical traffic patterns to identify peak load periods and growth rates specific to supply chain operations.

  2. Design load tests that accurately simulate realistic traffic ramp-up patterns based on actual usage scenarios.

  3. Establish automated scaling policies that can respond appropriately to gradual and sudden load increases.

  4. Implement comprehensive monitoring during load tests to identify performance bottlenecks and capacity constraints.

  5. Create regular load testing schedules that coincide with major system releases and supply chain system integrations.

  6. Document and analyze load test results to continuously improve system performance and scaling capabilities.