MLOps Blog Series Part 3: Testing scalability of secure machine learning systems using MLOps

The capacity of a system to adjust to changes by adding or removing resources to meet demand is known as scalability. Here are some tests to check the scalability of your model. System tests are carried out to test the robustness of the design of a system for given inputs and expected outputs (for example, an MLOps pipeline, inference). Acceptance tests (to fulfill user requirements) can be performed as part of system tests. A/B testing is performed by sending production traffic to alternate systems that will be evaluated.