From the course: Cloud-Based AI Solution Design Patterns
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AI-model operations monitoring and optimization
From the course: Cloud-Based AI Solution Design Patterns
AI-model operations monitoring and optimization
- The AI model operations monitoring and optimization pattern introduces monitors that check on a model's health and performance. While these are monitors that we can also put in place in on-premises environments, they're much more common and effective in cloud environments where they become cloud native extensions of the underlying cloud-based infrastructure. Let's begin with the model performance metrics monitor, which is used to measure the accuracy of the model's output results, as well as the model's overall efficiency. For example, it will check for degradation in the model's accuracy over time, and will also measure latency to determine whether the time the model is taking to generate its output is acceptable. In relation to this, the monitor may further track the number of times the model executes and produces output over a period of time, as well as the amount of infrastructure resources it consumes. The model health monitor is responsible for ensuring that the model is…
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