Autoprovisioning in Magic Containers is a feature that uses reinforcement learning to periodically analyze and adjust the deployment of your app across different data centers or regions. The goal is to optimize the distribution of your app to ensure it is located closer to users, reduce latency, and improve overall performance.

Autoprovisioning process

Autoprovisioning involves periodic checks of your app's traffic distribution worldwide. Each time it runs, the provisioner assesses the current traffic patterns and determines whether any adjustments are needed for deploying or undeploying instances from data centers.
The key steps in the autoprovisioning process include:

1. Traffic distribution analysis: The provisioner analyzes the current traffic distribution of your app globally.
2. Optimization Decision: Based on the traffic distribution, the provisioner decides whether to deploy additional instances in specific regions or undeploy instances where traffic demand is lower.
3. Deployment/Undeployment: The provisioner then takes action, deploying new instances in regions with increased demand or undeploying instances from regions where demand is lower.
4. Periodic execution: Autoprovisioning runs periodically to ensure that your app continuously adapts to changing traffic patterns.

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