Microsoft
DP-100 · Question #189
An organization creates and deploys a multi-class image classification deep learning model that uses a set of labeled photographs. The software engineering team reports there is a heavy inferencing lo
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Train and deploy models
Question
An organization creates and deploys a multi-class image classification deep learning model that uses a set of labeled photographs. The software engineering team reports there is a heavy inferencing load for the prediction web services during the summer. The production web service for the model fails to meet demand despite having a fully- utilized compute cluster where the web service is deployed. You need to improve performance of the image classification web service with minimal downtime and minimal administrative effort. What should you advise the IT Operations team to do?
Options
- ACreate a new compute cluster by using larger VM sizes for the nodes, redeploy the web service
- BIncrease the node count of the compute cluster where the web service is deployed.
- CIncrease the minimum node count of the compute cluster where the web service is deployed.
- DIncrease the VM size of nodes in the compute cluster where the web service is deployed.
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Topics
#Inference scaling#Azure ML Compute Cluster#Performance optimization#Horizontal scaling