Topic 1 Question 288
You have developed an AutoML tabular classification model that identifies high-value customers who interact with your organization's website. You plan to deploy the model to a new Vertex AI endpoint that will integrate with your website application. You expect higher traffic to the website during nights and weekends. You need to configure the model endpoint's deployment settings to minimize latency and cost. What should you do?
Configure the model deployment settings to use an n1-standard-32 machine type.
Configure the model deployment settings to use an n1-standard-4 machine type. Set the minReplicaCount value to 1 and the maxReplicaCount value to 8.
Configure the model deployment settings to use an n1-standard-4 machine type and a GPU accelerator. Set the minReplicaCount value to 1 and the maxReplicaCount value to 4.
Configure the model deployment settings to use an n1-standard-8 machine type and a GPU accelerator.
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- 正解だと思う選択肢: B
A (n1-standard-32): This is a much larger machine type and will likely be more expensive than necessary for your model. It could lead to unnecessary costs, especially during periods of low traffic. C and D (GPU Accelerators): While GPUs can be beneficial for some models, they are generally not required for tabular models. Adding a GPU would increase the cost without providing significant performance gains.
👍 3AB_C2024/11/27 - 正解だと思う選択肢: B
B) This option provides the most cost-effective and efficient solution because:
- Uses a suitably powerful machine type (n1-standard-4 machine)
- Autoscales with minReplicaCount and maxReplicaCount to adapt to the fluctuating traffic
- A larger machine type or accelerator is unnecessary. GPU provide better performance for DL models with massive datasets and complex architectures, not for tabular classification models.
👍 2carolctech2024/10/26
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