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NEW QUESTION: 1
A user has received a message from the support team that an issue occurred 1 week back
between 3 AM to 4 AM and the EC2 server was not reachable. The user is checking the CloudWatch metrics of that instance. How can the user find the data easily using the CloudWatch console?
A. It is not possible to find the exact time from the console. The user has to use CLI to provide the specific time
B. The user can find the data by giving the exact values in the time Tab under CloudWatch metrics
C. The user can find the data by filtering values of the last 1 week for a 1 hour period in the Relative tab under CloudWatch metrics
D. The user can find the data by giving the exact values in the Absolute tab under CloudWatch metrics
Answer: D
Explanation:
If the user is viewing the data inside the CloudWatch console, the console provides options to filter values either using the relative period, such as days /hours or using the Absolute tab where the user can provide data with a specific date and time. The console also provides the option to search using the local timezone under the time range caption in the console.

NEW QUESTION: 2
What happens after issuing the command vi without any additional parameters?
A. vi exits with an error message as it cannot be invoked without a file name to operate on.
B. vi starts and requires the user to explicitly either create a new or load an existing file.
C. vi starts and loads the last file used and moves the cursor to the position where vi was when it last exited.
D. vi starts and opens a new file which is filled with the content of the vi buffer if the buffer contains text.
E. vi starts in command mode and opens a new empty file.
Answer: E

NEW QUESTION: 3
You are operating a Google Kubernetes Engine (GKE) cluster for your company where different teams can run non-production workloads. Your Machine Learning (ML) team needs access to Nvidia Tesla P100 GPUs to train their models. You want to minimize effort and cost. What should you do?
A. Add a new, GPU-enabled, node pool to the GKE cluster. Ask your ML team to add the cloud.google.com/gke -accelerator: nvidia-tesla-p100 nodeSelectorto their pod specification.
B. Recreate all the nodes of the GKE cluster to enable GPUs on all of them.
C. Ask your ML team to add the "accelerator: gpu" annotation to their pod specification.
D. Create your own Kubernetes cluster on top of Compute Engine with nodes that have GPUs.
Dedicate this cluster to your ML team.
Answer: A
Explanation:
https://cloud.google.com/kubernetes-engine/docs/how-to/gpus