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NEW QUESTION: 1
A lightweight AP has been deployed in local mode in a network that consists of 10 wireless LAN controllers in a single mobility group. The AP has been configured to use primary, secondary, and tertiary Cisco WLCs. Due to a major power failure, all those Cisco WLCs are unavailable.
Which step does the AP take next?
A. The AP attempts to join the Cisco WLC that has the greatest capacity available.
B. The AP reboots and repeatedly attempts to join the configured primary, secondary, and tertiary Cisco WLCs in that order. The process continues until one of the configured Cisco WLCs is available.
C. The AP state transitions to AP Fallback Mode and continues to provide limited WLAN services (that is, no new client authentications) until a Cisco WLC is available.
D. The AP attempts to join a Cisco WLC configured as a master controller.
Answer: D
Explanation:
If a WLC is configured as a Master Controller, the LAP selects that WLC and sends it an LWAPP join request.
Reference: http://www.cisco.com/c/en/us/support/docs/wireless-mobility/wireless-lan-wlan/70333lap-registration.html
NEW QUESTION: 2
Which of the following is not true about the Huawei OceanStor 18000 Smart Matrix architecture:
A. Inherent Load Balancing: The controller is alive and well-balanced load sharing to improve storage resource utilization
B. Full Exchange: The use of PCIE1.0 full switching interconnect, providing sufficient switching bandwidth to meet the stringent performance requirements
C. scale-out: storage resources on-demand expansion, increase the engine to achieve performance, linear increase in capacity
D. Full redundancy: Redundancy of all components, intelligent switchover of component failures to meet stringent business continuity requirements
Answer: B
NEW QUESTION: 3
You are using Azure Machine Learning to train machine learning models. You need a compute target on which to remotely run the training script. You run the following Python code:
Answer:
Explanation:
Explanation
Box 1: Yes
The compute is created within your workspace region as a resource that can be shared with other users.
Box 2: Yes
It is displayed as a compute cluster.
View compute targets
1. To see all compute targets for your workspace, use the following steps:
2. Navigate to Azure Machine Learning studio.
3. Under Manage, select Compute.
4. Select tabs at the top to show each type of compute target.
Box 3: Yes
min_nodes is not specified, so it defaults to 0.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.amlcompute.amlcomputeprovis
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-create-attach-compute-studio