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NEW QUESTION: 1
ユーザーは、クライアントとロードバランサー間の安全なネゴシエーションのためのセキュリティポリシーを使用して、SSLでELBを構成しました。 ELBがサポートしているセキュリティポリシーは次のうちどれですか?
A. 他のすべてのオプション
B. デフォルトのセキュリティポリシー
C. 動的セキュリティポリシー
D. 事前定義されたセキュリティポリシー
Answer: D
Explanation:
Explanation
Elastic Load Balancing uses a Secure Socket Layer (SSL. negotiation configuration which is known as a Security Policy. It is used to negotiate the SSL connections between a client and the load balancer. ELB supports two policies:
Predefined Security Policy, which comes with predefined cipher and SSL protocols; Custom Security Policy, which allows the user to configure a policy.

NEW QUESTION: 2
What is a benefit of inter-SDDC networking between two VMware Cloud on AWS SDDCs in the same region?
A. increased public access speed
B. highest workload availability
C. reduction in licensing costs for NSX
D. lowest AWS networking charges
Answer: C

NEW QUESTION: 3
You plan to create an Azure virtual machine (VM) that runs the Linux operating system.
You must use the following values:

You need to create and connect to the VM.
Which three commands should you run in sequence? To answer, move the appropriate commands from the list of commands to the answer area and arrange them in the correct order.

Answer:
Explanation:


NEW QUESTION: 4
Azure MachineLearningワークスペースを作成します。
次の要件を満たすという名前のカスタムロールを作成する必要があります。
*ロールメンバーはワークスペースを削除できないようにする必要があります。
*ロールメンバーは、ワークスペースでコンピューティングリソースを作成、更新、または削除できないようにする必要があります。
*ロールメンバーは、ワークスペースに新しいユーザーを追加できないようにする必要があります。
Azure MachineLearningワークスペースでDataScientistロールのJSONファイルを作成する必要があります。
カスタムロールは、IT運用チームによって指定された制限を適用する必要があります。
どのJSONコードセグメントを使用する必要がありますか?
A)

B)

C)

D)

A. オプションC
B. オプションA
C. オプションB
D. オプションD
Answer: B
Explanation:
Explanation
The following custom role can do everything in the workspace except for the following actions:
* It can't create or update a compute resource.
* It can't delete a compute resource.
* It can't add, delete, or alter role assignments.
* It can't delete the workspace.
To create a custom role, first construct a role definition JSON file that specifies the permission and scope for the role. The following example defines a custom role named "Data Scientist Custom" scoped at a specific workspace level:
data_scientist_custom_role.json :
{
"Name": "Data Scientist Custom",
"IsCustom": true,
"Description": "Can run experiment but can't create or delete compute.",
"Actions": ["*"],
"NotActions": [
"Microsoft.MachineLearningServices/workspaces/*/delete",
"Microsoft.MachineLearningServices/workspaces/write",
"Microsoft.MachineLearningServices/workspaces/computes/*/write",
"Microsoft.MachineLearningServices/workspaces/computes/*/delete",
"Microsoft.Authorization/*/write"
],
"AssignableScopes": [
"/subscriptions/<subscription_id>/resourceGroups/<resource_group_name>/providers/Microsoft.MachineLearni
]
}
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-assign-roles

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