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NEW QUESTION: 1
ルートAWSアカウントの所有者が、Bob、John、Michaelの3人のIAMユーザーを作成しました。 MichaelはIAM管理者です。ボブとジョンはスーパーユーザーではなく、いくつかの定義済みポリシーを持つユーザーです。ジョンは自分のパスワードを変更する権限を持っていません。したがって、彼は自分のパスワードを変更するようにBobに依頼します。ボブはジョンのパスワードをどのように変更できますか？
A. MichaelがIAMパスワードを変更する権限を持つグループにBobを追加できる場合、これは可能です。
B. これは誤りです。 Johnのパスワードを変更できるのはMichaelだけです
C. ジョンが自分のパスワードを変更することは不可能です
D. BobがJohnのマネージャです
Answer: A
Explanation:
Generally with IAM users, the password can be modified in two ways. The first option is to define the IAM level policy which allows each user to modify their own passwords. The other option is to create a group and create a policy for the group which can change the passwords of various IAM users.
Reference: http://docs.aws.amazon.com/IAM/latest/UserGuide/HowToPwdIAMUser.html
NEW QUESTION: 2
You train a model and register it in your Azure Machine Learning workspace. You are ready to deploy the model as a real-time web service.
You deploy the model to an Azure Kubernetes Service (AKS) inference cluster, but the deployment fails because an error occurs when the service runs the entry script that is associated with the model deployment.
You need to debug the error by iteratively modifying the code and reloading the service, without requiring a re-deployment of the service for each code update.
What should you do?
A. Register a new version of the model and update the entry script to load the new version of the model from its registered path.
B. Add a breakpoint to the first line of the entry script and redeploy the service to AKS.
C. Create an Azure Container Instances (ACI) web service deployment configuration and deploy the model on ACI.
D. Modify the AKS service deployment configuration to enable application insights and re-deploy to AKS.
E. Create a local web service deployment configuration and deploy the model to a local Docker container.
Answer: C
Explanation:
How to work around or solve common Docker deployment errors with Azure Container Instances (ACI) and Azure Kubernetes Service (AKS) using Azure Machine Learning.
The recommended and the most up to date approach for model deployment is via the Model.deploy() API using an Environment object as an input parameter. In this case our service will create a base docker image for you during deployment stage and mount the required models all in one call. The basic deployment tasks are:
1. Register the model in the workspace model registry.
2. Define Inference Configuration:
a. Create an Environment object based on the dependencies you specify in the environment yaml file or use one of our procured environments.
b. Create an inference configuration (InferenceConfig object) based on the environment and the scoring script.
3. Deploy the model to Azure Container Instance (ACI) service or to Azure Kubernetes Service (AKS).
NEW QUESTION: 3
A security engineer is setting up passwordless authentication for the first time.
INSTRUCTIONS
Use the minimum set of commands to set this up and verify that it works. Commands cannot be reused.
If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.
Answer:
Explanation:
Explanation