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NEW QUESTION: 1
A company plans to move regulated and security-sensitive businesses to AWS. The Security team is developing a framework to validate the adoption of AWS best practice and industry-recognized compliance standards. The AWS Management Console is the preferred method for teams to provision resources.
Which strategies should a Solutions Architect use to meet the business requirements and continuously assess, audit, and monitor the configurations of AWS resources? (Choose two.)
A. Use CloudTrail integration with Amazon SNS to automatically notify unauthorized API activities.
Ensure that CloudTrail is enabled in all accounts and available AWS services. Evaluate the usage of Lambda functions to automatically revert non-authorized changes in AWS resources.
B. Use AWS Config rules to periodically audit changes to AWS resources and monitor the compliance of the configuration. Develop AWS Config custom rules using AWS Lambda to establish a test-driven development approach, and further automate the evaluation of configuration changes against the required controls.
C. Use AWS CloudTrail events to assess management activities of all AWS accounts. Ensure that CloudTrail is enabled in all accounts and available AWS services. Enable trails, encrypt CloudTrail event log files with an AWS KMS key, and monitor recorded activities with CloudWatch Logs.
D. Use the Amazon CloudWatch Events near-real-time capabilities to monitor system events patterns, and trigger AWS Lambda functions to automatically revert non-authorized changes in AWS resources. Also, target Amazon SNS topics to enable notifications and improve the response time of incident responses.
E. Use Amazon CloudWatch Logs agent to collect all the AWS SDK logs. Search the log data using a pre-defined set of filter patterns that machines mutating API calls. Send notifications using Amazon CloudWatch alarms when unintended changes are performed. Archive log data by using a batch export to Amazon S3 and then Amazon Glacier for a long-term retention and auditability.
Answer: B,C
Explanation:
Explanation
https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudwatch-alarms-for-cloudtrail.html
https://docs.aws.amazon.com/en_pv/awscloudtrail/latest/userguide/best-practices-security.html
NEW QUESTION: 2
A network engineer is disabling split horizon on a point-to-multipoint interface that is running RIPng.
Under which configuration mode can split horizon be disabled?
A. router(config-rtr)#
B. router(config)#
C. router(config-if)#
D. router(config-riping)#
Answer: A
NEW QUESTION: 3
Is it possible lo switch between backup methods when creating regular backup files?
A. Yes, in this case you will have to specify a new backup repository.
B. Yes, the new method leaves existing backups as they are and continues creating backups in the same backup repository.
C. No, if you want to create backups using another method, you have to create another backupjob.
D. Yes, the new method willtransform all existing backups in the appropriate way and continue creating backupsin the same backuprepository.
Answer: B
NEW QUESTION: 4
You collect data from a nearby weather station. You have a pandas dataframe named weather_df that includes the following data:
The data is collected every 12 hours: noon and midnight.
You plan to use automated machine learning to create a time-series model that predicts temperature over the next seven days. For the initial round of training, you want to train a maximum of 50 different models.
You must use the Azure Machine Learning SDK to run an automated machine learning experiment to train these models.
You need to configure the automated machine learning run.
How should you complete the AutoMLConfig definition? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: forcasting
Task: The type of task to run. Values can be 'classification', 'regression', or 'forecasting' depending on the type of automated ML problem to solve.
Box 2: temperature
The training data to be used within the experiment. It should contain both training features and a label column (optionally a sample weights column).
Box 3: observation_time
time_column_name: The name of the time column. This parameter is required when forecasting to specify the datetime column in the input data used for building the time series and inferring its frequency. This setting is being deprecated. Please use forecasting_parameters instead.
Box 4: 7
"predicts temperature over the next seven days"
max_horizon: The desired maximum forecast horizon in units of time-series frequency. The default value is 1.
Units are based on the time interval of your training data, e.g., monthly, weekly that the forecaster should predict out. When task type is forecasting, this parameter is required.
Box 5: 50
"For the initial round of training, you want to train a maximum of 50 different models." Iterations: The total number of different algorithm and parameter combinations to test during an automated ML experiment.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.auto