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NEW QUESTION: 1
A company is moving a business-critical, multi-tier application to AWS. The architecture consists of a desktop client application and server infrastructure. The server infrastructure resides in an on-premises data center that frequently fails to maintain the application uptime SLA of 99.95%. A Solutions Architect must re-architect the application to ensure that it can meet or exceed the SLA.
The application contains a PostgreSQL database running on a single virtual machine. The business logic and presentation layers are load balanced between multiple virtual machines. Remote users complain about slow load times while using this latency-sensitive application.
Which of the following will meet the availability requirements with little change to the application while improving user experience and minimizing costs?
A. Migrate the database to an Amazon RDS PostgreSQL Multi-AZ configuration. Host the application and presentation layers in automatically scaled AWS Fargate containers behind a Network Load Balancer.
Use Amazon ElastiCache to improve the user experience.
B. Migrate the database to an Amazon Redshift cluster with at least two nodes. Combine and host the application and presentation layers in automatically scaled Amazon ECS containers behind an Application Load Balancer. Use Amazon CloudFront to improve the user experience.
C. Migrate the database to a PostgreSQL database in Amazon EC2. Host the application and presentation layers in automatically scaled Amazon ECS containers behind an Application Load Balancer. Allocate an Amazon WorkSpaces WorkSpace for each end user to improve the user experience.
D. Migrate the database to an Amazon RDS Aurora PostgreSQL configuration. Host the application and presentation layers in an Auto Scaling configuration on Amazon EC2 instances behind an Application Load Balancer. Use Amazon AppStream 2.0 to improve the user experience.
Answer: D

NEW QUESTION: 2
An organization uses Azure Machine Learning service and wants to expand their use of machine learning.
You have the following compute environments. The organization does not want to create another compute environment.

You need to determine which compute environment to use for the following scenarios.
Which compute types should you use? To answer, drag the appropriate compute environments to the correct scenarios. Each compute environment may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: nb_server

Box 2: mlc_cluster
With Azure Machine Learning, you can train your model on a variety of resources or environments, collectively referred to as compute targets. A compute target can be a local machine or a cloud resource, such as an Azure Machine Learning Compute, Azure HDInsight or a remote virtual machine.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-set-up-training-targets

NEW QUESTION: 3
The executive team wants you to track labor costs for your project as well as progress on task completion and the resulting dates. What information must you update for tasks to provide this information?
A. Start, Work, and Remaining Work
B. Actual Start, Actual Work, and Remaining Work
C. Actual Start, Percent Complete, and Remaining Duration
D. Actual Start and Percent Complete
Answer: B

NEW QUESTION: 4
Which of the following can be implemented in hardware or software to protect a web server from cross-site scripting attacks?
A. Web Application Firewall
B. URL Content Filter
C. Intrusion Detection System
D. Flood Guard Protection
Answer: A
Explanation:
Cross-site scripting (XSS) is a form of malicious code-injection attack on a web server in which an attacker injects code into the content sent to website visitors. XSS can be mitigated by implementing patch management on the web server, using firewalls, and auditing for suspicious activity.