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NEW QUESTION: 1
You need to ensure that the solution can meet the scaling requirements for Policy Service. Which Azure Application Insights data model should you use?
A. an Application Insights metric
B. an Application Insights dependency
C. an Application Insights trace
D. an Application Insights even
Answer: A
Explanation:
Application Insights provides three additional data types for custom telemetry:
Trace - used either directly, or through an adapter to implement diagnostics logging using an instrumentation framework that is familiar to you, such as Log4Net or System.Diagnostics.
Event - typically used to capture user interaction with your service, to analyze usage patterns.
Metric - used to report periodic scalar measurements.
Scenario:
Policy service must use Application Insights to automatically scale with the number of policy actions that it is performing.
References:
https://docs.microsoft.com/en-us/azure/azure-monitor/app/data-model
NEW QUESTION: 2
A company is running a database on Amazon Aurora.
The database is idle every evening. An application that performs extensive reads on the database experiences performance issues during morning thus when user traffic spikes.
During these peak periods, the application receives timeout errors when reading from the database.
The company does not have a dedicated operations team and needs an automated solution to address the performance issues.
Which actions should a solutions architect take to automatically adjust to the increased read load on the database? (Select TWO )
A. Migrate the database to an Amazon RDS for MySQL Multi-AZ deployment
B. Migrate the database to Aurora Serverless.
C. Configure Aurora Auto Scaling with Aurora Replicas
D. Increase the instance size of the Aurora database
E. Migrate the data ase to an Aurora multi-master cluster
Answer: B,C
NEW QUESTION: 3
A company has application services that have been containerized and deployed on multiple Amazon EC2 instances with public IPs. An Apache Kafka cluster has been deployed to the EC2 instances. A PostgreSQL database has been migrated to Amazon RDS for PostgreSQL. The company expects a significant increase of orders on its platform when a new version of its flagship product is released.
What changes to the current architecture will reduce operational overhead and support the product release?
A. Deploy the application on a Kubernetes cluster created on the EC2 instances behind an Application Load Balancer. Deploy the DB instance in Multi-AZ mode and enable storage auto scaling. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.
B. Create an EC2 Auto Scaling group behind an Application Load Balancer. Create additional read replicas for the DB instance. Create Amazon Kinesis data streams and configure the application services to use the data streams. Store and serve static content directly from Amazon S3.
C. Create an EC2 Auto Scaling group behind an Application Load Balancer. Deploy the DB instance in Multi-AZ mode and enable storage auto scaling. Create Amazon Kinesis data streams and configure the application services to use the data streams. Store and serve static content directly from Amazon S3.
D. Deploy the application on Amazon Elastic Kubernetes Service (Amazon EKS) with AWS Fargate and enable auto scaling behind an Application Load Balancer. Create additional read replicas for the DB instance. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.
Answer: B
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