A customer owns a simple API for their website that receives about 1,000 requests each day and has an average response time of 50 ms. It is currently hosted on one c4.large instance. Which changes to the architecture will provide high availably at the LOWEST cost?

• A.Recreate the API using Amazon API Gateway and use AWS Lambda as the service backend
• B.Recreate the API using Amazon API Gateway and integrate the new API with the existing backend service
• C.Create an Auto Scaling group with a minimum of one instance and a maximum of two instances then use an Application Load Balancer to balance the traffic
• D.Create an Auto Scaling group with a minimum and a maximum of two instances, then use an Application Load Balancer to balance the traffic.

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If you are using Amazon RDS Provisioned lOPS storage with MySQL and Oracle database engines, you can scale the throughput of your database Instance by specifying the lOPS rate f rom ___ _

• A.1, 000 to 10, 000
• B.1,000 to 1, 00, 000
• C.10, 000 to 1, 00, 000
• D.100 to 1, 000

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A company is having issues with a newly deployed serverless infrastructure that uses Amazon API Gateway, Amazon Lambda, and Amazon DynamoDB.
In a steady state, the application performs as expected. However, during peak load, tens of thousands of simultaneous invocations are needed and user requests fail multiple times before succeeding. The company has checked the logs for each component, focusing specifically on Amazon CloudWatch Logs for Lambda. There are no errors logged by the services or applications.
What might cause this problem?

• A.Lambda has very low memory assigned, which causes the function to fail at peak load.
• B.Lambda is in a subnet that uses a NAT gateway to reach out of the internet, and the function instance does not have sufficient Amazon EC2 resources in the VPC to scale with the load.
• C.The throttle limit set on API Gateway is very low. During peak load, the additional requests are not making their way through to Lambda.
• D.DynamoDB is set up in an auto scaling mode. During peak load, DynamoDB adjusts capacity and throughput behind the scenes, which is causing the temporary downtime. Once the scaling completes, the retries go through successfully.

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A company stores 200 GB of data each month in Amazon S3. The company needs to perform analytics on this data at the end of each month to determine the number of items sold in each sales region for the previous month.
Which analytics strategy is MOST cost-effective for the company to use?

• A.Create an Amazon EMR cluster Query the data by using Amazon EMR, and store the results in Amazon S3 Visualize the data in Amazon QuickSight.
• B.Create an Amazon Elasticsearch Service (Amazon ES) cluster. Query the data in Amazon ES. Visualize the data by using Kibana.
• C.Create an Amazon Redshift cluster. Query the data in Amazon Redshift, and upload the results to Amazon S3. Visualize the data in Amazon QuickSight.
• D.Create a table in the AWS Glue Data Catalog. Query the data in Amazon S3 by using Amazon Athena.
  Visualize the data in Amazon QuickSight

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A company has an ecommerce application that stores data in an on-premises SQL database. The company has decided to migrate this database to AWS. However as part of the migration, the company wants to find a way to attain sub-millisecond responses to common read requests.
A solutions architect knows that the increase in speed is paramount and that a small percentage of stale data returned in the database reads is acceptable What should the solutions architect recommend?

• A.Build a database cache using Amazon Elasticsearch Service (Amazon ES)
• B.Build Amazon RDS read replicas.
• C.Build a database cache using Amazon ElastiCache
• D.Build the database as a larger instance type.

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