A company has a web application for travel ticketing. The application is based on a database that runs in a single data center in North America. The company wants to expand the application to serve a global user base. The company needs to display the application to multiple AWS Regions. Average latency must be less than 1 second on updates to reservation database.
The company wants to have separate deployments of its web platform across multiple Regions.
However, the company must maintain a single primary reservation database that is globally consistent.
Which solution should a solutions architect recommend to meet these requirements?

• A.Migrate the database to an Amazon Aurora MySQL database. Deploy Aurora Read Replicas in each Region. Use the correct Region endpoint in each Regional deployment for access to the database.
• B.Convert the application to use Amazon DynamoDB. Use a global table for the center reservation table.
  Use the correct Regional endpoint in each Regional deployment.
• C.Migrate the application to an Amazon Aurora Severless database. Deploy instances of the database to each Region. Use the correct Region endpoint in each Regional deployment to access the database. Use AWS Lambda functions to process event streams in each Region to synchronize the databases.
• D.Migrate the database to an Amazon RDS for MySQL database. Deploy MySQL read replicas in each Region. Use the correct Regional endpoint In each Regional deployment for access to the database.

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A customer has an application that is used by enterprise customers outside of AWS. Some of these customers use legacy firewalls that cannot whitelist by DNS name, but whitelist based only on IP address. The application is currently deployed in two Availability Zones, with one EC2 instance in each that has Elastic IP addresses. The customer wants to whitelist only two IP addresses, but the two existing EC2 instances cannot sustain the amount of traffic.
What can a Solutions Architect do to support the customer and allow for more capacity? (Choose two.)

• A.Create a Network Load Balancer with an interface in each subnet, and assign a static IP address to each subnet.
• B.Create additional EC2 instances and put them on standby. Remap an Elastic IP address to a standby instance in the event of a failure.
• C.Use Amazon Route 53 with a weighted, round-robin routing policy across the Elastic IP addresses to resolve one at a time.
• D.Add additional EC2 instances with Elastic IP addresses, and register them with Amazon Route 53
• E.Switch the two existing EC2 instances for an Auto Scaling group, and register them with the Network Load Balancer.

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A customer is complaining that requests made to theirload balancer are closing prematurely. The customer also mentions that the issue only happens when waiting for the multi-week report to be generated. Which option will resolve the customer's issue?

• A.Enable stickiness on the load balancer
• B.Disable connection draining on the load balancer
• C.Adjust the timeout on health check settings
• D.Increase the idle timeout on registered instances

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A company is running a series of national TV campaigns. These 30 second advertisements will introduce sudden traffic peaks targeted at a Node .js application. The company experts traffic to increase from five requests each minute to more than 5,000 requests each minutes.
Which AWS service should a Solution Architecture use to ensure traffic surges can be handled?

• A.Amazon ElasticCache
• B.Size EC2 instance to handle peak load
• C.An Auto Scaling group for EC2 instance.
• D.AWS Lambda

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A company has several teams, and each team has their own Amazon RDS database that totals 100 TB. The company is building a data query platform for Business Intelligence Analysts to generate a weekly business report: The new system must run ad-hoc SQL queries.
What is the MOST cost-effective solution?

• A.Use an AWS Glue crawler to crawl all the databases and create tables in the AWS Glue Data Catalog. Use an AWS Glue ETL job to load data from the RDS databases to Amazon S3, and use Amazon Athena to run the queries.
• B.Use an AWS Glue ETL job to copy all the RDS databases to a single Amazon Aurora PostgreSQL database. Run SQL queries on the Aurora PostgreSQL database.
• C.Create a new Amazon Redshift cluster. Create an AWS Glue ETL job to copy data from the RDS databases to the Amazon Redshift cluster. Use Amazon Redshift to run the query.
• D.Create an Amazon EMR cluster with enough core nodes. Run an Apache Spark job to copy data from the RDS databases to a Hadoop Distributed File System (HDFS). Use a local Apache Hive metastore to maintain the table definition. Use Spark SQL to run the query.

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