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QUESTION NO: 1
A media storage application uploads user photos to Amazon S3 for processing. End users are reporting that some uploaded photos are not being processed properly. The Application Developers trace the logs and find that AWS Lambda is experiencing execution issues when thousands of users are on the system simultaneously.
Issues are caused by:
* Limits around concurrent executions.
* The performance of Amazon DynamoDB when saving data.
Which actions can be taken to increase the performance and reliability of the application? (Choose two.)
A. Configure a dead letter queue that will reprocess failed or timed-out Lambda functions.
B. Add an Amazon ElastiCache layer to increase the performance of Lambda functions.
C. Evaluate and adjust the write capacity units (WCUs) for the DynamoDB tables.
D. Evaluate and adjust the read capacity units (RCUs) for the DynamoDB tables.
E. Use S3 Transfer Acceleration to provide lower-latency access to end users.
Answer: A,C
Explanation
B:
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadWriteCap acityMode.ht
D: https://aws.amazon.com/blogs/compute/robust-serverless-application-design-with-aws-lambda- dlq/c
QUESTION NO: 2
A company has a Microsoft SOL Server database in its data center and plans to migrate data to
Amazon Aurora MySQL. The company has already used Vie AWS Schema Conversion Tool to migrate triggers, stored procedures and other schema objects to Aurora MySQL The database contains 1 TB of data and grows toss than 1 M6 per day The company's data center is connected to AWS through a dedicated 1Gbps AWS Direct Connect connection.
The company would like to migrate data to Aurora MySQL and perform reconfigurations with minimal downtime to the applications.
Which solution meets the company's requirements?
A. Shut down application over the weekend Create an AWS QMS replication instance and task to migrate existing data from SQL Server to Aurora MySQL Perform application testing and migrate (he data to the new database endpoint
B. Create a SQL Server native backup file on Amazon S3 Create an AWS DMS replication instance and task to restore the SQL Server backup file to Aurora MySQL Create another AWS DMS task for ongoing replication from SQL Server to Aurora MySQL Perform application testing and migrate the data to the new database endpoint
C. Create a database snapshot of SQL Server on Amazon S3 Restore the database snapshot from
Amazon S3 to Aurora MySQL Create an AWS DMS replication instance and task tor ongoing replication from SQL Server to Aurora MySQL Perform application testing and migrate the data to the new database endpoint
D. Create an AWS DMS replication instance and task to migrate existing data and ongoing replication from SQL Server to Aurora MySQL Perform application testing and migrate the data to the new database endpoint
Answer: D
QUESTION NO: 3
A company wants to ensure that the workloads for each of its business units have complete autonomy and a minimal blast radius in AWS. The Security team must be able to control access to the resources and services in the account to ensure that particular services are not used by the business units.
How can a Solutions Architect achieve the isolation requirements?
A. Create one shared account for the entire company. Create individual IAM policies and resource tags for each business unit. Federate the account with an IdP, and create separate roles for the business units and the Security team.
B. Create individual accounts for each business unit. Federate each account with an IdP and create separate roles and policies for business units and the Security team.
C. Create one shared account for the entire company. Create separate VPCs for each business unit.
Create individual IAM policies and resource tags for each business unit. Federate each account with an IdP, and create separate roles for the business units and the Security team.
D. Create individual accounts for each business unit and add the account to an OU in AWS
Organizations.
Modify the OU to ensure that the particular services are blocked. Federate each account with an IdP, and create separate roles for the business units and the Security team.
Answer: D
QUESTION NO: 4
A company deployed a three-tier web application in two regions: us-east-1 and eu-west-1. The application must be active in both regions at the same time. The database tier of the application uses a single Amazon RDS Aurora database globally, with a master in us-east-1 and a read replica in eu- west-1. Both regions are connected by a VPN.
The company wants to ensure that the application remains available even in the event of a region- level failure of all of the application's components. It is acceptable for the application to be in read- only mode for up to 1 hour. The company plans to configure two Amazon Route 53 record sets, one for each of the regions.
How should the company complete the configuration to meet its requirements while providing the lowest latency for the application end-users? (Choose two.)
A. Use failover routing and configure the us-east-1 record set as primary and the eu-west-1 record set as secondary. Configure an HTTP health check for the web application in us-east-1, and associate it to the us-east-1 record set.
B. Use weighted routing and configure each record set with a weight of 50. Configure an HTTP health check for each region, and attach it to the record set for that region.
C. Configure an Amazon RDS event notifications to react to the failure of the database in us-east-1 by invoking an AWS Lambda function that promotes the read replica in eu-west-1.
D. Use latency-based routing for both record sets. Configure a health check for each region and attach it to the record set for that region.
E. Configure an Amazon CloudWatch alarm for the health checks in us-east-1, and have it invoke an
AWS Lambda function that promotes the read replica in eu-west-1.
Answer: C,D
Explanation
https://docs.aws.amazon.com/lambda/latest/dg/services-rds.html
QUESTION NO: 5
A company has a large on-premises Apache Hadoop cluster with a 20 PB HDFS database. The cluster is growing every quarter by roughly 200 instances and 1 PB. The company's goals are to enable resiliency for its Hadoop data, limit the impact of losing cluster nodes, and significantly reduce costs. The current cluster runs 24/7 and supports a variety of analysis workloads, including interactive queries and batch processing.
Which solution would meet these requirements with the LEAST expense and down time?
A. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent
Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on
Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
B. Use AWS Snowmobile to migrate the existing cluster data to Amazon S3. Create a persistent
Amazon EMR cluster of similar size and configuration to the current cluster. Store the data on EMRFS.
Minimize costs by using Reserved Instances. As the workload grows each quarter, purchase additional
Reserved Instances and add to the cluster.
C. Use AWS Direct Connect to migrate the existing cluster data to Amazon S3. Create a persistent
Amazon EMR cluster initially sized to handle the interactive workload based on historical data from the on-premises cluster. Store the data on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on
Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
D. Use AWS Snowball to migrate the existing cluster data to Amazon S3. Create a persistent Amazon
EMR cluster initially sized to handle the interactive workloads based on historical data from the on- premises cluster. Store the on EMRFS. Minimize costs using Reserved Instances for master and core nodes and Spot Instances for task nodes, and auto scale task nodes based on Amazon CloudWatch metrics. Create job-specific, optimized clusters for batch workloads that are similarly optimized.
Answer: A
Explanation
Q: How should I choose between Snowmobile and Snowball?
To migrate large datasets of 10PB or more in a single location, you should use Snowmobile. For datasets less than 10PB or distributed in multiple locations, you should use Snowball. In addition, you should evaluate the amount of available bandwidth in your network backbone. If you have a high speed backbone with hundreds of Gb/s of spare throughput, then you can use Snowmobile to migrate the large datasets all at once. If you have limited bandwidth on your backbone, you should consider using multiple Snowballs to migrate the data incrementally.
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Updated: May 28, 2022
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