1. Your application consists of 10% writes and 90% reads. You currently service all requests through a Route53 Alias Record directed towards an AWS(Amazon Web Service) ELB, which sits in front of an EC2 Auto Scaling Group. Your system is getting very expensive when there are large traffic spikes during certain news events, during which many more people request to read similar data all at the same time. What is the simplest and cheapest way to reduce costs and scale with spikes like this?

A) Create another ELB and Auto Scaling Group layer mounted on top of the other system, adding a tier to the system. Serve most read requests out of the top layer.
B) Create a Cloud Front Distribution and direct Route53 to the Distribution. Use the ELB as an Origin and specify Cache Behaviors to proxy cache requests which can be served late.
C) synchronously replicate common requests responses into S3 objects. When a request comes in for a pre computed response. redirect to AWS(Amazon Web Service) 53.
D) Create a Mem cached cluster in AWS(Amazon Web Service) Elastic Cache. Create cache logic to serve requests which can be served late from the in-memory cache for Increased performance.



2. You run a 2000-engineer organization. You are about to begin using AWS(Amazon Web Service) at a large scale for the first time. You want to integrate with your existing identity management system running on Microsoft Active Directory. because your organization Is a power-user of Active Directory. How should you manage your AWS(Amazon Web Service) identities in the most simple manner?

A) Use AWS(Amazon Web Service) Directory Service AD Connector
B) Use an Sync Domain running on AWS(Amazon Web Service) Directory Service.
C) Use an AWS(Amazon Web Service) Directory Sync Domain running on AWS(Amazon Web Service) Lambda
D) Use AWS(Amazon Web Service) Directory Service Simple AD.



3. You need your API backed by Dynamo DB to stay online during a total regional AWS(Amazon Web Service) failure. You can tolerate a couple minutes of lag or slowness during a large failure event, but the system should recover with normal operation after those few minutes. What Is a good approach?

A) Set up Dynamo DB cross-region replication In a master-standby configuration. with a single standby In another region. Create a cross region ELB pointing to a cross-region Auto Scaling Group, and direct a Routes3 Latency DNS Record with DNS Failover to the crossregion ELB.
B) Set up a Dynamo DB Global table. Create an Auto Scaling Group behind an ELB in each of the two regions your application layer in which the Dynamo DB is running In. Add a Route53 Latency DNS Record with DNS Failover. using the ELB5 in the two regions as the resource records.
C) Set up a Dynamo DB Multi-Region table. Create a cross-region ELS pointing to a crossregion Auto Scaling Group. and direct a Route53 Latency DNS Record with DNS Failover to the cross-region ELB.
D) Set up Dynamo DB cross-region replication in a master-standby configuration. with a single standby in another region. Create an Auto Scaling Group behind an ELS in each of the two regions for your application layer In which Dynamo DB is running In. Add a Route53 Latency DNS Record with DNS Failover, using the ELBs in the two regions as the resource records.



4. You need to run a very large batch data processing job one time per day. The source data exists entirely in 53, and the output of the processing job should also be written to S3 when finished. If you need to version control this processing job and all setup and teardown logic for the system, what approach should you use?

A) Model an AWS(Amazon Web Service) EMR job in AWS(Amazon Web Service) Cloud Formation.
B) Model an AWS(Amazon Web Service) EMR job In AWS(Amazon Web Service) Ops Works.
C) Model an AWS(Amazon Web Service) EMR job in AWS(Amazon Web Service) Elastic Beanstalk.
D) Model an AWS(Amazon Web Service) EMR job in AWS(Amazon Web Service) CLI Composer.



5. When thinking of AWS(Amazon Web Service) Elastic Beanstalk, the Swap Environment URLs feature most directly aids in what?

A) Mutable Rolling Deployments
B) Blue-Green Deployments
C) Canary Deployments
D) Immutable Rolling Deployments