1. If I want Cloud Formation stack status updates to show up in a continuous delivery system in as close to real time as possible, how should I achieve this?

A) Subscribe your continuous delivery system to an SQS queue that you also tell your Cloud Formation stack to publish events into.
B) Use a long-poll on the Resources object in your Cloud Formation stack and display those state changes in the UI for the system.
C) Subscribe your continuous delivery system to an SNS topic that you also tell your Cloud Formation stack to publish events into.
D) Use a long-poll on the List Stacks APl call for your Cloud Formation stack and display those state changes in the UI for the system.



2. You have deployed a Cloud formation template which is used to spin up resources in your account. Which of the following status in Cloud formation represents a failure.

A) UPDATE_IN_PROGRESS
B) UPDATE_COMPLETE_CLEAN UP_I N_PROGRESS
C) ROLLBACK_IN_PROGRESS
D) DELETE_COMPLETE



3. You need to scale an RDS deployment. You are operating at 10% writes and 90% reads, based on your logging. How best can you scale this In a simple way?

A) Create a second master RDS instance and peer the RDS groups.
B) Cache all the database responses on the read side with Cloud Front.
C) Create a Multi-AZ RDS installs and route read traffic to standby.
D) Create read replicas for RDS since the load is mostly reads



4. What is web identity federation?

A) Use of AWS(Amazon Web Service) STS Tokens to log in as a Google or Face book user.
B) Use of AWS(Amazon Web Service) lAM User tokens to log in as a Google or Face book user.
C) Use of an identity provider like Google or Face book to exchange for temporary AWS(Amazon Web Service) security credentials.
D) Use of an identity provider like Google or Face book to become an AWS(Amazon Web Service) lAM User.



5. You are designing a service that aggregates click stream data in batch and delivers reports to subscribers via email only once per week. Data is extremely spiky, geographically distributed, high-scale. and unpredictable. How should you design this system?

A) Use API Gateway Invoking Lambdas which PutRecords into Kinesis, and EMR running Spark performing GetRecords on Kinesis to scale with spikes. Spark on EMR outputs the analysis to S3. which are sent out via email.
B) Use AWS(Amazon Web Service) Elasticsearch service and EC2 Auto Scaling groups. The Autoscaling groups scale based on click throughput and stream into the Elasticsearch domain, which is also scalable. Use Kibana to generate reports periodically.
C) Use a CloudFront distribution with access log delivery to S3. Clicks should be recorded as querystring GETsI to the distribution. Reports are built and sent by periodically running EMR jobs over the access logs in S3. .
D) Use a large Red Shift cluster to perform the analysis, and a fleet of Lambdas to perform record Inserts into the Red Shlft tables. Lambda will scale rapidly enough for the traffic spikes.