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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q298-Q303):

NEW QUESTION # 298
Why are more frequent snapshots or EBS Volumes faster?

• A. AWS provisions more disk throughput for burst capacity during snapshots if the drive has been pre-warmed by snapshotting and reading all blocks.
• B. The drive is pre-warmed, so block access is more rapid for volumes when every block on the device has already been read at least one time.
• C. The snapshots are incremental so that only the blocks on the device that have changed after your last snapshot are saved in the new snapshot.
• D. Blocks in EBS Volumes are allocated lazily, since while logically separated from other EBS Volumes, Volumes often share the same physical hardware. Snapshotting the first time forces full block range allocation, so the second snapshot doesn't need to perform the allocation phase and is faster.

Answer: C

Explanation:
After writing data to an EBS volume, you can periodically create a snapshot of the volume to use as a baseline for new volumes or for data backup. If you make periodic snapshots of a volume, the snapshots are incremental so that only the blocks on the device that have changed after your last snapshot are saved in the new snapshot. Even though snapshots are saved incrementally, the snapshot deletion process is designed so that you need to retain only the most recent snapshot in order to restore the volume.
http://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-creating-snapshot.html

NEW QUESTION # 299
Your application's Auto Scaling Group scales up too quickly, too much, and stays scaled when traffic decreases.
What should you do to fix this?

• A. Raise the CloudWatch Alarms threshold associated with your autoscaling group, so the scaling takes more of an increase in demand before beginning.
• B. Set a longer cooldown period on the Group, so the system stops overshooting the target capacity. The issue is that the scaling system does not allow enough time for new instances to begin servicing requests before measuring aggregate load again.
• C. Use larger instances instead of many smaller ones, so the Group stops scaling out so much and wasting resources as the OS level, since the OS uses a higher proportion of resources on smaller instances.
• D. Calculate the bottleneck or constraint on the compute layer, then select that as the new metric, and set the metric thresholds to the bounding values that begin to affect response latency.

Answer: D

Explanation:
Systems will always over-scale unless you choose the metric that runs out first and becomes constrained first.
You also need to set the thresholds of the metric based on whether or not latency is affected by the change, to justify adding capacity instead of wasting money.
Reference:
http://docs.aws.amazon.com/AutoScaling/latest/DeveloperGuide/policy_creating.html

NEW QUESTION # 300
The development team is creating a social media game which ranks users on a scoreboard. The current implementation uses an Amazon RDS for MySQL database for storing user data; however, the game cannot display scores quickly enough during performance testing.
Which service would provide the fastest retrieval times?

• A. Use AWS Batch to compute and deliver user and score content.
• B. Deploy Amazon CloudFront for user and score content delivery.
• C. Set up Amazon ElastiCache to deliver user and score content.
• D. Migrate user data to Amazon DynamoDB for managing content.

Answer: C

NEW QUESTION # 301
Which tool will Ansible not use, even if available, to gather facts?

• A. lsb_release
• B. Ansible setup module
• C. facter
• D. ohai

Answer: A

Explanation:
Ansible will use it's own `setup' module to gather facts for the local system. Additionally, if ohai or facter are installed, those will also be used and all variables will be prefixed with `ohai_' or
`facter_' respectively. `lsb_relase' is a Linux tool for determining distribution information.
Reference: http://docs.ansible.com/ansible/setup_module.html

NEW QUESTION # 302
Which of the following Cache Engines does Opswork have built in support for?

• A. Redis
• B. Both Redis and Memcache
• C. Memcache
• D. There is no built in support as of yet for any cache engine

Answer: C

Explanation:
Explanation
The AWS Documentation mentions
AWS OpsWorks Stacks provides built-in support for Memcached. However, if Redis better suits your requirements, you can customize your stack so that your application servers use OastiCache Redis.
Although it works with Redis clusters, AWS clearly specifies that AWS Opsworks stacks provide built in support for Memcached.
Amazon OastiCache is an AWS service that makes it easy to provide caching support for your application server, using either the Memcached or Redis caching engines. OastiCache can be used to improve the application server performance running on AWS Opsworks stacks.
For more information on Opswork and Cache engines please refer to the below link:
* http://docs