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NEW QUESTION 39
Your IT company is currently hosting a production environment in Elastic beanstalk. You understand that the Elastic beanstalk service provides a facility known as Managed updates which are minor and patch version updates which are periodically required for your system. Your IT supervisor is worried about the impact that these updates would have on the system. What can you tell about the Elastic beanstalk service with regards to managed updates

A. Elastic Beanstalk applies managed updates with no reduction in capacityB. Package updates can be configurable weekly maintenance windowC. All of the aboveD. Elastic Beanstalk applies managed updates with no downtime

Answer: C

Explanation:
Explanation
The AWS Documentation mentions the following on package updates for the Clastic beanstalk environment You can configure your environment to apply minor and patch version updates automatically during a configurable weekly maintenance window with Managed Platform Updates. Elastic Beanstalk applies managed updates with no downtime or reduction in capacity, and cancels the update immediately if instances running your application on the new version fail health checks.
For more information on Elastic beanstalk managed updates please refer to the URL:
* https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/environment-platform-update-managed.html
* http://docs.aws.amazon.com/elasticbeanstalk/latest/dg/using-features.platform.upgrade.html

 

NEW QUESTION 40
A business has an application that consists of five independent AWS Lambda functions. The DevOps Engineer has built a CI/CD pipeline using AWS CodePipeline and AWS CodeBuild that builds, tests, packages, and deploys each Lambda function in sequence. The pipeline uses an Amazon CloudWatch Events rule to ensure the pipeline execution starts as quickly as possible after a change is made to the application source code.
After working with the pipeline for a few months the DevOps Engineer has noticed the pipeline takes too long to complete.
What should the DevOps Engineer implement to BEST improve the speed of the pipeline?

A. Modify the CodePipeline configuration to execute actions for each Lambda function in parallel by specifying the same runOrder.B. Modify the CodeBuild projects within the pipeline to use a compute type with more available network throughput.C. Create a custom CodeBuild execution environment that includes a symmetric multiprocessing configuration to run the builds in parallel.D. Modify each CodeBuild project to run within a VPC and use dedicated instances to increase throughput.

Answer: D

 

NEW QUESTION 41
During metric analysis, your team has determined that the company's website is experiencing response times during peak hours that are higher than anticipated.
You currently rely on Auto Scaling to make sure that you are scaling your environment during peak windows.
How can you improve your Auto Scaling policy to reduce this high response time? Choose 2 answers.

A. Create a script that runs and monitors your servers; when it detects an anomaly in load, it posts to an Amazon SNS topic that triggers Elastic Load Balancing to add more servers to the load balancer.B. Push custom metrics to CloudWatch for your application that include more detailed information about your web application, such as how many requests it is handling and how many are waiting to be processed.C. Update the CloudWatch metric used for your Auto Scaling policy, and enable sub-minute granularity to allow auto scaling to trigger faster.D. Push custom metrics to CloudWatch to monitor your CPU and network bandwidth from your servers, which will allow your Auto Scaling policy to have better fine-grain insight.E. Increase your Auto Scaling group's number of max servers.

Answer: B,E

 

NEW QUESTION 42
You are building out a layer in a software stack on AWS that needs to be able to scale out to react to increased
demand as fast as possible. You are running the code on EC2 instances in an Auto Scaling Group behind an
ELB. Which application code deployment method should you use?

A. Create a new Auto Scaling Launch Configuration with UserData scripts configured to pull the latest
code at all times.B. Bake an AMI when deploying new versions of code, and use that AMI for the Auto Scaling Launch
Configuration.C. Create a Dockerfile when preparing to deploy a new version to production and publish it to S3. Use
UserData in the Auto Scaling Launch configuration to pull down the Dockerfile from S3 and run it when
new instances launch.D. SSH into new instances that come online, and deploy new code onto the system by pulling it from an S3
bucket, which is populated by code that you refresh from source control on new pushes.

Answer: B

Explanation:
Explanation
Since the time required to spin up an instance is required to be fast, its better to create an AMI rather than use
User Data. When you use User Data, the script will be
run during boot up, and hence this will be slower.
An Amazon Machine Image (AMI) provides the information required to launch an instance, which is a virtual
server in the cloud. You specify an AM I when you launch
an instance, and you can launch as many instances from the AMI as you need. You can also launch instances
from as many different AMIs as you need.
For more information on the AMI, please refer to the below link:
* http://docs.aws.amazon.com/AWSCC2/latest/UserGuide/AMIs.html

 

NEW QUESTION 43
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