What is required to achieve gigabit network throughput on EC2?
You already selected cluster-compute, 10GB instances with enhanced networking, and your workload is already network-bound, but you are not seeing 10 gigabit speeds.

• A.Enable biplex networking on your servers, so packets are non-blocking in both directions and there's no switching overhead.
• B.Ensure the instances are in different VPCs so you don't saturate the Internet Gateway on any one VPC.
• C.Select PIOPS for your drives and mount several, so you can provision sufficient disk throughput.
• D.Use a placement group for your instances so the instances are physically near each other in the same Availability Zone.

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The Deployment team has grown substantially in recent months and so has the number of projects that use separate code repositories. The current process involves configuring AWS CodePipeline manually, and there have been service limit alerts for the count of Amazon S3 buckets. Which pipeline option will reduce S3 bucket sprawl alerts?

• A.Combine the multiple separate code repositories into a single one, and deploy using a global AWS CodePipeline that has logic for each project.
• B.Create new pipelines by using the AWS API or AWS CLI, and configure them to use a single global S3 bucket with separate prefixes for each project.
• C.Create a new pipeline in a different region for each project to bypass the service limits for S3 buckets in a single region.
• D.Create a new pipeline and for S3 bucket for each project by using the AWS API or AWS CLI to bypass the service limits for S3 buckets in a single account

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You work for a company that automatically tags photographs using artificial neural networks (ANNs), which run on GPUs using C++. You receive millions of images at a time, but only 3 times per day on average. These images are loaded into an AWS S3 bucket you control for you in a batch, and then the customer publishes a JSON-formatted manifest into another S3 bucket you control as well. Each image takes 10 milliseconds to process using a full GPU. Your neural network software requires 5 minutes to bootstrap. Image tags are JSON objects, and you must publish them to an S3 bucket. Which of these is the best system architectures for this system?

• A.Create an OpsWorks Stack with two Layers. The first contains lifecycle scripts for launching and bootstrapping an HTTP API on G2 instances for image processing, and the second has an always-on instance which monitors the S3 manifest bucket for new files. When a new file is detected, request instances to boot on the artificial neural network layer. When the instances are booted and the HTTP APIs are up, submit processing requests to individual instances.
• B.Make an S3 notification configuration which publishes to AWS Lambda on the manifest bucket. Make the Lambda create a CloudFormation Stack which contains the logic to construct an autoscaling worker tier of EC2 G2 instances with the artificial neural network code on each instance. Create an SQS queue of the images in the manifest. Tear the stack down when the queue is empty.
• C.Deploy your artificial neural network code to AWS Lambda as a bundled binary for the C++ extension.
  Make an S3 notification configuration on the manifest, which publishes to another AWS Lambda running controller code. This controller code publishes all the images in the manifest to AWS Kinesis.
  Your ANN code Lambda Function uses the Kinesis as an Event Source. The system automatically scales when the stream contains image events.
• D.Create an Auto Scaling Load Balanced Elastic Beanstalk worker tier Application and Environment.
  Deploy the artificial neural network code to G2 instances in this tier. Set the desired capacity to 1. Make the code periodically check S3 for new manifests. When a new manifest is detected, push all of the images in the manifest into the SQS queue associated with the Elastic Beanstalk worker tier.

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You run a SIP-based telephony application that uses Amazon EC2 for its web tier and uses MySQL on Amazon RDS as its database.
The application stores only the authentication profile data for its existing users in the database and therefore is read-intensive.
Your monitoring system shows that your web instances and the database have high CPU utilization.
Which of the following steps should you take in order to ensure the continual availability of your application? Choose 2 answers

• A.Set up an Auto Scaling group for the application tier and a policy that scales based on the Amazon RDS CloudWatch CPU utilization metric.
• B.Set up an Auto Scaling group for the application tier and a policy that scales based on the Amazon EC2 CloudWatch CPU utilization metric.
• C.Switch to General Purpose (SSD) Storage from Provisioned IOPS Storage (PIOPS) for the Amazon RDS database.
• D.Vertically scale up the Amazon EC2 instances manually.
• E.Use multiple Amazon RDS read replicas.
• F.Use a CloudFront RTMP download distribution with the application tier as the origin for the distribution.

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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 CloudFront.
• C.Create read replicas for RDS since the load is mostly reads.
• D.Create a Multi-AZ RDS installs and route read traffic to standby.

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