Amazon SAP-C02 Practice Test - Questions Answers, Page 15

Moving the application frontend to a static website that is hosted on Amazon S3 will save cost as S3 is cheaper than running EC2 instances.

Using Spot instances for the backend EC2 instances will also save cost, as they are significantly cheaper than On-Demand instances. This will be suitable for the application, as it has minimal traffic during the rest of the day, and the availability of spot instances will not negatively affect the application's availability.

Amazon S3 pricing: https://aws.amazon.com/s3/pricing/

Amazon EC2 Spot Instances documentation: https://aws.amazon.com/ec2/spot/

AWS Elastic Beanstalk documentation: https://aws.amazon.com/elasticbeanstalk/

Amazon Elastic Compute Cloud (EC2) pricing: https://aws.amazon.com/ec2/pricing/

They all mention using spot instances and EKS based on EC2. A spot instance is not appropriate for a production server and the company is developing new application designed for AWS Fargate, which means we must plan the future cost improvement including AWS Fargate. https://aws.amazon.com/savingsplans/compute-pricing/

The company wants to serve static content from an S3 bucket during the maintenance period. To do this, the following steps are required:

Upload static informational content to the S3 bucket. This will provide the source of the content that will be served to the visitors.

Set the S3 bucket as a second origin in the original CloudFront distribution. Configure the distribution and the S3 bucket to use an origin access identity (OAI). This will allow CloudFront to access the S3 bucket securely and prevent public access to the bucket.

During the weekly maintenance, edit the default cache behavior to use the S3 origin. Revert the change when the maintenance is complete. This will redirect all web requests to the S3 bucket instead of the Elastic Beanstalk domain name.

The other options are not correct because:

Creating a new CloudFront distribution is not necessary and would require changing the alternate domain name configuration.

Creating a cache behavior for the S3 origin on a new distribution would not work because the visitors would still access the original distribution using the alternate domain name.

Configuring Elastic Beanstalk to serve traffic from the S3 bucket is not possible and would not achieve the desired result.

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/DownloadDistS3AndCustomOrigins.html

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/private-content-restricting-access-to-s3.html

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/distribution-web-values-specify.html#DownloadDistValuesPathPattern

A Lambda function alias allows you to point to a specific version of a function and also can be updated to point to a new version of the function without modifying the client application. This way, the company can test different versions of the function with different environment variables and, once the optimal parameters are found, update the alias to point to the new version, without the need to update the client application.

By using this approach, the company can simplify the process of updating the environment variables, minimize disruption to users, and reduce the operational overhead.

AWS Lambda documentation: https://aws.amazon.com/lambda/

AWS Lambda Aliases documentation: https://docs.aws.amazon.com/lambda/latest/dg/aliases-intro.html

AWS Lambda versioning and aliases documentation: https://aws.amazon.com/blogs/compute/versioning-aliases-in-aws-lambda/

AWS Global Accelerator is a service that directs traffic to optimal endpoints (in this case, the Application Load Balancer) based on the health of the endpoints and network routing. It allows you to create an accelerator that directs traffic to multiple endpoint groups, one for each Region where the application is deployed. The accelerator uses the AWS global network to optimize the traffic routing to the healthy endpoint.

By using Global Accelerator, the company can use a single static IP address for the apex domain, and traffic will be directed to the optimal endpoint based on the user's location, without the need for additional load balancers or routing policies.

AWS Global Accelerator documentation: https://aws.amazon.com/global-accelerator/

Routing User Traffic to the Optimal AWS Region using Global Accelerator documentation: https://aws.amazon.com/blogs/networking-and-content-delivery/routing-user-traffic-to-the-optimal-aws-region-using-global-accelerator/

Deploying the shared libraries and custom classes to a Docker image and uploading the image to Amazon Elastic Container Registry (Amazon ECR) and creating a Lambda layer that uses the Docker image as the source. Then, deploying the API's Lambda functions as Zip packages and configuring the packages to use the Lambda layer would meet the requirements for simplifying the deployment and optimizing for code reuse.

A Lambda layer is a distribution mechanism for libraries, custom runtimes, and other function dependencies. It allows you to manage your in-development function code separately from your dependencies, this way you can easily update your dependencies without having to update your entire function code.

By deploying the shared libraries and custom classes to a Docker image and uploading the image to Amazon Elastic Container Registry (ECR), it makes it easy to manage and version the dependencies. This way, the company can use the same version of the dependencies across different Lambda functions.

By creating a Lambda layer that uses the Docker image as the source, the company can configure the API's Lambda functions to use the layer, reducing the need to include the dependencies in each function package, and making it easy to update the dependencies across all functions at once.

AWS Lambda Layers documentation: https://docs.aws.amazon.com/lambda/latest/dg/configuration-layers.html

AWS Elastic Container Registry (ECR) documentation: https://aws.amazon.com/ecr/

Building Lambda Layers with Docker documentation: https://aws.amazon.com/blogs/compute/building-lambda-layers-with-docker/

The company should use AWS IoT Greengrass to deploy the ML model to the local server and provide local feedback to the factory workers.AWS IoT Greengrass is a service that extends AWS cloud capabilities to local devices, allowing them to collect and analyze data closer to the source of information, react autonomously to local events, and communicate securely with each other on local networks1.AWS IoT Greengrass also supports ML inference at the edge, enabling devices to run ML models locally without requiring internet connectivity2.

The other options are not correct because:

Setting up an Amazon Kinesis video stream from each IP camera to AWS would not work if the factory's internet connectivity is down. It would also incur unnecessary costs and latency to stream video data to the cloud and back.

Ordering an AWS Snowball device would not be a scalable or cost-effective solution for deploying the ML model.AWS Snowball is a service that provides physical devices for data transfer and edge computing, but it is not designed for continuous operation or frequent updates3.

Deploying Amazon Monitron devices on each IP camera would not work because Amazon Monitron is a service that monitors the condition and performance of industrial equipment using sensors and machine learning, not cameras4.

https://aws.amazon.com/greengrass/

https://docs.aws.amazon.com/greengrass/v2/developerguide/use-machine-learning-inference.html

https://aws.amazon.com/snowball/

https://aws.amazon.com/monitron/

https://aws.amazon.com/blogs/architecture/accelerating-your-migration-to-aws/ Build a business case with AWS Migration Evaluator The foundation for a successful migration starts with a defined business objective (for example, growth or new offerings). In order to enable the business drivers, the established business case must then be aligned to a technical capability (increased security and elasticity). AWS Migration Evaluator (formerly known as TSO Logic) can help you meet these objectives. To get started, you can choose to upload exports from third-party tools such as Configuration Management Database (CMDB) or install a collector agent to monitor. You will receive an assessment after data collection, which includes a projected cost estimate and savings of running your on-premises workloads in the AWS Cloud. This estimate will provide a summary of the projected costs to re-host on AWS based on usage patterns. It will show the breakdown of costs by infrastructure and software licenses. With this information, you can make the business case and plan next steps.

'The AWS WAF API supports security automation such as blacklisting IP addresses that exceed request limits, which can be useful for mitigating HTTP flood attacks.' > https://aws.amazon.com/blogs/security/how-to-protect-dynamic-web-applications-against-ddos-attacks-by-using-amazon-cloudfront-and-amazon-route-53/