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A company is using AWS CodePipeline for the CI/CD of an application to an Amazon EC2 Auto Scaling group. All AWS resources are defined in AWS
CloudFormation templates. The application artifacts are stored in an Amazon S3 bucket and deployed to the Auto Scaling group using instance user data scripts.
As the application has become more complex, recent resource changes in the CloudFormation templates have caused unplanned downtime.
How should a solutions architect improve the CI/CD pipeline to reduce the likelihood that changes in the templates will cause downtime?
A software as a service (SaaS) based company provides a case management solution to customers A3 part of the solution. The company uses a standalone Simple Mail Transfer Protocol (SMTP) server to send email messages from an application. The application also stores an email template for acknowledgement email messages that populate customer data before the application sends the email message to the customer.
The company plans to migrate this messaging functionality to the AWS Cloud and needs to minimize operational overhead.
Which solution will meet these requirements MOST cost-effectively?
In this solution, the company can use Amazon SES to send email messages, which will minimize operational overhead as SES is a fully managed service that handles sending and receiving email messages. The company can store the email template on Amazon SES with parameters for the customer data and use an AWS Lambda function to call the SendTemplatedEmail API operation, passing in the customer data to replace the parameters and the email destination. This solution eliminates the need to set up and manage an SMTP server on EC2 instances, which can be costly and time-consuming.
A software company has deployed an application that consumes a REST API by using Amazon API Gateway. AWS Lambda functions, and an Amazon DynamoDB table. The application is showing an increase in the number of errors during PUT requests. Most of the PUT calls come from a small number of clients that are authenticated with specific API keys.
A solutions architect has identified that a large number of the PUT requests originate from one client. The API is noncritical, and clients can tolerate retries of unsuccessful calls. However, the errors are displayed to customers and are causing damage to the API's reputation.
What should the solutions architect recommend to improve the customer experience?
https://aws.amazon.com/premiumsupport/knowledge-center/aws-batch-requests-error/
https://aws.amazon.com/premiumsupport/knowledge-center/api-gateway-429-limit/
A company has an application that analyzes and stores image data on premises The application receives millions of new image files every day Files are an average of 1 MB in size The files are analyzed in batches of 1 GB When the application analyzes a batch the application zips the imagestogether The application then archives the images as a single file in an on-premises NFS server for long-term storage
The company has a Microsoft Hyper-V environment on premises and has compute capacity available The company does not have storage capacity and wants to archive the images on AWS The company needs the ability to retrieve archived data within t week of a request.
The company has a 10 Gbps AWS Direct Connect connection between its on-premises data center and AWS. The company needs to set bandwidth limits and schedule archived images to be copied to AWS dunng non-business hours.
Which solution will meet these requirements MOST cost-effectively?
Deploy DataSync Agent:
Install the AWS DataSync agent as a VM in your Hyper-V environment. This agent facilitates the data transfer between your on-premises storage and AWS.
Configure Source and Destination:
Set up the source location to point to your on-premises NFS server where the image batches are stored.
Configure the destination location to be an Amazon S3 bucket with the Glacier Deep Archive storage class. This storage class is cost-effective for long-term storage with retrieval times of up to 12 hours.
Create DataSync Tasks:
Create and configure DataSync tasks to manage the data transfer. Schedule these tasks to run during non-business hours to minimize bandwidth usage during peak times. The tasks will handle the copying of data batches from the NFS server to the S3 bucket.
Set Bandwidth Limits:
In the DataSync configuration, set bandwidth limits to control the amount of data being transferred at any given time. This ensures that your network's performance is not adversely affected during business hours.
Delete On-Premises Data:
After successfully copying the data to S3 Glacier Deep Archive, configure the DataSync task to delete the data from your on-premises NFS server. This helps manage storage capacity on-premises and ensures data is securely archived on AWS.
This approach leverages AWS DataSync for efficient, secure, and automated data transfer, and S3 Glacier Deep Archive for cost-effective long-term storage.
Reference
AWS DataSync Overview41.
AWS Storage Blog on DataSync Migration40.
Amazon S3 Transfer Acceleration Documentation42.
A company needs to architect a hybrid DNS solution. This solution will use an Amazon Route 53 private hosted zone for the domain cloud.example.com for the resources stored within VPCs.
The company has the following DNS resolution requirements:
* On-premises systems should be able to resolve and connect to cloud.example.com.
* All VPCs should be able to resolve cloud.example.com.
There is already an AWS Direct Connect connection between the on-premises corporate network and AWS Transit Gateway. Which architecture should the company use to meet these requirements with the HIGHEST performance?
Amazon Route 53 Resolver is a managed DNS resolver service from Route 53 that helps to create conditional forwarding rules to redirect query traffic1. By associating the private hosted zone to all the VPCs, the solutions architect can enable DNS resolution for cloud.example.com within the VPCs. By creating a Route 53 inbound resolver in the shared services VPC, the solutions architect can enable DNS resolution for cloud.example.com from on-premises systems. By attaching all VPCs to the transit gateway, the solutions architect can enable connectivity between the VPCs and the on-premises network through AWS Direct Connect. By creating forwarding rules in the on-premises DNS server for cloud.example.com that point to the inbound resolver, the solutions architect can direct DNS queries for cloud.example.com to the Route 53 Resolver endpoint in AWS. This solution will provide the highest performance as it leverages Route 53 Resolver's optimized routing and caching capabilities.
