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A company has a latency-sensitive trading platform that uses Amazon DynamoDB as a storage backend. The company configured the DynamoDB table to use on-demand capacity mode. A solutions architect needs to design a solution to improve the performance of the trading platform. The new solution must ensure high availability for the trading platform.
Which solution will meet these requirements with the LEAST latency?
A. Create a two-node DynamoDB Accelerator (DAX) cluster Configure an application to read and write data by using DAX.
B. Create a three-node DynamoDB Accelerator (DAX) cluster. Configure an application to read data by using DAX and to write data directly to the DynamoDB table.
C. Create a three-node DynamoDB Accelerator (DAX) cluster. Configure an application to read data directly from the DynamoDB table and to write data by using DAX.
D. Create a single-node DynamoD8 Accelerator (DAX) cluster. Configure an application to read data by using DAX and to write data directly to the DynamoD8 table.
Explanation:
A DAX cluster can be deployed with one or two nodes for development or test workloads. One- and two-node clusters are not fault-tolerant, and we don't recommend using fewer than three nodes for production use. If a one- or two-node cluster encounters software or hardware errors, the cluster can become unavailable or lose cached data.A DAX cluster can be deployed with one or two nodes for development or test workloads. One- and two-node clusters are not fault-tolerant, and we don't recommend using fewer than three nodes for production use. If a one- or two-node cluster encounters software or hardware errors, the cluster can become unavailable or lose cached data.
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/DAX.concepts.cluster.html
A company is running a two-tier web-based application in an on-premises data center. The application layer consists of a single server running a stateful application. The application connects to a PostgreSQL database running on a separate server. The application’s user base is expected to grow significantly, so the company is migrating the application and database to AWS. The solution will use Amazon Aurora PostgreSQL, Amazon EC2 Auto Scaling, and Elastic Load Balancing.
Which solution will provide a consistent user experience that will allow the application and database tiers to scale?
A. Enable Aurora Auto Scaling for Aurora Replicas. Use a Network Load Balancer with the least outstanding requests routing algorithm and sticky sessions enabled.
B. Enable Aurora Auto Scaling for Aurora writers. Use an Application Load Balancer with the round robin routing algorithm and sticky sessions enabled.
C. Enable Aurora Auto Scaling for Aurora Replicas. Use an Application Load Balancer with the round robin routing and sticky sessions enabled.
D. Enable Aurora Scaling for Aurora writers. Use a Network Load Balancer with the least outstanding requests routing algorithm and sticky sessions enabled.
Explanation:
Aurora Auto Scaling enables your Aurora DB cluster to handle sudden increases in connectivity or workload. When the connectivity or workload decreases, Aurora Auto Scaling removes unnecessary Aurora Replicas so that you don't pay for unused provisioned DB instances
A company is running an application on Amazon EC2 instances in the AWS Cloud. The application is using a MongoDB database with a replica set as its data tier. The MongoDB database is installed on systems in the company's on-premises data center and is accessible through an AWS Direct Connect connection to the data center environment.
A solutions architect must migrate the on-premises MongoDB database to Amazon DocumentDB (with MongoDB compatibility).
Which strategy should the solutions architect choose to perform this migration?
A. Create a fleet of EC2 instances. Install MongoDB Community Edition on the EC2 instances, and create a database. Configure continuous synchronous replication with the database that is running in the on-premises data center.
B. Create an AWS Database Migration Service (AWS DMS) replication instance. Create a source endpoint for the on-premises MongoDB database by using change data capture (CDC). Create a target endpoint for the Amazon DocumentDB database. Create and run a DMS migration task.
C. Create a data migration pipeline by using AWS Data Pipeline. Define data nodes for the on-premises MongoDB database and the Amazon DocumentDB database. Create a scheduled task to run the data pipeline.
D. Create a source endpoint for the on-premises MongoDB database by using AWS Glue crawlers. Configure continuous asynchronous replication between the MongoDB database and the Amazon DocumentDB database.
Explanation:
https://aws.amazon.com/getting-started/hands-on/move-to-managed/migrate-mongodb-to-documentdb/
A company's interactive web application uses an Amazon CloudFront distribution to serve images from an Amazon S3 bucket. Occasionally, third-party tools ingest corrupted images into the S3 bucket. This image corruption causes a poor user experience in the application later. The company has successfully implemented and tested Python logic to detect corrupt images.
A solutions architect must recommend a solution to integrate the detection logic with minimal latency between the ingestion and serving.
Which solution will meet these requirements?
A. Use a Lambda@Edge function that is invoked by a viewer-response event.
B. Use a Lambda@Edge function that is invoked by an origin-response event.
C. Use an S3 event notification that invokes an AWS Lambda function.
D. Use an S3 event notification that invokes an AWS Step Functions state machine.
Explanation:
This solution will allow the detection logic to be run as soon as the image is uploaded to the S3 bucket, before it is served to users via the CloudFront distribution. This way, the detection logic can quickly identify any corrupted images and prevent them from being served to users, minimizing latency between ingestion and serving.
[Reference: AWS Lambda@Edge documentation:
https://docs.aws.amazon.com/lambda/latest/dg/lambda-edge.html You can use Lambda@Edge to run your code in response to CloudFront events, such as a viewer request, an origin request, a response, or an error., , ]
A company needs to optimize the cost of backups for Amazon Elastic File System (Amazon EFS). A solutions architect has already configured a backup plan in AWS Backup for the EFS backups. The backup plan contains a rule with a lifecycle configuration to transition EFS backups to cold storage after 7 days and to keep the backups for an additional 90 days.
After I month, the company reviews its EFS storage costs and notices an increase in the EFS backup costs. The EFS backup cold storage produces almost double the cost of the EFS warm backup storage.
What should the solutions architect do to optimize the cost?
A. Modify the backup rule's lifecycle configuration to move the EFS backups to cold storage after 1 day. Set the backup retention period to 30 days.
B. Modify the backup rule's lifecycle configuration to move the EFS backups to cold storage after 8 days. Set the backup retention period to 30 days.
C. Modify the backup rule's lifecycle configuration to move the EFS backups to cold storage after 1 day. Set the backup retention period to 90 days.
D. Modify the backup rule's lifecycle configuration to move the EFS backups to cold storage after 8 days. Set the backup retention period to 98 days.
Explanation:
The cost of EFS backup cold storage is $0.01 per GB-month, whereas the cost of EFS backup warm storage is $0.05 per GB-month1. Therefore, moving the backups to cold storage as soon as possible will reduce the storage cost. However, cold storage backups must be retained for a minimum of 90 days2, otherwise they incur a pro-rated charge equal to the storage charge for the remaining days1. Therefore, setting the backup retention period to 30 days will incur a penalty of 60 days of cold storage cost for each backup deleted. This penalty will still be lower than keeping the backups in warm storage for 7 days and then in cold storage for 83 days, which is the current configuration. Therefore, option A is the most cost-effective solution.
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