Amazon S3 Glacier Instant Retrieval is an archive storage class that delivers the lowest-cost storage for long- lived data that is rarely accessed and requires retrieval in milliseconds. With S3 Glacier Instant Retrieval, you can save up to 68% on storage costs compared to using the S3 Standard-Infrequent Access (S3 Standard-IA) storage class, when your data is accessed once per quarter.https://aws.amazon.com/s3/storage-classes/glacier
/instant-retrieval/
* Understanding Storage Requirements:
* Files are large and infrequently accessed, but need to be available within minutes when requested in the first year.
* Long-term (7-year) retention is required.
* Cost-effectiveness is a top priority.
* Why S3 Glacier Instant Retrieval:
* Matches the retrieval requirements (access within minutes).
* More cost-effective than S3 Standard for infrequently accessed data.
* Simpler to use than traditional Glacier where retrievals take hours.
* Why S3 Glacier Deep Archive:
* Most cost-effective S3 storage class for long term archival.
* Meets the 7-year retention requirement.
* S3 Lifecycle Policy:
* Automate the transition from Glacier Instant Retrieval to Glacier Deep Archive after one year.
* Optimize costs by matching storage classes to access patterns.

To monitor memory usage in Amazon Elastic Beanstalk environments, it's important to understand that default Elastic Beanstalk monitoring capabilities in Amazon CloudWatch do not track memory usage, as memory metrics are not collected by default. Instead, theAmazon CloudWatch agentmust be configured to collect memory usage metrics.
* Why Option C is Correct:
* TheAmazon CloudWatch agentcan be installed and configured to monitor system-level metrics such as memory and disk utilization.
* To enable memory tracking, developers need to install the CloudWatch agent on the Amazon Elastic Compute Cloud (EC2) instances associated with the Elastic Beanstalk environment.
* After installation, the agent can be configured to collect memory metrics, which can then be sent to CloudWatch for further analysis.
* How to Implement This Solution:
* Install the CloudWatch Agent:Use .ebextensions or AWS Systems Manager to install and configure the CloudWatch agent on the EC2 instances running in the Elastic Beanstalk environment.
* Modify CloudWatch Agent Configuration:Create a config.json file that specifies memory usage tracking and other desired metrics.
* Enable Metrics Reporting:The CloudWatch agent can push the metrics to CloudWatch, where they can be monitored.
* Why Other Options are Incorrect:
* Option A:Configuring the agent to push logs is not sufficient to track memory metrics. This option addresses logging but not system-level metrics like memory usage.
* Option B:The .ebextensions directory is used to customize Elastic Beanstalk environments but does not directly track memory metrics without additional configuration of the CloudWatch agent.
* Option D:Configuring a CloudWatch dashboard will only visualize the metrics that are already being collected. It will not enable memory usage tracking.
* AWS Documentation References:
* Amazon CloudWatch Agent Overview
* Elastic Beanstalk Customization Using .ebextensions
* Monitoring Custom Metrics

https://docs.aws.amazon.com/cognito/latest/developerguide/amazon-cognito-integrating-user-pools-with-identity-pools.html

AWS Systems Manager Parameter Store is a service that provides secure, hierarchical storage for configuration data and secrets. Parameter Store supports SecureString parameters, which are encrypted using AWS Key Management Service (AWS KMS) keys. SecureString parameters can be used to store license keys in AWS and retrieve them securely from automation scripts that run in EC2 instances or CloudFormation stacks. Parameter Store is a cost-effective solution because it does not charge for storing parameters or API calls. Reference: Working with Systems Manager parameters