SAA-C03 AWS Certified Solutions Architect - Associate (SAA-C03) Questions and Answers

Amazon EC2 Auto Scaling offers the ability to add lifecycle hooks to your Auto Scaling groups. These hooks let you create solutions that are aware of events in the Auto Scaling instance lifecycle, and then perform a custom action on instances when the corresponding lifecycle event occurs. (https://docs.aws.amazon.com/autoscaling /ec2/userguide/lifecycle-hooks.html)

The best option is to use the AWS Snow Family console to order several AWS Snowball Edge Storage Optimized devices and use the devices to transfer the data to Amazon S3. Snowball Edge is a petabyte-scale data transfer device that can help transfer large amounts of data securely and quickly. Using Snowball Edge can be the most cost-effective solution for transferring large amounts of data over long distances and can help meet the requirement of transferring 600 TB of data within two weeks.

Using Amazon SQS will help minimize the number of connections to the database, as the API will write data to a queue instead of directly to the database. Additionally, using an AWS Lambda function that Amazon SQS invokes to write data from the queue to the database will help ensure that data is not lost during periods of heavy traffic, as the queue will serve as a buffer between the API and the database.

This answer is correct because it meets the requirements of securely migrating the existing data to AWS and satisfying the new regulation. AWS DataSync is a service that makes it easy to move large amounts of data online between on-premises storage and Amazon S3. DataSync automatically encrypts data in transit and verifies data integrity during transfer. AWS CloudTrail is a service that records AWS API calls for your account and delivers log files to Amazon S3. CloudTrail can log data events, which show the resource operations performed on or within a resource in your AWS account, such as S3 object-level API activity. By using CloudTrail to log data events, you can audit access at all levels of the stored data.

References:

https://docs.aws.amazon.com/datasync/latest/userguide/what-is-datasync.html

https://docs.aws.amazon.com/awscloudtrail/latest/userguide/logging-data-events-with-cloudtrail.html

Session Manager is a fully managed AWS Systems Manager capability. With Session Manager, you can manage your Amazon Elastic Compute Cloud (Amazon EC2) instances, edge devices, on-premises servers, and virtual machines (VMs). You can use either an interactive one-click browser-based shell or the AWS Command Line Interface (AWS CLI). Session Manager provides secure and auditable node management without the need to open inbound ports, maintain bastion hosts, or manage SSH keys. Session Manager also allows you to comply with corporate policies that require controlled access to managed nodes, strict security practices, and fully auditable logs with node access details, while providing end users with simple one-click cross-platform access to your managed nodes. https://docs.aws.amazon.com/systems-manager/latest/userguide/session-manager.html

https://aws.amazon.com/blogs/security/how-to-prevent-uploads-of-unencrypted-objects-to- amazon-s3/#:~:text=Solution%20overview,console%2C%20CLI%2C%20or%20SDK.&text=To%20encrypt%20an%20object%20at,S3%2C%20or%20SSE%2DKMS.

Amazon Aurora Serverless for MySQL is a fully managed, auto-scaling relational database service that scales up or down automatically based on the application demand. This service provides all the capabilities of Amazon Aurora, such as high availability, durability, and security, without requiring the customer to provision any database instances. With Amazon Aurora Serverless for MySQL, the sales team can enjoy minimal downtime since the database is designed to automatically scale to accommodate the increased traffic. Additionally, the service allows the customer to pay only for the capacity used, making it cost-effective for infrequent access patterns. Amazon RDS for MySQL could also be an option, but it requires the customer to select an instance type, and the database administrator would need to monitor and adjust the instance size manually to accommodate the increasing traffic.

https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-mixed-instances-groups.html

AWS Snowball is a secure data transport solution that accelerates moving large amounts of data into and out of the AWS cloud. It can move up to 80 TB of data at a time, and provides a network bandwidth of up to 50 Mbps, so it is well-suited for the task. Additionally, it is secure and easy to use, making it the ideal solution for this migration.

Frequent feature testing -

- Multiple Elastic Beanstalk environments can be created easily for development, testing and production use cases.

- Traffic can be routed between environments for A/B testing and feature iteration using simple URL swapping techniques. No complex routing rules or infrastructure changes required.

The solution that meets the requirements is to develop an on-premises custom identity broker application or process that uses AWS Security Token Service (AWS STS) to get short-lived credentials. This solution allows the company to use its existing LDAP directory service to authenticate its users to the AWS Management Console, without requiring SAML compatibility. The custom identity broker application or process can act as a proxy between the LDAP directory service and AWS STS, and can request temporary security credentials for the users based on their LDAP attributes and roles. The users can then use these credentials to access the AWS Management Console via a sign-in URL generated by the identity broker. This solution also enhances security by using short-lived credentials that expire after a specified duration.

The other solutions do not meet the requirements because they either require SAML compatibility or do not provide access to the AWS Management Console. Enabling AWS IAM Identity Center (AWS Single Sign-On) between AWS and the on-premises LDAP would require the LDAP directory service to support SAML 2.0, which is not the case for this scenario. Creating an IAM policy that uses AWS credentials and integrating the policy into LDAP would not provide access to the AWS Management Console, but only to the AWS APIs. Setting up a process that rotates the IAM credentials whenever LDAP credentials are updated would also not provide access to the AWS Management Console, but only to the AWS CLI. Therefore, these solutions are not suitable for the given requirements.

The best solution to meet these requirements with the least amount of operational overhead is to enable Amazon DynamoDB Streams on the table and use triggers to write to a single Amazon Simple Notification Service (Amazon SNS) topic to which the teams can subscribe. This solution requires minimal configuration and infrastructure setup, and Amazon DynamoDB Streams provide a low-latency way to capture changes to the DynamoDB table. The triggers automatically capture the changes and publish them to the SNS topic, which notifies the internal teams.

https://aws.amazon.com/caching/session-management/

Windows file server is on-premise and we need something to replicate the data to the cloud, the only option we have is AWS FSx for Windows File Server. Also, since the information is confidential and sensitive, we also want to make sure that the appropriate users have access to it in a secure manner. https://docs.aws.amazon.com/fsx/ latest/WindowsGuide/what-is.html

The combination of steps that will accomplish the task of making the web server accessible from everywhere on port 443 is to create a security group with a rule to allow TCP port 443 from source 0.0.0.0/0 (A) and to update the network ACL to allow inbound TCP port 443 from source 0.0.0.0/0 (C). This will ensure that traffic to port 443 is allowed both at the security group level and at the network ACL level, which will make the web server accessible from everywhere on port 443.

Amazon S3 is a highly scalable, durable, and cost-effective object storage service that can store millions of images1. Amazon DynamoDB is a fully managed NoSQL database that can handle high throughput and low latency for key-value and document data2. By using S3 to store the images and DynamoDB to store the geographic codes and image S3 URLs, the solution can achieve high availability and scalability during natural disasters. It can also leverage DynamoDB’s features such as caching, auto-scaling, and global tables to improve performance and reduce costs2.

A. Store the images and geographic codes in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance. This solution will not meet the requirement of scalability and cost-effectiveness, as Oracle is a relational database that may not handle large volumes of unstructured data such as images efficiently3. It also involves higher licensing and operational costs than S3 and DynamoDB12.

C. Store the images and geographic codes in an Amazon DynamoDB table Configure DynamoDB Accelerator (DAX) during times of high load. This solution will not meet the requirement of cost-effectiveness, as storing images in DynamoDB will consume more storage space and incur higher charges than storing them in S312. It will also require additional configuration and management of DAX clusters to handle high load.

D. Store the images in Amazon S3 buckets Store geographic codes and image S3 URLs in a database table Use Oracle running on an Amazon RDS Multi-AZ DB instance. This solution will not meet the requirement of scalability and cost-effectiveness, as Oracle is a relational database that may not handle high throughput and low latency for key-value data such as geographic codes efficiently3. It also involves higher licensing and operational costs than DynamoDB2.

Reference URL: https://dynobase.dev/dynamodb-vs-s3/

https://docs.aws.amazon.com/sns/latest/dg/sns-server-side-encryption.html https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-server-side-encryption.html

https://aws.amazon.com/about-aws/whats-new/2018/04/announcing-s3-one-zone-infrequent-access-a-new-amazon-s3-storage-class/?nc1=h_ls

The most suitable design change for the company’s application is to request strongly consistent reads for the table. This change will ensure that the requests to the table return the latest data, reflecting the updates from all prior write operations.

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB supports two types of read consistency: eventually consistent reads and strongly consistent reads. By default, DynamoDB uses eventually consistent reads, unless users specify otherwise1.

Eventually consistent reads are reads that may not reflect the results of a recently completed write operation. The response might not include the changes because of the latency of propagating the data to all replicas. If users repeat their read request after a short time, the response should return the updated data. Eventually consistent reads are suitable for applications that do not require up-to-date data or can tolerate eventual consistency1.

Strongly consistent reads are reads that return a result that reflects all writes that received a successful response prior to the read. Users can request a strongly consistent read by setting the ConsistentRead parameter to true in their read operations, such as GetItem, Query, or Scan. Strongly consistent reads are suitable for applications that require up-to-date data or cannot tolerate eventual consistency1.

The other options are not correct because they do not address the issue of read consistency or are not relevant for the use case. Adding read replicas to the table is not correct because this option is not supported by DynamoDB. Read replicas are copies of a primary database instance that can serve read-only traffic and improve availability and performance. Read replicas are available for some relational database services, such as Amazon RDS or Amazon Aurora, but not for DynamoDB2. Using a global secondary index (GSI) is not correct because this option is not related to read consistency. A GSI is an index that has a partition key and an optional sort key that are different from those on the base table. A GSI allows users to query the data in different ways, with eventual consistency3. Requesting eventually consistent reads for the table is not correct because this option is already the default behavior of DynamoDB and does not solve the problem of requests not returning the latest data.

References:

Read consistency - Amazon DynamoDB

Working with read replicas - Amazon Relational Database Service

Working with global secondary indexes - Amazon DynamoDB

https://aws.amazon.com/blogs/compute/building-loosely-coupled-scalable-c-applications- with-amazon-sqs-and-amazon-sns/

https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-dead-letter-queues.html

CloudFront uses a local cache to provide the response, AWS Global accelerator proxies requests and connects to the application all the time for the response.

https://docs.aws.amazon.com/AmazonCloudFron t/latest/DeveloperGuide/private-content-restricting-access-to-s3.html#private-content-granting-permissions-to-oai

As they would like to retrieve the data with sub-millisecond, DynamoDB with DAX is the answer. DynamoDB supports some of the world's largest scale applications by providing consistent, single-digit millisecond response times at any scale. You can build applications with virtually unlimited throughput and storage.

https://aws.amazon.com/dynamodb/dax/?nc1=h_ls

AURORA is 5x performance improvement over MySQL on RDS and handles more read requests than write,; maintaining high availability = Multi-AZ deployment

"For archive data that needs immediate access, such as medical images, news media assets, or genomics data, choose the S3 Glacier Instant Retrieval storage class, an archive storage class that delivers the lowest cost storage with milliseconds retrieval. For archive data that does not require immediate access but needs the flexibility to retrieve large sets of data at no cost, such as backup or disaster recovery use cases, choose S3 Glacier Flexible Retrieval (formerly S3 Glacier), with retrieval in minutes or free bulk retrievals in 5-12 hours." https://aws.amazon.com/about-aws/whats-new/2021/11/amazon-s3-glacier-instant-retrieval-storage-class/

To launch a one-deal-a-day website on AWS with millisecond latency during peak hours and with the least operational overhead, the best option is to use an Amazon S3 bucket to host the website's static content, deploy an Amazon CloudFront distribution, set the S3 bucket as the origin, use Amazon API Gateway and AWS Lambda functions for the backend APIs, and store the data in Amazon DynamoDB. This option requires minimal operational overhead and can handle millions of requests each hour with millisecond latency during peak hours. Therefore, option D is the correct answer.

https://aws.amazon.com/vi/caching/session-management/

In order to address scalability and to provide a shared data storage for sessions that can be accessible from any individual web server, you can abstract the HTTP sessions from the web servers themselves. A common solution to for this is to leverage an In-Memory Key/Value store such as Redis and Memcached. ElastiCache offerings for In-Memory key/value stores include ElastiCache for Redis, which can support replication, and ElastiCache for Memcached which does not support replication.

https://docs.aws.amazon.com/whitepapers/latest/disaster-recovery-workloads-on-aws/disaster-recovery-options-in-the-cloud.html

To improve the architecture of this application, the best solution would be to use Amazon Simple Queue Service (Amazon SQS) to buffer the requests and decouple the S3 bucket from the Lambda function. This will ensure that the documents are not lost and can be processed at a later time if the Lambda function is not available. This will ensure that the documents are not lost and can be processed at a later time if the Lambda function is not available. By using Amazon SQS, the architecture is decoupled and the Lambda function can process the documents in a scalable and fault-tolerant manner

This combination of actions will provide high availability and minimum latency for global users by using AWS Global Accelerator and Application Load Balancers. AWS Global Accelerator is a networking service that helps you improve the availability, performance, and security of your internet-facing applications by using the AWS global network. It provides two global static public IPs that act as a fixed entry point to your application endpoints, such as Application Load Balancers, in multiple Regions1. Global Accelerator uses the AWS backbone network to route traffic to the optimal regional endpoint based on health, client location, and policies that you configure. It also offers TCP and UDP support, traffic encryption, and DDoS protection2. Application Load Balancers are external load balancers that distribute incoming application traffic across multiple targets, such as EC2 instances, in multiple Availability Zones. They support both HTTP and HTTPS (SSL/TLS) protocols, and offer advanced features such as content-based routing, health checks, and integration with other AWS services3. By creating external Application Load Balancers in front of the application in each Region, you can ensure that the application can handle varying load patterns and scale on demand. By creating an AWS Global Accelerator accelerator to route traffic to the load balancers in each Region, you can leverage the performance, security, and availability of the AWS global network to deliver the best possible user experience.

References: 1: What is AWS Global Accelerator? - AWS Global Accelerator4, Overview section2: Network Acceleration Service - AWS Global Accelerator - AWS5, Why AWS Global Accelerator? section. 3: What is an Application Load Balancer? - Elastic Load Balancing6, Overview section.

These are some of the main use cases for AWS DataSync: • Data migration – Move active datasets rapidly over the network into Amazon S3, Amazon EFS, or FSx for Windows File Server. DataSync includes automatic encryption and data integrity validation to help make sure that your data arrives securely, intact, and ready to use.

"DataSync includes encryption and integrity validation to help make sure your data arrives securely, intact, and ready to use." https://aws.amazon.com/datasync/faqs/

To store and access files that are 25 GB or larger across many EC2 instances and across multiple Availability Zones, Amazon Elastic File System (Amazon EFS) is a suitable solution. Amazon EFS provides a simple, scalable, elastic file system that can be mounted on multiple EC2 instances concurrently. Amazon EFS supports high availability and durability by storing data across multiple Availability Zones within a Region.

References:

What Is Amazon Elastic File System?

Using EFS with EC2

Amazon Cognito identity pools assign your authenticated users a set of temporary, limited-privilege credentials to access your AWS resources. The permissions for each user are controlled through IAM roles that you create. https://docs.aws.amazon.com/cognito/latest/developerguide/role-based- access-control.html

Migrating to Amazon MQ reduces the overhead on the queue management. C and D are dismissed. Deciding between A and B means deciding to go for an AutoScaling group for EC2 or an RDS for Postgress (both multi- AZ). The RDS option has less operational impact, as provide as a service the tools and software required. Consider for instance, the effort to add an additional node like a read replica, to the DB. https://docs.aws.amazon.com/amazon-mq/latest/developer-guide/active-standby-broker-deployment.html https://aws.amazon.com/rds/postgresql/

 Security groups are virtual firewalls that protect AWS instances and can be applied to EC2, ELB and RDS1. Security groups have rules for inbound and outbound traffic and are stateful, meaning that responses to allowed inbound traffic are allowed to flow out of the instance2. Network ACLs are different from security groups in several ways. They cover entire subnets, not individual instances, and are stateless, meaning that they require rules for both inbound and outbound traffic2. Network ACLs also support deny rules, while security groups only support allow rules2.

To meet the requirements of the scenario, the solutions architect should create two security groups: one for the DB instance and one for the web servers in the public subnet. The security group for the DB instance should allow traffic from the public subnet CIDR block on port 3306, which is the default port for MySQL3. This way, only the web servers in the public subnet can access the DB instance on that port. The security group for the web servers should allow traffic from 0 0 0 O’O on port 443, which is the default port for HTTPS4. This way, the web servers can accept secure connections from the internet on that port.

Using AWS WAF has several benefits. Additional protection against web attacks using criteria that you specify. You can define criteria using characteristics of web requests such as the following: Presence of SQL code that is likely to be malicious (known as SQL injection). Presence of a script that is likely to be malicious (known as cross-site scripting). AWS Firewall Manager simplifies your administration and maintenance tasks across multiple accounts and resources for a variety of protections. https://docs.aws.amazon.com/waf/latest/developerguide/what-is-aws-waf.html

Amazon Athena can be used to query JSON in S3

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/header-caching.html Configuring caching based on the language of the viewer: If you want CloudFront to cache different versions of your objects based on the language specified in the request, configure CloudFront to forward the Accept-Language header to your origin.

This option is the most secure because it follows the principle of least privilege and grants only the necessary permissions to the Lambda function without exposing any credentials in the code. The IAM role can be configured as the Lambda function’s execution role and the IAM policy can specify the S3 bucket ARN and the s3:GetObject action12. Option A is less secure because it grants read access to any principal that has access to the S3 bucket, which could be more than the Lambda function. Option C is less secure because it embeds credentials in the code, which could be compromised or exposed. Option D is less secure because it grants read access to all S3 buckets in the account, which could be more than what the Lambda function needs.

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

Amazon RDS for MySQL is a fully-managed relational database service that makes it easy to set up, operate, and scale MySQL deployments in the cloud. Amazon Aurora Serverless is an on-demand, auto-scaling configuration for Amazon Aurora (MySQL-compatible edition), where the database will automatically start up, shut down, and scale capacity up or down based on your application’s needs. It is a simple, cost-effective option for infrequent, intermittent, or unpredictable workloads.

https://aws.amazon.com/blogs/security/control-access-to-aws-resources-by-using-the-aws- organization-of-iam-principals/

The aws:PrincipalOrgID global key provides an alternative to listing all the account IDs for all AWS accounts in an organization. For example, the following Amazon S3 bucket policy allows members of any account in the XXX organization to add an object into the examtopics bucket.

{"Version": "2020-09-10",

"Statement": {

"Sid": "AllowPutObject",

"Effect": "Allow",

"Principal": "*",

"Action": "s3:PutObject",

"Resource": "arn:aws:s3:::examtopics/*",

"Condition": {"StringEquals":

{"aws:PrincipalOrgID":["XXX"]}}}}

https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_condition-keys.html

https://aws.amazon.com/ebs/features/ Amazon EBS provides a range of options that allow you to optimize storage performance and cost for your workload. These options are divided into two major categories: SSD-backed storage for transactional workloads, such as databases and boot volumes (performance depends primarily on IOPS), and HDD-backed storage for throughput intensive workloads, such as MapReduce and log processing (performance depends primarily on MB/s).

Creating a peering connection between the two VPCs and configuring an inbound rule for the ElastiCache cluster's security group to allow inbound connection from the application's security group is the most cost-effective solution. Peering connections are free and you only incur the cost of configuring the security group rules. The Transit VPC solution requires additional VPCs and associated resources, which would incur additional costs.

Before Testing | AWS Certification Information and Policies | AWS

https://aws.amazon.com/certification/policies/before-testing/

To minimize development changes while moving the application to AWS and to ensure a high level of availability, the company can rehost the application in AWS Elastic Beanstalk with the .NET platform in a Multi-AZ deployment. This will allow the application to run in a highly available environment without requiring any changes to the application code.

The company can also use AWS Database Migration Service (AWS DMS) to migrate the Oracle database to Oracle on Amazon RDS in a Multi-AZ deployment. This will allow the company to maintain the existing database platform while still achieving a high level of availability.

https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html

AWS Shield Advanced is designed to provide enhanced protection against DDoS attacks with proactive engagement and response capabilities, making it the best solution for this scenario.

AWS Shield Advanced: This service provides advanced protection against DDoS attacks. It includes detailed attack diagnostics, 24/7 access to the AWS DDoS Response Team (DRT), and financial protection against DDoS-related scaling charges. Shield Advanced also integrates with Route 53 and the Application Load Balancer (ALB) to ensure comprehensive protection for your web applications.

Route 53 and ALB Protection: By adding your Route 53 hosted zones and ALB resources to AWS Shield Advanced, you ensure that these components are covered under the enhanced protection plan. Shield Advanced actively monitors traffic and provides real-time attack mitigation, minimizing the impact of DDoS attacks on your application.

Why Not Other Options?:

Option A (AWS Config): AWS Config is a configuration management service and does not provide DDoS protection or detection capabilities.

Option B (AWS WAF): While AWS WAF can help mitigate some types of attacks, it does not provide the comprehensive DDoS protection and proactive engagement offered by Shield Advanced.

Option C (GuardDuty): GuardDuty is a threat detection service that identifies potentially malicious activity within your AWS environment, but it is not specifically designed to provide DDoS protection.

AWS References:

AWS Shield Advanced - Overview of AWS Shield Advanced and its DDoS protection capabilities.

Integrating AWS Shield Advanced with Route 53 and ALB - Detailed guidance on how to protect Route 53 and ALB with AWS Shield Advanced.

In Static Websites, Web pages are returned by the server which are prebuilt.

They use simple languages such as HTML, CSS, or JavaScript.

There is no processing of content on the server (according to the user) in Static Websites. Web pages are returned by the server with no change therefore, static Websites are fast.

There is no interaction with databases.

Also, they are less costly as the host does not need to support server-side processing with different languages.

============

In Dynamic Websites, Web pages are returned by the server which are processed during runtime means they are not prebuilt web pages but they are built during runtime according to the user’s demand.

These use server-side scripting languages such as PHP, Node.js, ASP.NET and many more supported by the server.

So, they are slower than static websites but updates and interaction with databases are possible.

company need to setup a cheaper connection (200 M) but B is incorrect because you can only order port speeds of 1, 10, or 100 Gbps for more flexibility you can go with hosted connection, You can order port speeds between 50 Mbps and 10 Gbps. https://docs.aws.amazon.com/whitepapers/latest/aws-vpc-connectivity-options/aws-direct-connect.html

"Create an Amazon SQS queue to hold the jobs that needs to be processed. Create an Amazon EC2 Auto Scaling group for the compute application. Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of items in the SQS queue"

In this case we need to find a durable and loosely coupled solution for storing jobs. Amazon SQS is ideal for this use case and can be configured to use dynamic scaling based on the number of jobs waiting in the queue.To configure this scaling you can use the backlog per instance metric with the target value being the acceptable backlog per instance to maintain. You can calculate these numbers as follows: Backlog per instance: To calculate your backlog per instance, start with the ApproximateNumberOfMessages queue attribute to determine the length of the SQS queue

https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_scps_exam ples_vpc.html#example_vpc_2

The allowed block size is between a /28 netmask and /16 netmask. The CIDR block must not overlap with any existing CIDR block that's associated with the VPC. https://docs.aws.amazon.com/vpc/latest/userguide/configure-your-vpc.html

https://docs.amazonaws.cn/en_us/IAM/latest/UserGuide/reference_policies_examples_s3_rw-bucket.html

The policy is separated into two parts because the ListBucket action requires permissions on the bucket while the other actions require permissions on the objects in the bucket. You must use two different Amazon Resource Names (ARNs) to specify bucket-level and object-level permissions. The first Resource element specifies arn:aws:s3:::AdminTools for the ListBucket action so that applications can list all objects in the AdminTools bucket.

Option A is the most appropriate solution for reducing replication lag without significant changes to the application code and minimizing ongoing operational overhead. Migrating the database to Amazon Aurora MySQL allows for improved replication performance and higher scalability compared to Amazon RDS for MySQL. Aurora Replicas provide faster replication, reducing the replication lag, and Aurora Auto Scaling ensures that there are enough Aurora Replicas to handle the incoming traffic. Additionally, Aurora MySQL native functions can replace the stored procedures, reducing the load on the database and improving performance.

This solution meets the requirements of saving money on storage while keeping the most accessed files readily available for the users. S3 Lifecycle policy can automatically move objects from one storage class to another based on predefined rules. S3 Standard-IA is a lower-cost storage class for data that is accessed less frequently, but requires rapid access when needed. It is suitable for ringtones older than 90 days that are downloaded infrequently.

Option A is incorrect because configuring S3 Standard-IA for the initial storage tier of the objects can incur higher costs for frequent access and retrieval fees. Option B is incorrect because moving the files to S3 Intelligent-Tiering can incur additional monitoring and automation fees that may not be necessary for ringtones older than 90 days. Option C is incorrect because using S3 inventory to manage objects and move them to S3 Standard-IA can be complex and time-consuming, and it does not provide automatic cost savings.

References:

https://aws.amazon.com/s3/storage-classes/

https://aws.amazon.com/s3/cloud-storage-cost-optimization-ebook/

1. lowest possible latency + node to node ==> cluster placement(must be within one AZ), so C, D out

2. For EBS Multi-Attach, up to 16 instances can be attached to a single volume==>we have 16 linux instance==>more close to A

3. "need a shared block device volume"==>EBS Multi-attach is Block Storage whereas EFS is File Storage==> B out

4. EFS automatically replicates data within and across 3 AZ==>we use cluster placement so all EC2 are within one AZ.

5. EBS Multi-attach volumes can be used for clients within a single AZ.

https://repost.aws/questions/QUK2RANw1QTKCwpDUwCCI72A/efs-vs-ebs-mult-attach

bottlenecks can be avoided with queues (SQS).

High availability can be enabled for this architecture quite simply by modifying the existing Auto Scaling group to use multiple availability zones. The ASG will automatically balance the load so you don't actually need to specify the instances per AZ.

AWS Shield Advanced provides expanded DDoS attack protection for your Amazon EC2 instances, Elastic Load Balancing load balancers, CloudFront distributions, Route 53 hosted zones, and AWS Global Accelerator standard accelerators. https://docs.aws.amazon.com/waf/latest/developerguide/what-is-aws-waf.html

You can use CloudFront to deliver video on demand (VOD) or live streaming video using any HTTP origin. One way you can set up video workflows in the cloud is by using CloudFront together with AWS Media Services. https://docs.aws.am azon.com/AmazonCloudFront/latest/DeveloperGuide/on-demand-streaming-video.html

https://docs.aws.amazon.com/whitepapers/latest/aws-vpc-connectivity-options/aws-direct-connect-aws-transit-gateway.html

We recommend that you use On-Demand Instances for applications with short-term, irregular workloads that cannot be interrupted. https://docs.aws.amazon.co m/AWSEC2/latest/UserGuide/ec2-on-demand-instances.html

https://computingforgeeks.com/stream-logs-in-aws-from-cloudwatch-to-elasticsearch/

This approach ensures that the order creation and payment processing steps are separate and atomic. By sending the order information to an SQS FIFO queue, the payment service can process the order one at a time and in the order they were received. If the payment service is unable to process an order, it can be retried later, preventing the creation of multiple orders. The deletion of the message from the queue after it is processed will prevent the same message from being processed multiple times.

https://docs.aws.amazon.com/lambda/latest/dg/configuration-vpc.html#vpc-managing-eni

Migrate the database to Amazon Aurora MySQL - this will let the DB scale on it's own; it'll scale automatically without needing adjustment. Create AMI of the web app and using a launch template - this will make the creating of any future instances of the app seamless. They can then be added to the auto scaling group which will save them money as it will scale up and down based on demand. Using a spot fleet to launch instances- This solves the "MOST cost-effective" portion of the question as spot instances come at a huge discount at the cost of being terminated at any time Amazon deems fit. I think this is why there's a bit of disagreement on this. While it's the most cost effective, it would be a terrible choice if amazon were to terminate that spot instance during a busy period.

Before you begin: Decide which two Availability Zones you will use for your EC2 instances. Configure your virtual private cloud (VPC) with at least one public subnet in each of these Availability Zones. These public subnets are used to configure the load balancer. You can launch your EC2 instances in other subnets of these Availability Zones instead.

Deploy the application servers by using Amazon EC2 instances in an Auto Scaling group across multiple Availability Zones. Use an Amazon RDS DB instance in a Multi-AZ configuration. To make an existing application highly available and resilient while avoiding any single points of failure and giving the application the ability to scale to meet user demand, the best solution would be to deploy the application servers using Amazon EC2 instances in an Auto Scaling group across multiple Availability Zones and use an Amazon RDS DB instance in a Multi-AZ configuration. By using an Amazon RDS DB instance in a Multi-AZ configuration, the database is automatically replicated across multiple Availability Zones, ensuring that the database is highly available and can withstand the failure of a single Availability Zone. This provides fault tolerance and avoids any single points of failure.

Composite alarms determine their states by monitoring the states of other alarms. You can **use composite alarms to reduce alarm noise**. For example, you can create a composite alarm where the underlying metric alarms go into ALARM when they meet specific conditions. You then can set up your composite alarm to go into ALARM and send you notifications when the underlying metric alarms go into ALARM by configuring the underlying metric alarms never to take actions. Currently, composite alarms can take the following actions: https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Create_Composite_Alarm.html

https://docs.aws.amazon.com/AmazonRDS/latest/UserGu ide/USER_RestoreFromSnapshot.html#USER_RestoreFromSnapshot.CON

Under "Encrypt unencrypted resources" - https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/EBSEncryptio n.html

EC2 instance Savings Plan saves 72% while Compute Savings Plans saves 66%. But according to link, it says "Compute Savings Plans provide the most flexibility and help to reduce your costs by up to 66%. These plans automatically apply to EC2 instance usage regardless of instance family, size, AZ, region, OS or tenancy, and also apply to Fargate and Lambda usage." EC2 instance Savings Plans are not applied to Fargate or Lambda

Amazon CloudFront is a content delivery network (CDN) that speeds up the delivery of static and dynamic web content, such as HTML pages, images, and videos. By using CloudFront, the HTML pages will be served to users from the edge location that is closest to them, resulting in faster delivery and a better user experience. CloudFront can also handle the high traffic and large number of requests expected for the global event, ensuring that the HTML pages are available and accessible to users around the world.

Use a group email address for the management account's root user https://docs.aws.amazon.com/organizations/latest/userguide/orgs_best-practices_mgmt-acct.html#best-practices_mgmt-acct_email-address

(https://aws.amazon.com/blogs/security/how-to-restrict-amazon-s3-bucket-access-to-a-specific-iam-role/ )

This solution meets the requirements of a serverless solution, encryption, replication, and SQL analysis with the least operational overhead. Amazon Athena is a serverless interactive query service that can analyze data in S3 using standard SQL. S3 Cross-Region Replication (CRR) can replicate encrypted objects to an S3 bucket in another Region automatically. Server-side encryption with AWS KMS multi-Region keys (SSE-KMS) can encrypt the data at rest using keys that are replicated across multiple Regions. Creating a new S3 bucket can avoid potential conflicts with existing data or configurations.

Option B is incorrect because Amazon RDS is not a serverless solution and it cannot query data in S3 directly. Option C is incorrect because server-side encryption with Amazon S3 managed encryption keys (SSE-S3) does not use KMS keys and it does not support multi-Region replication. Option D is incorrect because Amazon RDS is not a serverless solution and it cannot query data in S3 directly. It is also incorrect for the same reason as option C.

References:

https://docs.aws.amazon.com/AmazonS3/latest/userguide/replication-walkthrough-4.html

https://aws.amazon.com/blogs/storage/considering-four-different-replication-options-for-data-in-amazon-s3/

https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingEncryption.html

https://aws.amazon.com/athena/

https://aws.amazon.com/kms/faqs/ #:~:text=If%20you%20are%20a%20developer%20who%20needs%20to%20digitally,a%20broad%20set%20of%20industry%20and%20regional%20compliance%20regimes.

https://aws.amazon.com/p remiumsupport/knowledge-center/cloudwatch-memory-metrics-ec2/

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resour ce-ecs-taskdefinition.html

Many applications, including those built on modern serverless architectures, can have a large number of open connections to the database server and may open and close database connections at a high rate, exhausting database memory and compute resources. Amazon RDS Proxy allows applications to pool and share connections established with the database, improving database efficiency and application scalability. https://aws.amazon.com/id/rds/proxy/

https://docs.aws.amazon.com/AmazonRDS/late st/AuroraUserGuide/Aurora.Replication.html

#Aurora.Replication.Replicas Aurora Replicas have two main purposes. You can issue queries to them to scale the read operations for your application. You typically do so by connecting to the reader endpoint of the cluster. That way, Aurora can spread the load for read-only connections across as many Aurora Replicas as you have in the cluster. Aurora Replicas also help to increase availability. If the writer instance in a cluster becomes unavailable, Aurora automatically promotes one of the reader instances to take its place as the new writer.

https://docs.aws.amazon.com/Amazon RDS/latest/AuroraUserGuide/Aurora.Overview.html

Amazon S3 is cheapest and can be accessed from anywhere.

To meet the new requirement of transferring files over a private route, the EC2 instances should be moved to private subnets, which do not have direct access to the internet. This ensures that the traffic for file transfers does not go over the internet. To enable the EC2 instances to access Amazon S3, a VPC endpoint for Amazon S3 can be created. VPC endpoints allow resources within a VPC to communicate with resources in other services without the traffic being sent over the internet. By linking the VPC endpoint to the route table for the private subnets, the EC2 instances can access Amazon S3 over a private connection within the VPC.

AWS Fargate is a serverless experience for user applications, allowing the user to concentrate on building applications instead of configuring and managing servers. Fargate also automates resource management, allowing users to easily scale their applications in response to demand.

The details are revealed in below url: https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/FIFO-queues.html

FIFO (First-In-First-Out) queues are designed to enhance messaging between applications when the order of operations and events is critical, or where duplicates can't be tolerated. Examples of situations where you might use FIFO queues include the following: To make sure that user-entered commands are run in the right order. To display the correct product price by sending price modifications in the right order. To prevent a student from enrolling in a course before registering for an account.

https://aws.amazon.com/dynamodb/dax/

This solution meets the requirements of a two-tier application that has a variable demand based on the time of day and must be available at all times, while minimizing the overall cost. EC2 Reserved Instances can provide significant savings compared to On-Demand Instances for the baseline level of usage, and they can guarantee capacity reservation when needed. EC2 Spot Instances can provide up to 90% savings compared to On-Demand Instances for any additional capacity that the application needs during peak hours. Spot Instances are suitable for stateless applications that can tolerate interruptions and can be replaced by other instances. Stopping the RDS database when it is not in use can reduce the cost of running the database tier.

Option A is incorrect because using all EC2 Spot Instances can affect the availability of the application if there are not enough spare capacity or if the Spot price exceeds the maximum price. Stopping the RDS database when it is not in use can reduce the cost of running the database tier, but it can also affect the availability of the application. Option B is incorrect because purchasing EC2 Instance Savings Plans to cover five EC2 instances can lock in a fixed amount of compute usage per hour, which may not match the actual usage pattern of the application. Purchasing an RDS Reserved DB Instance can provide savings for the database tier, but it does not allow stopping the database when it is not in use. Option D is incorrect because purchasing EC2 Instance Savings Plans to cover two EC2 instances can lock in a fixed amount of compute usage per hour, which may not match the actual usage pattern of the application. Using up to three additional EC2 On-Demand Instances as needed can incur higher costs than using Spot Instances.

References:

https://aws.amazon.com/ec2/pricing/reserved-instances/

https://aws.amazon.com/ec2/spot/

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_StopInstance.html

Service control policies (SCPs) are one type of policy that you can use to manage your organization. SCPs offer central control over the maximum available permissions for all accounts in your organization, allowing you to ensure your accounts stay within your organization's access control guidelines. See https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_scp.html.

ElastiCache, enhances the performance of web applications by quickly retrieving information from fully-managed in-memory data stores. It utilizes Memcached and Redis, and manages to considerably reduce the time your applications would, otherwise, take to read data from disk-based databases. Amazon CloudFront supports dynamic content from HTTP and WebSocket protocols, which are based on the Transmission Control Protocol (TCP) protocol. Common use cases include dynamic API calls, web pages and web applications, as well as an application's static files such as audio and images. It also supports on-demand media streaming over HTTP. AWS Global Accelerator supports both User Datagram Protocol (UDP) and TCP-based protocols. It is commonly used for non-HTTP use cases, such as gaming, IoT and voice over IP. It is also good for HTTP use cases that need static IP addresses or fast regional failover

https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_aws-services-that-work-with-iam.html

https://aws.amazon.com/about-aws/whats-new/2017/10/aws-waf-now-supports-geographic-match/

AWS Database Migration Service supports homogeneous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle or Microsoft SQL Server to Amazon Aurora. With AWS Database Migration Service, you can also continuously replicate data with low latency from any supported source to any supported target. For example, you can replicate from multiple sources to Amazon Simple Storage Service (Amazon S3) to build a highly available and scalable data lake solution. You can also consolidate databases into a petabyte-scale data warehouse by streaming data to Amazon Redshift. Learn more about the supported source and target databases. https://aws.amazon.com/dms/

https://docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-target-tracking.html

To ensure that Amazon S3 buckets do not have unauthorized configuration changes, a solutions architect should turn on AWS Config with the appropriate rules. AWS Config is a service that allows users to audit and assess their AWS resource configurations for compliance with industry standards and internal policies. It provides a detailed view of the resources and their configurations, including information on how the resources are related to each other. By turning on AWS Config with the appropriate rules, users can identify and remediate unauthorized configuration changes to their Amazon S3 buckets.

https://docs.aws.amazon.com/ses/latest/dg/send-email-formatted.html

D. Create an Amazon EventBridge (Amazon CloudWatch Events) scheduled event that invokes an AWS Lambda function to query the application's API for the data. This step can be done using AWS Lambda to extract the shipping statistics and organize the data into an HTML format.

B. Use Amazon Simple Email Service (Amazon SES) to format the data and send the report by email. This step can be done by using Amazon SES to send the report to multiple email addresses at the same time every morning.

Therefore, options D and B are the correct choices for this question. Option A is incorrect because Kinesis Data Firehose is not necessary for this use case. Option C is incorrect because AWS Glue is not required to query the application's API. Option E is incorrect because S3 event notifications cannot be used to send the report by email.

This approach will allow the EC2 instance to access the internet and download the monthly security updates while still being located in a private subnet. By creating a NAT gateway and placing it in a public subnet, it will allow the instances in the private subnet to access the internet through the NAT gateway. And then, configure the private subnet route table to use the NAT gateway as the default route. This will ensure that all outbound traffic is directed through the NAT gateway, allowing the EC2 instance to access the internet while still maintaining the security of the private subnet.

This option is the most efficient because it uses Amazon SQS, which is a fully managed message queuing service that lets you send, store, and receive messages between software components at any volume, without losing messages or requiring other services to be available1. It also uses an SQS message queue to asynchronously dispatch requests to the different application tiers, which decouples the image upload process from the thumbnail generation process and enables scalability and reliability. It also alerts the user through an application message that the image was received, which provides a faster response time to the user than waiting for the thumbnail generation to complete. Option A is less efficient because it uses a custom AWS Lambda function to generate the thumbnail and alert the user, which is a way to run code without provisioning or managing servers. However, this does not use an asynchronous dispatch mechanism to separate the image upload process from the thumbnail generation process. It also uses the image upload process as an event source to invoke the Lambda function, which could cause concurrency issues if there are many images uploaded at once. Option B is less efficient because it uses AWS Step Functions, which is a fully managed service that provides a graphical console to arrange and visualize the components of your application as a series of steps2. However, this does not use an asynchronous dispatch mechanism to separate the image upload process from the thumbnail generation process. It also uses Step Functions to handle the orchestration between the application tiers and alert the user when thumbnail generation is complete, which could introduce additional complexity and latency. Option D is less efficient because it uses Amazon SNS, which is a fully managed messaging service that enables you to send messages or notifications directly to users with SMS text messages or email3. However, this does not use an asynchronous dispatch mechanism to separate the image upload process from the thumbnail generation process. It also uses SNS notification topics and subscriptions to generate the thumbnail after the image upload is complete and message the user’s mobile app by way of a push notification after thumbnail generation is complete, which could introduce additional complexity and latency.

The storage solution that will meet these requirements most cost-effectively is B: Create an S3 Lifecycle configuration to transition objects from S3 Standard to S3 Glacier Deep Archive after 1 month. Amazon S3 Glacier Deep Archive is a secure, durable, and extremely low-cost Amazon S3 storage class for long-term retention of data that is rarely accessed and for which retrieval times of several hours are acceptable. It is the lowest-cost storage option in Amazon S3, making it a cost-effective choice for storing backup files that are not accessed after 1 month. You can use an S3 Lifecycle configuration to automatically transition objects from S3 Standard to S3 Glacier Deep Archive after 1 month. This will minimize the storage costs for the backup files that are not accessed frequently.

Configure provisioned concurrency for the Lambda function that handles the requests. Provisioned concurrency allows you to set the amount of compute resources that are available to the Lambda function, so that it can handle more requests at once and reduce latency. Caching the results of the queries in Amazon S3 could also help to reduce latency, but it would not be as effective as setting up provisioned concurrency. Increasing the size of the database would not help to reduce latency, as this would not increase the number of connections the Lambda function could establish, and establishing a direct connection between the frontend application and the database would bypass the API, which would not be the best solution either.

Using AWS Lambda with Amazon API Gateway - AWS Lambda

https://docs.aws.amazon.com/lambda/latest/dg/services-apigateway.html

AWS Lambda FAQs

https://aws.amazon.com/lambda/faqs/

https://www.learnaws.org/2020/12/13/aws-rds-proxy-deep-dive/

RDS proxy can improve application availability in such a situation by waiting for the new database instance to be functional and maintaining any requests received from the application during this time. The end result is that the application is more resilient to issues with the underlying database.

This will enable solution to hold data till the time DB comes back to normal. RDS proxy is to optimally utilize the connection between Lambda and DB. Lambda can open multiple connection concurrently which can be taxing on DB compute resources, hence RDS proxy was introduced to manage and leverage these connections efficiently.

https://aws.amazon.com/fsx/lustre/

Amazon FSx has native support for Windows file system features and for the industry-standard Server Message Block (SMB) protocol to access file storage over a network. https://docs.aws.amazon.com/fsx/latest/WindowsGuide/what-is.html

This approach will provide both high availability and scalability for the website platform. By moving the database to Amazon Aurora with a read replica in another availability zone, it will provide a failover option for the database. The use of an Application Load Balancer and an Auto Scaling group across two availability zones allows for automatic scaling of the website to meet increased user demand. Additionally, creating an AMI from the original EC2 instance allows for easy replication of the instance in case of failure.

https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/field-level-encryption.html

"With Amazon CloudFront, you can enforce secure end-to-end connections to origin servers by using HTTPS. Field-level encryption adds an additional layer of security that lets you protect specific data throughout system processing so that only certain applications can see it."

"Replication from the primary DB cluster to all secondaries is handled by the Aurora storage layer rather than by the database engine, so lag time for replicating changes is minimal—typically, less than 1 second. Keeping the database engine out of the replication process means that the database engine is dedicated to processing workloads. It also means that you don't need to configure or manage the Aurora MySQL binlog (binary logging) replication."

https://aws.amazon.com/premiumsupport/knowledge-center/s3-private-connection-no-authentication/

https://aws.amazon.com/blogs/aws/amazon-aurora-fast-database-cloning/

A. Create an Amazon API Gateway REST API. Configure the method to use the Lambda function. Enable IAM authentication on the API. This option is the most operationally efficient as it allows you to use API Gateway to handle the HTTPS endpoint and also allows you to use IAM to authenticate the calls to the microservice. API Gateway also provides many additional features such as caching, throttling, and monitoring, which can be useful for a microservice.

This solution meets the requirements of a customer-facing application that has a clearly defined access pattern throughout the year and a variable number of reads and writes that depend on the time of year. Amazon DynamoDB is a fully managed NoSQL database service that can handle any level of request traffic and data size. DynamoDB auto scaling can automatically adjust the provisioned read and write capacity based on the actual workload. DynamoDB on-demand backups can create full backups of the tables for data protection and archival purposes. DynamoDB Streams can capture a time-ordered sequence of item-level modifications in the tables for audit purposes.

Option B is incorrect because Amazon Redshift is a data warehouse service that is designed for analytical workloads, not for customer-facing applications. Option C is incorrect because Amazon RDS with Provisioned IOPS can provide consistent performance for relational databases, but it may not be able to handle unpredictable spikes in traffic and data size. Option D is incorrect because Amazon Aurora MySQL with auto scaling can provide high performance and availability for relational databases, but it does not support audit logging as a parameter.

References:

https://aws.amazon.com/dynamodb/

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/AutoScaling.html

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/BackupRestore.html

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Streams.html

By purchasing a Compute Savings Plan, the company can save on the costs of running both EC2 instances and Lambda functions. The Lambda functions can be connected to the private subnet that contains the EC2 instances through a VPC endpoint for AWS services or a VPC peering connection. This provides direct network access to the EC2 instances while keeping the traffic within the private network, which helps to minimize network latency. Optimizing the Lambda functions’ duration, memory usage, number of invocations, and amount of data transferred can help to further minimize costs and improve performance. Additionally, using a private subnet helps to ensure that the EC2 instances are not directly accessible from the public internet, which is a security best practice.

https://aws.amazon.com/global-accelerator/faqs/

HTTP /HTTPS - ALB ; TCP and UDP - NLB; Lowest latency routing and more throughput. Also supports failover, uses Anycast Ip addressing - Global Accelerator Caching at Egde Locations – Cloutfront

WS Global Accelerator automatically checks the health of your applications and routes user traffic only to healthy application endpoints. If the health status changes or you make configuration updates, AWS Global Accelerator reacts instantaneously to route your users to the next available endpoint..

SSE-S3 - is free and uses AWS owned CMKs (CMK = Customer Master Key). The encryption key is owned and managed by AWS, and is shared among many accounts. Its rotation is automatic with time that varies as shown in the table here. The time is not explicitly defined.

SSE-KMS - has two flavors:

AWS managed CMK. This is free CMK generated only for your account. You can only view it policies and audit usage, but not manage it. Rotation is automatic - once per 1095 days (3 years),

Customer managed CMK. This uses your own key that you create and can manage. Rotation is not enabled by default. But if you enable it, it will be automatically rotated every 1 year. This variant can also use an imported key material by you. If you create such key with an imported material, there is no automated rotation. Only manual rotation.

SSE-C - customer provided key. The encryption key is fully managed by you outside of AWS. AWS will not rotate it.

This solution meets the requirements of moving data to an Amazon S3 bucket, encrypting the data when it is stored in the S3 bucket, and automatically rotating the encryption key every year with the least operational overhead. AWS Key Management Service (AWS KMS) is a service that enables you to create and manage encryption keys for your data. A customer managed key is a symmetric encryption key that you create and manage in AWS KMS. You can enable automatic key rotation for a customer managed key, which means that AWS KMS generates new cryptographic material for the key every year. You can set the S3 bucket’s default encryption behavior to use the customer managed KMS key, which means that any object that is uploaded to the bucket without specifying an encryption method will be encrypted with that key.

Option A is incorrect because using server-side encryption with Amazon S3 managed encryption keys (SSE-S3) does not allow you to control or manage the encryption keys. SSE-S3 uses a unique key for each object, and encrypts that key with a master key that is regularly rotated by S3. However, you cannot enable or disable key rotation for SSE-S3 keys, or specify the rotation interval. Option C is incorrect because manually rotating the KMS key every year can increase the operational overhead and complexity, and it may not meet the requirement of rotating the key every year if you forget or delay the rotation process. Option D is incorrect because encrypting the data with customer key material before moving the data to the S3 bucket can increase the operational overhead and complexity, and it may not provide consistent encryption for all objects in the bucket. Creating a KMS key without key material and importing the customer key material into the KMS key can enable you to use your own source of random bits to generate your KMS keys, but it does not support automatic key rotation.

References:

https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html

https://docs.aws.amazon.com/kms/latest/developerguide/rotate-keys.html

https://docs.aws.amazon.com/AmazonS3/latest/userguide/bucket-encryption.html

AWS Config is a fully managed service that allows the company to assess, audit, and evaluate the configurations of its AWS resources. It provides a detailed inventory of the resources in use and tracks changes to resource configurations. AWS Config can detect configuration changes and alert the company when changes occur. It also provides a historical view of changes, which is essential for compliance and governance purposes. AWS CloudTrail is a fully managed service that provides a detailed history of API calls made to the company's AWS resources. It records all API activity in the AWS account, including who made the API call, when the call was made, and what resources were affected by the call. This information is critical for security and auditing purposes, as it allows the company to investigate any suspicious activity that might occur on its AWS resources.

S3 Intelligent-Tiering - Perfect use case when you don't know the frequency of access or irregular patterns of usage.

Amazon S3 offers a range of storage classes designed for different use cases. These include S3 Standard for general-purpose storage of frequently accessed data; S3 Intelligent-Tiering for data with unknown or changing access patterns; S3 Standard-Infrequent Access (S3 Standard-IA) and S3 One Zone-Infrequent Access (S3 One Zone-IA) for long-lived, but less frequently accessed data; and Amazon S3 Glacier (S3 Glacier) and Amazon S3 Glacier Deep Archive (S3 Glacier Deep Archive) for long-term archive and digital preservation. If you have data residency requirements that can’t be met by an existing AWS Region, you can use the S3 Outposts storage class to store your S3 data on-premises. Amazon S3 also offers capabilities to manage your data throughout its lifecycle. Once an S3 Lifecycle policy is set, your data will automatically transfer to a different storage class without any changes to your application.

https://aws.amazon.com/getting-started/hands-on/getting-sta rted-using-amazon-s3-intelligent-tiering/?nc1=h_ls

You might want to use Transfer Acceleration on a bucket for various reasons, including the following:

You have customers that upload to a centralized bucket from all over the world.

You transfer gigabytes to terabytes of data on a regular basis across continents.

You are unable to utilize all of your available bandwidth over the Internet when uploading to Amazon S3.

https://docs.aws.amazon.com/AmazonS3/latest/dev/transfer-acceleration.html

https://aws.amazon.com/s3/transfer- acceleration/#:~:text=S3%20Transfer%20Acceleration%20(S3TA)%20reduces,to%20S3%20for%20remote%20applications:

"Amazon S3 Transfer Acceleration can speed up content transfers to and from Amazon S3 by as much as 50-500% for long-distance transfer of larger objects. Customers who have either web or mobile applications with widespread users or applications hosted far away from their S3 bucket can experience long and variable upload and download speeds over the Internet"

https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuoverview.html

"Improved throughput - You can upload parts in parallel to improve throughput."

EC2 Spot Instances allow users to bid on spare Amazon EC2 computing capacity and can be a cost-effective solution for stateless, interruptible workloads that can be started and stopped at any time. Since the batch processing job is stateless, can be started and stopped at any time, and typically takes upwards of 60 minutes to complete, EC2 Spot Instances would be a good fit for this workload.

https://aws.amazon.com/es/blogs/big-data/real-time-analytics-with-amazon-redshift-streaming-ingestion/

This answer is correct because it provides Regional failover capabilities for the online gaming application by using AWS Global Accelerator. AWS Global Accelerator is a networking service that helps you improve the availability, performance, and security of your public applications. Global Accelerator provides two global static public IPs that act as a fixed entry point to your application endpoints, such as NLBs, in different AWS Regions. Global Accelerator uses the AWS global network to route traffic to the optimal regional endpoint based on health, client location, and policies that you configure. Global Accelerator also terminates TCP and UDP traffic at the edge locations, which reduces the number of hops and improves the network performance. By adding AWS Global Accelerator in front of the NLBs, you can achieve Regional failover for your online gaming application.

References:

https://docs.aws.amazon.com/global-accelerator/latest/dg/what-is-global-accelerator.html

https://aws.amazon.com/global-accelerator/

S3 Storage Lens is a fully managed S3 storage analytics solution that provides a comprehensive view of object storage usage, activity trends, and recommendations to optimize costs. Storage Lens allows you to analyze object access patterns across all of your S3 buckets and generate detailed metrics and reports.

as the policy prevents anyone from doing any EC2 action on any region except us-east-1 and allows only users with source ip 10.100.100.0/24 to terminate instances. So user with source ip 10.100.100.254 can terminate instances in us-east-1 region.

https://aws.amazon.com/premiumsupport/knowledge-center/elb-redirect-http-to-https-using-alb/

How can I redirect HTTP requests to HTTPS using an Application Load Balancer? Last updated: 2020-10-30 I want to redirect HTTP requests to HTTPS using Application Load Balancer listener rules. How can I do this? Resolution Reference: https://aws.amazon.com/premiumsupport/knowledge-center/elb-redirect-http-to-https-using-alb/

https://aws.amazon.com/about-aws/whats-new/2018/03/introducing-amazon-vpc-nat-gateway-in-the-aws-govcloud-us-region/#:~:text=NAT%20Gateway%20is%20a%20highly,instances%20in %20a%20private%20subnet.

https://docs.aws.amazon.com/vpc/latest/userguide/vpc-nat-comparison.html

To maximize resiliency and scalability, the best solution is to use an Amazon SQS queue as a destination for the jobs. This decouples the primary server from the compute nodes, allowing them to scale independently. This also helps to prevent job loss in the event of a failure. Using an Auto Scaling group of Amazon EC2 instances for the compute nodes allows for automatic scaling based on the workload. In this case, it's recommended to configure the Auto Scaling group based on the size of the Amazon SQS queue, which is a better indicator of the actual workload than the load on the primary server or compute nodes. This approach ensures that the application can handle variable workloads, while also minimizing costs by automatically scaling up or down the compute nodes as needed.

https://aws.amazon.com/s3/storage-classes/?trk=66264cd8-3b73-416c-9693-ea7cf4fe846a &sc_channel=ps&s_kwcid=AL!4422!3!536452716950!p!!g!!aws%20s3%20pricing&ef_id=Cj0KCQjwnbmaBhD-ARIsAGTPcfVHUZN5_BMrzl5zBcaC8KnqpnNZvjbZzqPkH6k7q4JcYO5KFLx0YYgaAm6nEALw_wcB:G:s&s_kwcid=AL!4422!3!536452716950!p!!g!!aws%20s3%20pricing

 AWS Snowball Edge is a type of Snowball device with on-board storage and compute power for select AWS capabilities. Snowball Edge can do local processing and edge-computing workloads in addition to transferring data between your local environment and the AWS Cloud1. Users can order an AWS Snowball Edge Storage Optimized device that includes Amazon EC2 compute to move 50 TB of data from on premises to AWS. The Storage Optimized device has 80 TB of usable storage and 40 vCPUs of compute power2. Users can copy the data to the device using the AWS OpsHub graphical user interface or the Snowball client command line tool3. Users can also create and run Amazon EC2 instances on the device using Amazon Machine Images (AMIs) that are compatible with the sbe1 instance type. Users can use the Snowball Edge device to transfer the data and run the transformation job locally without using any network bandwidth.

Users can also create a new EC2 instance on AWS to run the transformation application after the data transfer is complete. Amazon EC2 is a web service that provides secure, resizable compute capacity in the cloud. Users can launch an EC2 instance in the same AWS Region where they send their Snowball Edge device and choose an AMI that matches their application requirements. Users can use the EC2 instance to continue running the transformation job in the AWS Cloud.

Amazon CloudFront is a content delivery network (CDN) that caches content at edge locations around the world, providing low latency and high transfer speeds to users accessing the content. Adding a CloudFront distribution in front of the S3 bucket will cache the static website's content at edge locations around the world, decreasing latency for users accessing the website. This solution is also cost-effective as it only charges for the data transfer and requests made by users accessing the content from the CloudFront edge locations. Additionally, this solution provides scalability and reliability benefits as CloudFront can automatically scale to handle increased demand and provide high availability for the website.

https://www.amazonaws.cn/en/ce rtificate-manager/faqs/#Managed_renewal_and_deployment

https://aws.amazon.com/premiumsupport/knowledge-center/acm-certificate-expiration/

https://aws.amazon.com/premiumsupport/knowledge-center/multivalue-versus-simple-policies/

Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between Software-as-a-Service (SaaS) applications like Salesforce, SAP, Zendesk, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift, in just a few clicks. https://aws.amazon.com/appflow/

Spot Instances are EC2 instances that are available at up to a 90% discount compared to On-Demand prices. Spot Instances are suitable for stateless, fault-tolerant, and flexible workloads that can tolerate interruptions. Spot Instances can be reclaimed by EC2 when the demand for On-Demand capacity increases, but they provide a two-minute warning before termination. EKS managed node groups automate the provisioning and lifecycle management of nodes for EKS clusters. Managed node groups can use Spot Instances to reduce costs and scale the cluster based on demand. Managed node groups also support features such as Capacity Rebalancing and Capacity Optimized allocation strategy to improve the availability and resilience of Spot Instances. This solution will meet the requirements most cost-effectively, as it leverages the lowest-priced EC2 capacity and does not require any manual intervention.

References:

1 explains how to create and use managed node groups with EKS.

2 describes how to use Spot Instances with managed node groups.

3 provides an overview of Spot Instances and their benefits.

https://docs.aws.a mazon.com/kms/latest/developerguide/rotate-keys.html

When you enable automatic key rotation for a customer managed key, AWS KMS generates new cryptographic material for the KMS key every year. AWS KMS also saves the KMS key's older cryptographic material in perpetuity so it can be used to decrypt data that the KMS key encrypted.

Key rotation in AWS KMS is a cryptographic best practice that is designed to be transparent and easy to use. AWS KMS supports optional automatic key rotation only for customer managed CMKs. Enable and disable key rotation. Automatic key rotation is disabled by default on customer managed CMKs. When you enable (or re-enable) key rotation, AWS KMS automatically rotates the CMK 365 days after the enable date and every 365 days thereafter.

https://aws.amazon.com/solutions/implementations/aws-streaming-data-solution-for-amazon-kinesis/

A function URL is a unique identifier for a Lambda function that can be used to invoke the function over HTTPS. It is composed of the API endpoint of the AWS Region where the function is deployed, and the name or ARN of the function1. By creating a function URL for the Lambda function, the solution can make the Lambda function available for the third party to call with the most operational efficiency.

B. Deploy an Application Load Balancer (ALB) in front of the Lambda function. Provide the ALB URL to the third party for the webhook. This solution will not meet the requirement of the most operational efficiency, as it involves creating and managing an additional resource (ALB) that is not necessary for invoking a Lambda function over HTTPS2.

C. Create an Amazon Simple Notification Service (Amazon SNS) topic. Attach the topic to the Lambda function. Provide the public hostname of the SNS topic to the third party for the webhook. This solution will not work, as Amazon SNS topics do not have public hostnames that can be used as webhooks. SNS topics are used to publish messages to subscribers, not to receive messages from external sources3.

D. Create an Amazon Simple Queue Service (Amazon SQS) queue. Attach the queue to the Lamb-da function. Provide the public hostname of the SQS queue to the third party for the webhook. This solution will not work, as Amazon SQS queues do not have public hostnames that can be used as webhooks. SQS queues are used to send, store, and receive messages between AWS services, not to receive messages from external sources.

Reference URL: https://docs.aws.amazon.com/lambda/latest/dg/lambda-api-permissions-ref.html

Amazon CloudFront is a content delivery network (CDN) that can improve the performance and reduce the cost of serving static content from a website. CloudFront can cache static files at edge locations closer to the users, reducing the latency and data transfer costs. CloudFront can also integrate with Amazon S3 as the origin for the static content, eliminating the need for EC2 instances to host the website. CloudFront meets all the requirements of the question, while the other options do not. References:

https://aws.amazon.com/blogs/architecture/architecting-a-low-cost-web-content-publishing-system/

https://nodeployfriday.com/posts/static-website-hosting/

https://aws.amazon.com/cloudfront/

AWS Network Firewall supports both inspection and filtering as required

https://aws.amazon.com/eb s/features/

"Provisioned IOPS volumes are backed by solid-state drives (SSDs) and are the highest performance EBS volumes designed for your critical, I/O intensive database applications.

These volumes are ideal for both IOPS-intensive and throughput-intensive workloads that require extremely low latency."

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html

https://aws.amazon.com/getting-started/hands-on/filter-messages-published-to-topics/

https://aws.amazon.com/vpc/faqs/#:~:text=Can%20a%20subnet% 20span%20Availability,within%20a%20single%20Availability%20Zone.

AWS Secrets Manager helps you protect secrets needed to access your applications, services, and IT resources. The service enables you to easily rotate, manage, and retrieve database credentials, API keys, and other secrets throughout their lifecycle.

https://docs.aws.amazon.com/secretsmanager/latest/userguide/intro.html

Secrets Manager enables you to replace hardcoded credentials in your code, including passwords, with an API call to Secrets Manager to retrieve the secret programmatically. This helps ensure the secret can't be compromised by someone examining your code, because the secret no longer exists in the code. Also, you can configure Secrets Manager to automatically rotate the secret for you according to a specified schedule. This enables you to replace long-term secrets with short-term ones, significantly reducing the risk of compromise.

Amazon S3 sends event notifications about S3 buckets (for example, object created, object removed, or object restored) to an SNS topic in the same Region.

The SNS topic publishes the event to an SQS queue in the central Region.

The SQS queue is configured as the event source for your Lambda function and buffers the event messages for the Lambda function.

The Lambda function polls the SQS queue for messages and processes the Amazon S3 event notifications according to your application’s requirements.

https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/subscribe-a- lambda-function-to-event-notifications-from-s3-buckets-in-different-aws-regions.html

This option is the most efficient because it deploys the web tier and the application tier to a second Region, which provides high availability and redundancy for the application. It also uses an Amazon Aurora global database, which is a feature that allows a single Aurora database to span multiple AWS Regions1. It also deploys the database in the primary Region and the second Region, which provides low latency global reads and fast recovery from a Regional outage. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which provides data protection by routing traffic to healthy endpoints in different Regions2. It also promotes the secondary to primary as needed, which provides data consistency by allowing write operations in one of the Regions at a time3. This solution meets the requirement of expanding globally and ensuring that its application has minimal downtime. Option A is less efficient because it extends the Auto Scaling groups for the web tier and the application tier to deploy instances in Availability Zones in a second Region, which could incur higher costs and complexity than deploying them separately. It also uses an Aurora global database to deploy the database in the primary Region and the second Region, which is correct. However, it does not use Amazon Route 53 health checks with a failover routing policy to the second Region, which could result in traffic being routed to unhealthy endpoints. Option B is less efficient because it deploys the web tier and the application tier to a second Region, which is correct. It also adds an Aurora PostgreSQL cross-Region Aurora Replica in the second Region, which provides read scalability across Regions. However, it does not use an Aurora global database, which provides faster replication and recovery than cross-Region replicas. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which is correct. However, it does not promote the secondary to primary as needed, which could result in data inconsistency or loss. Option C is less efficient because it deploys the web tier and the application tier to a second Region, which is correct. It also creates an Aurora PostgreSQL database in the second Region, which provides data redundancy across Regions. However, it does not use an Aurora global database or cross-Region replicas, which provide faster replication and recovery than creating separate databases. It also uses AWS Database Migration Service (AWS DMS) to replicate the primary database to the second Region, which provides data migration between different sources and targets. However, it does not use an Aurora global database or cross-Region replicas, which provide faster replication and recovery than using AWS DMS. It also uses Amazon Route 53 health checks with a failover routing policy to the second Region, which is correct.

https://aws.amazon.com/ step-functions/#:~:text=AWS%20Step%20Functions%20is%20a,machine%20learning%20(ML)%20pipelines.

"A common use case for AWS Step Functions is a task that requires human intervention (for example, an approval process). Step Functions makes it easy to coordinate the components of distributed applications as a series of steps in a visual workflow called a state machine. You can quickly build and run state machines to execute the steps of your application in a reliable and scalable fashion. (https://aws.amazon.com/pt/blogs/compute/implementing-serverless-manual-approval-steps-in-aws-step-functions-and-amazon-api-gate way/)"

https://aws.amazon.com/premiumsuppor t/knowledge-center/public-load-balancer-private-ec2/

Amazon Transcribe now supports speaker labeling for streaming transcription. Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for you to convert speech-to-text. In live audio transcription, each stream of audio may contain multiple speakers. Now you can conveniently turn on the ability to label speakers, thus helping to identify who is saying what in the output transcript. https://aws.amazon.com/about- aws/whats-new/2020/08/amazon-transcribe-supports-speaker-labeling-streaming-transcription/

EBS encryption by default is a feature that enables encryption for all new EBS volumes and snapshots created in a Region1. EBS encryption by default uses a service managed key or a customer managed key that is stored in AWS KMS1. EBS encryption by default is suitable for scenarios where data at rest must be encrypted by using a customer managed key, such as the digital media streaming application in the scenario1.

To meet the requirements of the scenario, the solutions architect should enable EBS encryption by default in the AWS Region where the EKS cluster will be created. The solutions architect should select the customer managed key as the default key for encryption1. This way, all new EBS volumes and snapshots created in that Region will be encrypted by using the customer managed key.

EKS encryption provider support is a feature that enables envelope encryption of Kubernetes secrets in EKS with a customer managed key that is stored in AWS KMS2. Envelope encryption means that data is encrypted by data encryption keys (DEKs) using AES-GCM; DEKs are encrypted by key encryption keys (KEKs) according to configuration in AWS KMS3. EKS encryption provider support is suitable for scenarios where secrets must be encrypted by using a customer managed key, such as the digital media streaming application in the scenario2.

To meet the requirements of the scenario, the solutions architect should create the EKS cluster and create an IAM role that has a policy that grants permission to the customer managed key. The solutions architect should associate the role with the EKS cluster2. This way, the EKS cluster can use envelope encryption of Kubernetes secrets with the customer managed key.

AWS Step Functions is a fully managed service that makes it easy to build applications by coordinating the components of distributed applications and microservices using visual workflows. With Step Functions, you can combine multiple AWS Lambda functions into responsive serverless applications and orchestrate data and services that run on Amazon EC2 instances, containers, or on-premises servers. Step Functions also allows for manual approvals as part of the workflow. This solution meets all the requirements with the least operational overhead.

https://aws. amazon.com/step-functions/#:~:text=AWS%20Step%20Functions%20is%20a,machine%20learning%20(ML)%20pipelines.

This option is the most efficient because it uses AWS DataSync, which is a secure, online service that automates and accelerates moving data between on-premises and AWS Storage services1. It also uses DataSync to transfer large amounts of data back and forth between NFS file systems in the two Regions on a periodic basis, which simplifies and speeds up the data transfer process with minimal operational overhead. This solution meets the requirement of transferring large amounts of data back and forth between NFS file systems in the two Regions on a periodic basis with the least operational overhead. Option B is less efficient because it uses AWS Snowball devices, which are physical devices that let you transfer large amounts of data into and out of AWS2. However, this does not provide a periodic data transfer solution, as it requires manual handling and shipping of the devices. Option C is less efficient because it sets up an SFTP server on Amazon EC2, which is a way to provide secure file transfer protocol (SFTP) access to files stored in Amazon S33. However, this does not provide a periodic data transfer solution, as it requires manual initiation and monitoring of the file transfers. Option D is less efficient because it uses AWS Database Migration Service (AWS DMS), which is a service that helps you migrate databases to AWS quickly and securely. However, this does not provide a data transfer solution for NFS file systems, as it only supports relational databases and non-relational data stores.

This option is the most efficient because it uses API usage plans and API keys, which are features of Amazon API Gateway that allow you to control who can access your API and how much and how fast they can access it1. It also implements API usage plans and API keys to limit the access of users who do not have a subscription, which enables you to create different tiers of access for your API and charge users accordingly. This solution meets the requirement of updating the application so that only users who have a subscription can access premium content. Option A is less efficient because it uses API caching and throttling on the API Gateway API, which are features of Amazon API Gateway that allow you to improve the performance and availability of your API and protect your backend systems from traffic spikes2. However, this does not provide a way to limit the access of users who do not have a subscription. Option B is less efficient because it uses AWS WAF on the API Gateway API, which is a web application firewall service that helps protect your web applications or APIs against common web exploits that may affect availability, compromise security, or consume excessive resources3. However, this does not provide a way to limit the access of users who do not have a subscription. Option C is less efficient because it uses fine-grained IAM permissions to the premium content in the DynamoDB table, which are permissions that allow you to control access to specific items or attributes within a table4. However, this does not provide a way to limit the access of users who do not have a subscription at the API level.

This solution will allow the company to host all three tiers on Amazon EC2 instances while using Amazon FSx for Windows File Server to provide Windows-based file sharing between the tiers. This will allow the company to use specific features of SQL Server, such as native backups and Data Quality Services, while sharing files for processing between the tiers.

https://docs.aws.amazon.com/efs/latest/ug/how-it-works.html#how-it-works-ec2

Share the existing KMS key with the MSP external account because it has already been used to encrypt the AMI snapshot. https://docs.aws.amazon.com/kms/latest/developerguide/key-policy-modifying-external-accounts.html

VPC endpoint allows you to connect to AWS services using a private network instead of using the public Internet

The correct answer is Option D. Deploy an S3 VPC gateway endpoint into the VPC and attach an endpoint policy that allows access to the S3 buckets. By deploying an S3 VPC gateway endpoint, the application can access the S3 buckets over a private network connection within the VPC, eliminating the need for data transfer over the internet. This can help reduce data transfer fees as well as improve the performance of the application. The endpoint policy can be used to specify which S3 buckets the application has access to.

This answer is correct because it meets the requirements of migrating a 20 TB MySQL database within 2 weeks with minimal downtime and cost-effectively. The AWS Snowball Edge Storage Optimized device has up to 80 TB of usable storage space, which is enough to fit the database. The AWS Database Migration Service (AWS DMS) can migrate data from MySQL to Amazon Aurora, Amazon RDS for MySQL, or MySQL on Amazon EC2 with minimal downtime by continuously replicating changes from the source to the target. The AWS Schema Conversion Tool (AWS SCT) can convert the source schema and code to a format compatible with the target database. By using these services together, the company can migrate the database to AWS with minimal downtime and cost. The Snowball Edge device can be shipped back to AWS to finish the migration and continue the ongoing replication until the database is fully migrated.

References:

https://docs.aws.amazon.com/snowball/latest/developer-guide/device-differences.html

https://docs.aws.amazon.com/dms/latest/userguide/CHAP_Source.MySQL.html

https://docs.aws.amazon.com/SchemaConversionTool/latest/userguide/CHAP_Source.MySQL.htm

This answer is correct because it meets the requirements of scaling to meet future application capacity demands and ensuring high availability across all three Availability Zones. By migrating the MySQL database to Amazon RDS for MySQL with a Multi-AZ DB cluster deployment, the company can benefit from automatic failover, backup, and patching of the database across multiple Availability Zones. By using Amazon ElastiCache for Redis with high availability, the company can store session data and cache reads in a fast, in-memory data store that can also fail over across Availability Zones. By migrating the web server to an Auto Scaling group that is in three Availability Zones, the company can automatically scale the web server capacity based on the demand and traffic patterns.

References:

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.MultiAZ.html

https://docs.aws.amazon.com/AmazonElastiCache/latest/red-ug/AutoFailover.html

https://docs.aws.amazon.com/autoscaling/ec2/userguide/what-is-amazon-ec2-auto-scaling.html

To clone the production data into the test environment with high I/O performance and without affecting the production environment, the best option is to take EBS snapshots of the production EBS volumes and restore them onto new EBS volumes in the test environment. Then, attach the new EBS volumes to EC2 instances in the test environment. This option minimizes the time required to clone the data and ensures that modifications to the cloned data do not affect the production environment. Therefore, option C is the correct answer.

The basic difference between Snowball and Snowball Edge is the capacity they provide. Snowball provides a total of 50 TB or 80 TB, out of which 42 TB or 72 TB is available, while Amazon Snowball Edge provides 100 TB, out of which 83 TB is available.

https://www.quora.com/How-can-I-use-DynamoDB-for-storing-metadata-for-Amazon-S3- objects

This solution meets the requirements of scalability, performance, and availability. AWS Lambda can process the photos in parallel and scale up or down automatically depending on the demand. Amazon S3 can store the photos and metadata reliably and durably, and provide high availability and low latency. DynamoDB can store the metadata efficiently and provide consistent performance. This solution also reduces the cost and complexity of managing EC2 instances and EBS volumes.

Option A is incorrect because storing the photos in DynamoDB is not a good practice, as it can increase the storage cost and limit the throughput. Option B is incorrect because Kinesis Data Firehose is not designed for processing photos, but for streaming data to destinations such as S3 or Redshift. Option D is incorrect because increasing the number of EC2 instances and using Provisioned IOPS SSD volumes does not guarantee scalability, as it depends on the load balancer and the application code. It also increases the cost and complexity of managing the infrastructure.

References:

https://aws.amazon.com/certification/certified-solutions-architect-professional/

https://www.examtopics.com/discussions/amazon/view/7193-exam-aws-certified-solutions-architect-professional-topic-1/

https://aws.amazon.com/architecture/

it allows the company to encrypt the Kubernetes secrets object in the EKS cluster with the least operational overhead. By enabling secrets encryption in the EKS cluster, the company can use AWS Key Management Service (AWS KMS) to generate and manage encryption keys for encrypting and decrypting secrets at rest. This is a simple and secure way to protect sensitive information in EKS clusters. References:

Encrypting Kubernetes secrets with AWS KMS

Kubernetes Secrets

EFS is a standard file system, it scales automatically and is highly available.

AWS Elastic Beanstalk provides an easy and quick way to deploy, manage, and scale applications. It supports a variety of platforms, including Java and Apache Tomcat. By using Elastic Beanstalk, the solutions architect can upload the Java application and configure the environment to run Apache Tomcat.

It uses Amazon Kinesis Data Firehose which is a fully managed service for delivering real-time streaming data to destinations such as Amazon S3. This service requires less operational overhead as compared to option A, B, and D. Additionally, it also uses Amazon API Gateway which is a fully managed service for creating, deploying, and managing APIs. These services help in reducing the operational overhead and automating the data ingestion process.

To achieve high availability with minimum downtime and minimum loss of data, the Auto Scaling group should be configured to use multiple Availability Zones to ensure that there is no single point of failure. The database should be configured as Multi-AZ to enable automatic failover in case of an outage in the primary Availability Zone. Additionally, an Amazon RDS Proxy instance can be used to improve the scalability and availability of the database by reducing connection failures and improving failover times.

it allows the company to keep the CloudTrail logs and query them at any time. By using the CloudTrail event history in the centralized account, the company can view, filter, and download recent API activity across multiple AWS accounts. By creating an Amazon Athena table from the CloudTrail event history, the company can use a serverless interactive query service that makes it easy to analyze data in S3 using standard SQL. By querying the CloudTrail logs from Athena, the company can gain insights into user activity and resource changes. References:

Viewing Events with CloudTrail Event History

Querying AWS CloudTrail Logs

Amazon Athena

AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. Lambda can be used to tag resources with the cost center ID of the user who created the resource, by querying the RDS database that maps users to cost centers. Amazon EventBridge is a serverless event bus service that enables event-driven architectures. EventBridge can be configured to react to AWS CloudTrail events, which are recorded API calls made by or on behalf of the AWS account. EventBridge can invoke the Lambda function when a resource is created in the specific AWS account, passing the user identity and resource information as parameters. This solution will meet the requirements, as it enables automatic tagging of resources based on the user and cost center mapping.

References:

1 provides an overview of AWS Lambda and its benefits.

2 provides an overview of Amazon EventBridge and its benefits.

3 explains the concept and benefits of AWS CloudTrail events.

"Security groups create an outbound rule for every inbound rule." Not completely right. Statefull does NOT mean that if you create an inbound (or outbound) rule, it will create an outbound (or inbound) rule. What it does mean is: suppose you create an inbound rule on port 443 for the X ip. When a request enters on port 443 from X ip, it will allow traffic out for that request in the port 443. However, if you look at the outbound rules, there will not be any outbound rule on port 443 unless explicitly create it. In ACLs, which are stateless, you would have to create an inbound rule to allow incoming requests and an outbound rule to allow your application responds to those incoming requests.

https://docs.aws.amazon.com/vpc/latest/userguide/VPC_SecurityGroups.html#SecurityGroupRules

it allows the company to improve the response time of the web application and decrease latency when retrieving product details from the Amazon DynamoDB table. By setting up a DynamoDB Accelerator (DAX) cluster, the company can use a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement. By routing all read requests through DAX, the company can reduce the number of read operations on the DynamoDB table and improve the user experience. References:

Amazon DynamoDB Accelerator (DAX)

Using DAX with DynamoDB

Kubernetes API requests within your cluster's VPC (such as node to control plane communication) use the private VPC endpoint. https://docs.aws.amazon.com/eks/latest/userguide/cluster-endpoint.html

AWS Lambda charges you based on the number of invocations and the execution time of your function. Since the data processing job is relatively small (2 MB of data), Lambda is a cost-effective choice. You only pay for the actual usage without the need to provision and maintain infrastructure.

To connect two VPCs in the same Region within the same AWS account, VPC peering is the most cost-effective solution. VPC peering allows direct network traffic between the VPCs without requiring a gateway, VPN connection, or AWS Transit Gateway. VPC peering also does not incur any additional charges for data transfer between the VPCs.

References:

What Is VPC Peering?

VPC Peering Pricing

This answer is correct because it meets the requirements of maximizing the reliability of the application’s infrastructure. You can update the DB instance to be Multi-AZ, which means that Amazon RDS automatically provisions and maintains a synchronous standby replica in a different Availability Zone. The primary DB instance is synchronously replicated across Availability Zones to a standby replica to provide data redundancy and minimize latency spikes during system backups. Running a DB instance with high availability can enhance availability during planned system maintenance. It can also help protect your databases against DB instance failure and Availability Zone disruption. You can also enable deletion protection on the DB instance, which prevents the DB instance from being deleted by any user. You can place the EC2 instances behind an Application Load Balancer, which distributes incoming application traffic across multiple targets, such as EC2 instances, in multiple Availability Zones. This increases the availability and fault tolerance of your applications. You can run the EC2 instances in an EC2 Auto Scaling group across multiple Availability Zones, which ensures that you have the correct number of EC2 instances available to handle the load for your application. You can use scaling policies to adjust the number of instances in your Auto Scaling group in response to changing demand.

References:

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.MultiAZSingleStandby.html

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_DeleteInstance.html#USER_DeleteInstance.DeletionProtection

https://docs.aws.amazon.com/elasticloadbalancing/latest/application/introduction.html

https://docs.aws.amazon.com/autoscaling/ec2/userguide/AutoScalingGroup.html

AWS Lambda is a service that lets users run code without provisioning or managing servers. It automatically scales and manages the underlying compute resources for the code. It supports multiple languages, such as Java, Python, Node.js, and Go1. By using AWS Lambda for the REST API, the solution can meet the requirements of 1 GB of memory and minimal administrative effort.

Amazon RDS is a service that makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating time-consuming administration tasks such as hardware provisioning, database setup, patching and backups. It supports multiple database engines, such as MySQL, PostgreSQL, Oracle, and SQL Server2. By using Amazon RDS for the data store, the solution can meet the requirements of 2 GB of storage and a relational format.

A. Amazon EC2. This solution will not meet the requirement of minimal administrative effort, as Amazon EC2 is a service that provides virtual servers in the cloud that users have to configure and manage themselves. It requires users to choose an instance type, an operating system, a security group, and other options3.

D. Amazon DynamoDB. This solution will not meet the requirement of a relational format, as Amazon DynamoDB is a service that provides a key-value and document database that delivers single-digit millisecond performance at any scale. It is a non-relational or NoSQL database that does not support joins or transactions.

E. Amazon Elastic Kubernetes Services (Amazon EKS). This solution will not meet the requirement of minimal administrative effort, as Amazon EKS is a service that provides a fully managed Kubernetes service that users have to configure and manage themselves. It requires users to create clusters, nodes groups, pods, services, and other Kubernetes resources.

Reference URL: https://aws.amazon.com/lambda/

 To use an event-driven programming model with AWS Lambda and reduce operational overhead, Amazon API Gateway and Amazon DynamoDB are suitable solutions. Amazon API Gateway can receive the data from the sensors and invoke AWS Lambda functions to process the data. AWS Lambda can run code without provisioning or managing servers, and scale automatically with the incoming requests. Amazon DynamoDB can store the data in a fast and flexible NoSQL database that can handle any amount of data with consistent performance.

References:

What Is Amazon API Gateway?

What Is AWS Lambda?

What Is Amazon DynamoDB?

https://spin.atomicobject.com/2020/09/15/aws-s3-encrypt-existing-objects/

The solution that meets the requirements of high availability, resiliency, and minimal operational effort is to use AWS Transfer for SFTP and an Amazon S3 bucket for storage. This solution allows the company to securely transfer files over SFTP to Amazon S3, which is a durable and scalable object storage service. The company can then modify the application to pull the batch files from Amazon S3 to an Amazon EC2 instance for processing. The EC2 instance can be part of an Auto Scaling group with a scheduled scaling policy to run the batch operation only at night. This way, the company can save costs by scaling down the EC2 instances when they are not needed. The other solutions do not meet all the requirements because they either use Amazon EFS or Amazon EBS for storage, which are more expensive and less scalable than Amazon S3, or they do not use a scheduled scaling policy to optimize the EC2 instances usage. References :=

AWS Transfer for SFTP

Amazon S3

Amazon EC2 Auto Scaling

it allows the company to deploy an application that processes large quantities of data in parallel and prevent groups of nodes from sharing the same underlying hardware. By running the EC2 instances in a spread placement group, the company can launch a small number of instances across distinct underlying hardware to reduce correlated failures. A spread placement group ensures that each instance is isolated from each other at the rack level. References:

Placement Groups

Spread Placement Groups

AWS Global Accelerator is a networking service that improves the performance and availability of applications for global users. It uses the AWS global network to route user traffic to the optimal endpoint based on performance and health. It also provides static IP addresses that act as a fixed entry point to the applications and support both TCP and UDP protocols1. By using AWS Global Accelerator, the solution can ensure the lowest possible latency for all users.

A. Use AWS Global Accelerator to create an accelerator. Create an Application Load Balancer (ALB) behind an accelerator endpoint that uses Global Accelerator integration and listening on the TCP and UDP ports. Update the Auto Scaling group to register instances on the ALB. This solution will not work, as ALB does not support UDP protocol2.

C. Create an Amazon CloudFront content delivery network (CDN) endpoint. Create a Network Load Balancer (NLB) behind the endpoint and listening on the TCP and UDP ports. Update the Auto Scaling group to register instances on the NLB. Update CloudFront to use the NLB as the origin. This solution will not work, as CloudFront does not support UDP protocol3.

D. Create an Amazon Cloudfront content delivery network (CDN) endpoint. Create an Application Load Balancer (ALB) behind the endpoint and listening on the TCP and UDP ports. Update the Auto Scaling group to register instances on the ALB. Update CloudFront to use the ALB as the origin. This solution will not work, as CloudFront and ALB do not support UDP protocol23.

Reference URL: https://aws.amazon.com/global-accelerator/

AWS Fargate is a technology that you can use with Amazon ECS to run containers without having to manage servers or clusters of Amazon EC2 instances. With Fargate, you no longer have to provision, configure, or scale clusters of virtual machines to run containers. https://docs.aws.amazon.com/AmazonECS/latest/userguide/what-is-fargate.html

To resolve the issue of longer delivery times for meeting invitations, the solutions architect can recommend adding an Auto Scaling group for the application that sends meeting invitations and configuring the Auto Scaling group to scale based on the depth of the SQS queue. This will allow the application to scale up as the number of appointment requests increases, improving the performance and delivery times of the meeting invitations.

To ingest, transform, and query real-time streaming data from multiple sources, Amazon Kinesis and Amazon MSK are suitable solutions. Amazon Kinesis Data Streams can stream the data from various sources and integrate with other AWS services. Amazon Kinesis Data Analytics can transform the data using SQL or Apache Flink. Amazon Kinesis Data Firehose can write the data to Amazon S3 or other destinations. Amazon Athena can query the transformed data from Amazon S3 using standard SQL. Amazon MSK can stream the data using Apache Kafka, which is a popular open-source platform for streaming data. AWS Glue can transform the data using Apache Spark or Python scripts and write the data to Amazon S3 or other destinations. Amazon Athena can also query the transformed data from Amazon S3 using standard SQL.

References:

What Is Amazon Kinesis Data Streams?

What Is Amazon Kinesis Data Analytics?

What Is Amazon Kinesis Data Firehose?

What Is Amazon Athena?

What Is Amazon MSK?

What Is AWS Glue?

Provisioned capacity is best if you have relatively predictable application traffic, run applications whose traffic is consistent, and ramps up or down gradually. On-demand capacity mode is best when you have unknown workloads, unpredictable application traffic and also if you only want to pay exactly for what you use. The on-demand pricing model is ideal for bursty, new, or unpredictable workloads whose traffic can spike in seconds or minutes, and when under-provisioned capacity would impact the user experience. https://docs.aws.amazon.com/wellarchitected/latest/serverless-applications-lens/capacity.html

 it allows the company to store sensitive customer information in a managed AWS service and give customers the ability to complete purchase transactions on the website. By using AWS Key Management Service (AWS KMS) client-side encryption, the company can encrypt the data before sending it to Amazon RDS for MySQL. This ensures that sensitive customer data is protected, even from database administrators, as only the application has access to the encryption keys. References:

Using Encryption with Amazon RDS for MySQL

Encrypting Amazon RDS Resources

https://aws.amazon.com/blogs/aws/introducing-amazon-s3-object-lambda-use-your-cod e-to-process-data-as-it-is-being-retrieved-from-s3/

S3 Object Lambda is a new feature of Amazon S3 that enables customers to add their own code to process data retrieved from S3 before returning it to the application. By using S3 Object Lambda, the data can be processed and transformed in real-time, without the need to store multiple copies of the data in separate S3 buckets or DynamoDB tables.

In this case, the Pll can be removed from the data by the code added to S3 Object Lambda before returning the data to the two applications that do not need to process Pll. The one application that requires Pll can be pointed to the original S3 bucket where the Pll is still stored.

Using S3 Object Lambda is the simplest and most cost-effective solution, as it eliminates the need to maintain multiple copies of the same data in different buckets or tables, which can result in additional storage costs and operational overhead.

To reduce startup latency for Lambda functions that run on Java 11, Lambda SnapStart is a suitable solution. Lambda SnapStart is a feature that enables faster cold starts and lower outlier latencies for Java 11 functions. Lambda SnapStart uses a pre-initialized Java Virtual Machine (JVM) to run the functions, which reduces the initialization time and memory footprint. Lambda SnapStart does not incur any additional charges.

References:

Lambda SnapStart for Java 11 Functions

Lambda SnapStart FAQs

This answer is correct because it meets the requirements of accommodating the larger workload without adding infrastructure and minimizing the cost. Reserved DB instances are a billing discount applied to the use of certain on-demand DB instances in your account. Reserved DB instances provide you with a significant discount compared to on-demand DB instance pricing. You can buy reserved DB instances for the total workload and choose between three payment options: No Upfront, Partial Upfront, or All Upfront. You can make the Amazon RDS for PostgreSQL DB instance larger by modifying its instance type to a higher performance class. This way, you can increase the CPU, memory, and network capacity of your DB instance and handle the increased workload.

References:

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_WorkingWithReservedDBInstances.html

https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.DBInstanceClass.html

https://aws.amazon.com/blogs/big-data/manage-fine-grained-access-control-using-aws-lake-formation/

A cluster placement group is a logical grouping of EC2 instances within a single Availability Zone that are placed close together to minimize network latency. This is suitable for latency-sensitive HPC workloads that require high network performance. A compute optimized EC2 instance is an instance type that has a high ratio of vCPUs to memory, which is ideal for compute-intensive applications. Amazon FSx for NetApp ONTAP is a fully managed service that provides NFS and SMB multi-protocol access from the file system, as well as features such as data deduplication, compression, thin provisioning, and snapshots. This solution will meet the requirements with the least latency, as it leverages the low-latency network and storage performance of AWS.

References:

1 explains how cluster placement groups work and their benefits.

2 describes the characteristics and use cases of compute optimized EC2 instances.

3 provides an overview of Amazon FSx for NetApp ONTAP and its features.

A cross-account IAM role is a way to grant users from one AWS account access to resources in another AWS account. The cross-account IAM role can have a read-only access policy attached to it, which allows the users to download objects from the S3 buckets without modifying or deleting them. The cross-account IAM role also reduces the operational overhead of managing multiple IAM users and policies in each account. The cross-account IAM role meets all the requirements of the question, while the other options do not. References:

https://docs.aws.amazon.com/AmazonS3/latest/userguide/example-walkthroughs-managing-access-example2.html

https://aws.amazon.com/blogs/storage/setting-up-cross-account-amazon-s3-access-with-s3-access-points/

https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_create_for-user_externalid.html

Generally, for building a hierarchical relationship model, a graph database such as Amazon Neptune is a better choice. In some cases, however, DynamoDB is a better choice for hierarchical data modeling because of its flexibility, security, performance, and scale. https://docs.aws.amazon.com/prescriptive-guidance/latest/dynamodb-hierarchical-data-model/introduction.html

"An active, long-running transaction can slow the process of creating the read replica. We recommend that you wait for long-running transactions to complete before creating a read replica. If you create multiple read replicas in parallel from the same source DB instance, Amazon RDS takes only one snapshot at the start of the first create action. When creating a read replica, there are a few things to consider. First, you must enable automatic backups on the source DB instance by setting the backup retention period to a value other than 0. This requirement also applies to a read replica that is the source DB instance for another read replica" https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_ReadRepl.html

it allows the company to protect sensitive information submitted by users throughout the entire application stack and restrict access to certain applications. By configuring a CloudFront field-level encryption profile, the company can encrypt specific fields of user data at the edge locations before sending it to the origin servers. By using public-private key pairs, the company can ensure that only authorized applications can decrypt and access the sensitive information. References:

Field-Level Encryption

Encrypting and Decrypting Data

Consider using the default aws/s3 KMS key if: You're uploading or accessing S3 objects using AWS Identity and Access Management (IAM) principals that are in the same AWS account as the AWS KMS key. You don't want to manage policies for the KMS key. Consider using a customer managed key if: You want to create, rotate, disable, or define access controls for the key. You want to grant cross-account access to your S3 objects. You can configure the policy of a customer managed key to allow access from another account. https://repost.aws/knowledge-center/s3-object-encryption-keys

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This allows you to use your data to gain new insights for your business and customers. The first step to create a data warehouse is to launch a set of nodes, called an Amazon Redshift cluster. After you provision your cluster, you can upload your data set and then perform data analysis queries. Regardless of the size of the data set, Amazon Redshift offers fast query performance using the same SQL-based tools and business intelligence applications that you use today.

"You cannot reference the security group of a peer VPC that's in a different Region. Instead, use the CIDR block of the peer VPC." https://docs.aws.amazon.com/vpc/latest/peering/vpc-peering-security-groups.html

for "Highly available": Multi-AZ & for "least amount of changes to the application": Elastic Beanstalk automatically handles the deployment, from capacity provisioning, load balancing, auto-scaling to application health monitoring

AWS Backup is a fully managed service that allows you to centralize and automate data protection of AWS services across compute, storage, and database. AWS Backup Vault Lock is an optional feature of a backup vault that can help you enhance the security and control over your backup vaults. When a lock is active in Compliance mode and the grace time is over, the vault configuration cannot be altered or deleted by a customer, account/data owner, or AWS. This ensures that your backups are available for you until they reach the expiration of their retention periods and meet the regulatory requirements. References: https://docs.aws.amazon.com/aws-backup/latest/devguide/vaul t-lock.html

it allows the company to reduce the data output costs for accessing Amazon S3 from Amazon EC2 instances in a VPC. By provisioning a VPC gateway endpoint, the company can enable private connectivity between the VPC and S3. By configuring the route table for the private subnet to use the gateway endpoint as the route for all S3 traffic, the company can avoid using a NAT gateway, which charges for data processing and data transfer. References:

VPC Endpoints for Amazon S3

VPC Endpoints Pricing

Amazon Neptune: Neptune is a fully managed graph database service that is optimized for storing and querying highly connected data. It supports both property graph and RDF graph models, making it suitable for applications that need to analyze relationships between data entities.

Neptune Streams: Neptune Streams captures changes to the graph and streams these changes to other AWS services. This is useful for applications that need to monitor and respond to changes in real-time, such as providing recommendations based on user interactions and relationships.

Least Operational Overhead: Using Neptune Streams directly with Amazon Neptune ensures that the solution is tightly integrated, reducing the need for additional components and minimizing operational overhead. This integration simplifies the architecture by eliminating the need for a separate service like Kinesis for change processing.

References:

Amazon Neptune Documentation

Neptune Streams Documentation

Amazon GuardDuty is a threat detection service that continuously monitors for malicious activity and unauthorized behavior across the AWS account and workloads. GuardDuty analyzes data sources such as AWS CloudTrail event logs, Amazon VPC Flow Logs, and DNS logs to identify potential threats such as compromised instances, reconnaissance, port scanning, and data exfiltration. GuardDuty can report its findings to AWS Security Hub, which is a service that provides a comprehensive view of the security posture of the AWS account and workloads. Security Hub aggregates, organizes, and prioritizes security alerts from multiple AWS services and partner solutions, and displays them on a dashboard. This solution will meet the requirements, as it enables continuous monitoring, reporting, and visualization of malicious activity in the AWS account, workloads, and access patterns to the S3 bucket.

References:

1 provides an overview of Amazon GuardDuty and its benefits.

2 explains how GuardDuty generates and reports findings based on threat detection.

3 provides an overview of AWS Security Hub and its benefits.

4 describes how Security Hub collects and displays findings from multiple sources on a dashboard

AWS Fargate is a serverless compute engine for containers that provides resource isolation at the pod level in Amazon EKS. Each pod gets its own CPU, memory, storage, and elastic network interface, ensuring that resources are not shared. This makes Fargate the ideal choice for multi-tenant architectures that require strict isolation.

Option A, C, and D: While EC2-based EKS solutions with taints and tolerations can provide logical isolation, they do not offer the strict physical isolation of resources like Fargate.

AWS Documentation References:

AWS Fargate Overview

EKS with Fargate Resource Isolation

Understanding the Requirement: The order processing system requires multiple independent validation steps, each handled by separate Lambda functions, with each function accessing only the subset of order information it needs. The system should be loosely coupled to accommodate future changes.

Analysis of Options:

Amazon SQS with a new Lambda function for transformation: This involves additional complexity in creating and managing multiple SQS queues and an extra Lambda function for data transformation.

Amazon SNS with message filtering: While SNS supports message filtering, it is more suited for pub/sub messaging patterns rather than event-driven processing requiring fine-grained control over the data sent to each function.

Amazon EventBridge with input transformers: EventBridge is designed for event-driven architectures, allowing for fine-grained control with input transformers that can modify and filter the event data sent to each target Lambda function, ensuring each function receives only the necessary information.

SQS with synchronous Lambda invocations: This approach adds unnecessary complexity with synchronous invocations and is not ideal for an event-driven, loosely coupled architecture.

Best Solution:

Amazon EventBridge with input transformers: This option provides the most flexible, scalable, and loosely coupled architecture, enabling each Lambda function to receive only the required subset of data.

References:

Amazon EventBridge

EventBridge Input Transformer

Amazon S3 Intelligent-Tiering: This storage class is designed to optimize costs by automatically moving data between two access tiers (frequent and infrequent) when access patterns change. It provides cost savings without performance impact or operational overhead.

S3 Lifecycle Rules: By creating an S3 Lifecycle rule, the company can automatically transition objects to the Intelligent-Tiering storage class. This eliminates the need for manual intervention and ensures that objects are moved to the most cost-effective storage tier based on their access patterns.

Operational Efficiency: Intelligent-Tiering requires no additional management and delivers immediate availability for frequently accessed objects. This makes it the most operationally efficient solution for the given requirements.

References:

Amazon S3 Intelligent-Tiering

S3 Lifecycle Policies

Aurora I/O-Optimized: This storage configuration is designed to provide consistent high performance for Aurora databases. It automatically scales IOPS as the workload increases, without needing to provision IOPS separately.

Cost-Effectiveness: With Aurora I/O-Optimized, you only pay for the storage and I/O you use, making it a cost-effective solution for applications with varying and unpredictable I/O demands.

Implementation:

During the creation of the Aurora PostgreSQL Serverless v2 cluster, select the I/O-Optimized storage configuration.

The storage system will automatically handle scaling and performance optimization based on the application load.

Operational Efficiency: This configuration reduces the need for manual tuning and ensures optimal performance without additional administrative overhead.

References:

Amazon Aurora I/O-Optimized

 This solution meets the requirements with the least operational overhead because it uses AWS services that are fully managed and scalable. The EventBridge rule can detect the DeleteKey operation from the AWS KMS API and trigger the Systems Manager Automation runbook, which can execute a predefined workflow to cancel the key deletion. The EventBridge rule can also publish an SNS message to the topic that sends an email notification to the administrators. This way, the company can prevent the accidental deletion of KMS keys and notify the administrators of any attempts to delete them.

Option A is not a valid solution because AWS Config rules are used to evaluate the configuration of AWS resources, not to cancel the deletion of KMS keys. Option B is not a valid solution because it requires creating and maintaining a custom Lambda function that has logic to prevent KMS key deletion, which adds operational overhead. Option D is not a valid solution because it only notifies the administrators of the DeleteKey operation, but does not cancel it.

References:

Using Amazon EventBridge rules to trigger Systems Manager Automation workflows - AWS Systems Manager

Using Amazon SNS for system-to-administrator communications - Amazon Simple Notification Service

Deleting AWS KMS keys - AWS Key Management Service

Option A allows importing your own encryption keys into AWS KMS, ensuring control over key material.

Option D uses S3 Glacier with SSE-C, where the customer controls the encryption keys, meeting compliance needs.

Option B uses AWS-managed key material, violating the requirement for key material control.

Option C and E are not fully compliant with the control requirement.

AWS Organizations: AWS Organizations allows you to create multiple AWS accounts and manage them centrally. You can organize accounts into organizational units (OUs) and apply policies to these units.

Organizational Units (OUs):

Create separate OUs for each department: finance, data analytics, and development.

Place the respective AWS accounts for each department into their corresponding OUs.

Service Control Policies (SCPs):

SCPs are policies that can restrict which AWS services and actions are available to accounts in an OU.

Create SCPs to define which services each department can use and attach these policies to the appropriate OUs.

SCPs apply to all IAM users, groups, and roles within the accounts in the OU, providing centralized control over service usage.

Operational Efficiency: Using AWS Organizations and SCPs provides a scalable and centralized way to manage permissions across multiple accounts with minimal operational overhead.

References:

AWS Organizations

Service Control Policies

AWS Backup is the most appropriate solution for managing backups with minimal operational overhead while meeting the regulatory requirement to retain data for 90 days and enabling point-in-time restore for up to 14 days.

AWS Backup: AWS Backup provides a centralized backup management solution that supports automated backup scheduling, retention management, and compliance reporting across AWS services, including Amazon RDS. By creating a backup plan, you can define a retention period (in this case, 90 days) and automate the backup process.

Point-in-Time Restore (PITR): Amazon RDS supports point-in-time restore for up to 35 days with automated backups. By using AWS Backup in conjunction with RDS, you ensure that your backup strategy meets the requirement for restoring data to a specific point in time within the last 14 days.

Why Not Other Options?:

Option A (RDS Automated Backups): While RDS automated backups support PITR, they do not directly support retention beyond 35 days without manual intervention.

Option B (Manual Snapshots): Manually creating and managing snapshots is operationally intensive and less automated compared to AWS Backup.

Option C (Aurora Clones): Aurora Clone is a feature specific to Amazon Aurora and is not applicable to Amazon RDS for Oracle.

AWS References:

AWS Backup - Overview of AWS Backup and its capabilities.

Amazon RDS Automated Backups - Information on how RDS automated backups work and their limitations.

AWS Secrets Manager is designed specifically to securely store and manage sensitive information such as database credentials. It integrates seamlessly with AWS services like Lambda and RDS, and it provides automatic credential rotation with minimal operational overhead.

AWS Secrets Manager: By storing the database credentials in Secrets Manager, you ensure that the credentials are securely stored, encrypted, and managed. Secrets Manager provides a built-in mechanism to automatically rotate credentials at regular intervals (e.g., every 30 days), which helps in maintaining security best practices without requiring additional manual intervention.

Lambda Integration: The Lambda function can be easily configured to retrieve the credentials from Secrets Manager using the AWS SDK, ensuring that the credentials are accessed securely at runtime.

Why Not Other Options?:

Option A (Parameter Store with Rotation): While Parameter Store can store parameters securely, Secrets Manager is more tailored for secrets management and automatic rotation, offering more features and less operational overhead.

Option C (Encrypted Lambda environment variable): Storing credentials directly in Lambda environment variables, even when encrypted, requires custom code to manage rotation, which increases operational complexity.

Option D (KMS with automatic rotation): KMS is for managing encryption keys, not for storing and rotating secrets like database credentials. This option would require more custom implementation to manage credentials securely.

AWS References:

AWS Secrets Manager - Detailed documentation on how to store, manage, and rotate secrets using AWS Secrets Manager.

Using Secrets Manager with AWS Lambda - Guidance on integrating Secrets Manager with Lambda for secure credential management.

Understanding the Requirement: The application running on EC2 instances in private subnets needs frequent access to large confidential files stored in S3, minimizing data transfer costs.

Analysis of Options:

Gateway Endpoint for S3: Provides a secure, scalable, and cost-effective way for instances in private subnets to access S3 without using the internet or NAT gateways, thus minimizing data transfer costs.

Single NAT Gateway: Incurs additional costs for data transfer through the NAT gateway, which is not cost-effective.

PrivateLink Interface Endpoint for S3: Primarily used for accessing AWS services over a private connection but is more complex and costly compared to a gateway endpoint for S3.

Multiple NAT Gateways: Increases costs significantly and adds complexity without offering the cost benefits of a gateway endpoint.

Best Solution:

Gateway Endpoint for S3: This solution provides the required access with the least data transfer costs and minimal complexity.

References:

VPC Endpoints for Amazon S3

Gateway Endpoints

AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. By creating a Config rule, you can automatically check whether your Amazon EBS volumes are encrypted and flag those that are not, with minimal cost and configuration effort.

AWS Config Rule: AWS Config provides managed rules that you can use to automatically check the compliance of your resources against predefined or custom criteria. In this case, you would create a rule to evaluate EBS volumes and determine if they are encrypted. If a volume is not encrypted, the rule will flag it, allowing you to take corrective action.

Operational Overhead: This approach significantly reduces operational overhead because once the rule is in place, it continuously monitors your EBS volumes for compliance, and there’s no need for manual checks or custom scripting.

Why Not Other Options?:

Option A (Lambda with API calls and EventBridge): While this can work, it involves writing and maintaining custom code, which increases operational overhead compared to using a managed AWS Config rule.

Option B (API calls on Fargate): Running API calls on Fargate is more complex and costly compared to using AWS Config, which provides a simpler, managed solution.

Option C (IAM policy with Cost Explorer): This option does not directly enforce encryption compliance and involves manual intervention, making it less efficient and more prone to errors.

AWS References:

AWS Config Rules - Overview of AWS Config rules and how they can be used to evaluate resource configurations.

Amazon EBS Encryption - Information on how to manage and enforce encryption for EBS volumes.

Comprehensive Explanation:Using CloudFront with signed cookies allows access control to the files based on the user's credentials while providing a consistent URL for all users. This approach ensures high performance and scalability while keeping access restricted to authorized users. Using signed URLs (D) would require individual URLs for each file, which contradicts the requirement to use the same URL.

References:

CloudFront Signed Cookies

Amazon S3 and CloudFront Integration

Amazon Route 53 Multivalue Answer Routing: This routing policy allows Route 53 to return multiple values, such as IP addresses, in response to DNS queries. This can distribute traffic across multiple resources and includes health checks to ensure traffic is only routed to healthy instances.

Health Checks:

Configure health checks for each Region to monitor the health of the website instances.

Route 53 will only include healthy instances in the DNS responses, ensuring that traffic is not routed to an unhealthy Region.

Load Distribution and Disaster Recovery:

Multivalue answer routing helps balance the load between instances in different Regions.

If instances in one Region become unhealthy, Route 53 will route traffic to the healthy instances in the other Region.

Operational Simplicity: This solution does not require complex configurations or additional resources, making it a simple yet effective way to distribute traffic and ensure high availability.

References:

Amazon Route 53 Routing Policies

Multivalue Answer Routing

Amazon Timestream: Purpose-built time series database optimized for telemetry and IoT data ingestion and analytics.

Amazon SageMaker: Provides ML capabilities for predictive maintenance workflows.

Amazon QuickSight: Efficiently generates interactive, real-time visual reports from Timestream data.

Optimized for Scale: Timestream efficiently handles large-scale telemetry data with time-series indexing and queries.

AWS Lake Formation is designed for managing fine-grained access control to data in an efficient manner:

Granular Permissions: Lake Formation allows column-level, row-level, and table-level access controls, which can precisely define access to PII data.

Integration with AWS Glue Catalog: Lake Formation natively integrates with AWS Glue for seamless data cataloging and access control.

Operational Efficiency: Centralized access control policies minimize the need for separate IAM roles or policies.

Why Other Options Are Not Ideal:

Option A:

Creating multiple IAM policies introduces complexity and lacks column-level access control.Not efficient.

Option B:

Managing multiple IAM roles for granular access is operationally complex.Not efficient.

Option D:

Creating views in Glue adds unnecessary complexity and may not provide the level of granularity that Lake Formation offers.Not the best choice.

AWS References:

AWS Lake Formation:AWS Documentation - Lake Formation

Fine-Grained Permissions with Lake Formation:AWS Documentation - Fine-Grained Permissions

AWS WAF (Web Application Firewall): AWS WAF allows you to create custom rules to block or allow web requests based on conditions that you specify.

Web ACL (Access Control List):

Create a web ACL and associate it with the ALB.

Use IP rule sets to specify the IP addresses of the retail locations that are allowed to access the application.

Security and Flexibility:

AWS WAF provides a scalable way to manage access control, ensuring that only traffic from registered IP addresses is allowed.

You can dynamically update the IP rule sets to add or remove IP addresses as needed.

Operational Simplicity: Using AWS WAF with a web ACL is straightforward and integrates seamlessly with the ALB, providing an efficient solution for managing access control based on IP addresses.

References:

AWS WAF

How AWS WAF Works