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

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

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

This solution meets the requirement of reducing the number of database reads while ensuring high availability for a batch application that consists of a backend with multiple Amazon RDS databases. Amazon RDS read replicas are copies of the primary database instance that can serve read-only traffic. You can create one or more read replicas for a primary database instance and connect to them using a special endpoint. Read replicas can improve the performance and availability of your application by offloading read queries from the primary database instance.

Option B is incorrect because using Amazon ElastiCache for Redis can provide a fast, in-memory data store that can cache frequently accessed data, but it does not support replication from Amazon RDS databases. Option C is incorrect because using Amazon Route 53 DNS caching can improve the performance and availability of DNS queries, but it does not reduce the number of database reads. Option D is incorrect because using Amazon ElastiCache for Memcached can provide a fast, in-memory data store that can cache frequently accessed data, but it does not support replication from Amazon RDS databases.

References:

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

The solution that meets the requirements with the least operational overhead is to create a **Regional AWS WAF web ACL with a rate-based rule** and associate the web ACL with the API Gateway stage. This solution will protect the application from HTTP flood attacks by monitoring incoming requests and blocking requests from IP addresses that exceed the predefined rate. Amazon CloudFront distribution with Lambda@Edge in front of the API Gateway Regional API endpoint is also a good solution but it requires more operational overhead than the previous solution. Using Amazon CloudWatch metrics to monitor the Count metric and alerting the security team when the predefined rate is reached is not a solution that can protect against HTTP flood attacks. Creating an Amazon CloudFront distribution in front of the API Gateway Regional API endpoint with a maximum TTL of 24 hours is not a solution that can protect against HTTP flood attacks.

Amazon DocumentDB (with MongoDB compatibility) is a fast, reliable, and fully managed database service. Amazon DocumentDB makes it easy to set up, operate, and scale MongoDB-compatible databases in the cloud. With Amazon DocumentDB, you can run the same application code and use the same drivers and tools that you use with MongoDB.

https://docs.aws.amazon.com/documentdb/latest/developerguide/what-is.html

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

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.

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

A solutions architect should recommend option A, which is to configure AWS WAF rules and associate them with the ALB. This will allow the company to apply traffic filtering at the application layer, which is necessary for protecting the ALB against common application-level attacks such as cross-site scripting or SQL injection. AWS WAF is a managed service that makes it easy to protect web applications from common web exploits that could affect application availability, compromise security, or consume excessive resources. The company can easily manage and update the rules to ensure the security of its application.

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

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

https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-scaling-target-tracking.html#target-tracking-choose-metrics

A target tracking scaling policy is a type of dynamic scaling policy that adjusts the capacity of an Auto Scaling group based on a specified metric and a target value1. A target tracking scaling policy can automatically scale out or scale in the Auto Scaling group to keep the actual metric value at or near the target value1. A target tracking scaling policy is suitable for scenarios where the load on the application changes frequently and unpredictably, such as during working hours2.

To meet the requirements of the scenario, the solutions architect should use a target tracking scaling policy to scale the Auto Scaling group based on instance CPU utilization. Instance CPU utilization is a common metric that reflects the demand on the application1. The solutions architect should specify a target value that represents the ideal average CPU utilization level for the application, such as 50 percent1. Then, the Auto Scaling group will scale out or scale in to maintain that level of CPU utilization.

Scheduled scaling is a type of scaling policy that performs scaling actions based on a date and time3. Scheduled scaling is suitable for scenarios where the load on the application changes periodically and predictably, such as on weekends2.

To meet the requirements of the scenario, the solutions architect should also use scheduled scaling to change the Auto Scaling group minimum, maximum, and desired capacity to zero for weekends. This way, the Auto Scaling group will terminate all instances on weekends when they are not required to operate. The solutions architect should also revert to the default values at the start of the week, so that the Auto Scaling group can resume normal operation.

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.

The S3 Block Public Access feature allows you to restrict public access to S3 buckets and objects within the account. You can enable this feature at the account level to prevent any S3 bucket from being made public, regardless of the bucket policy settings. AWS Organizations can be used to apply a Service Control Policy (SCP) to the account to prevent IAM users from changing this setting, ensuring that all S3 objects remain private. This is a straightforward and effective solution that requires minimal operational overhead.

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.

This solution satisfies the requirements in the following ways:

• AWS Backup will automatically take full backups of the DynamoDB table on the schedule defined in the backup plan (the first of each month).

• The lifecycle policy can transition backups to cold storage after 6 months, meeting that requirement.

• Setting a 7-year retention period in the backup plan will ensure each backup is retained for 7 years as required.

• AWS Backup manages the backup jobs and lifecycle policies, requiring no custom scripting or management.

Read replica use cases - You have a production database that is taking on normal load & You want to run a reporting application to run some analytics • You create a Read Replica to run the new workload there • The production application is unaffected • Read replicas are used for SELECT (=read) only kind of statements (not INSERT, UPDATE, DELETE)

Configure an EC2 Auto Scaling scheduled scaling policy based on the monthly schedule is the best option because it allows for the proactive scaling of the EC2 instances before the monthly batch run begins. This will ensure that the application is able to handle the increased workload without experiencing downtime. The scheduled scaling policy can be configured to increase the number of instances in the Auto Scaling group a few hours before the batch run and then decrease the number of instances after the batch run is complete. This will ensure that the resources are available when needed and not wasted when not needed. The most appropriate solution to handle the increased workload during the monthly batch run and avoid downtime would be to configure an EC2 Auto Scaling scheduled scaling policy based on the monthly schedule.

https://docs.aws.amazon.com/autoscaling/ec2/userguide/ec2-auto-scaling-scheduled-scaling.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.

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

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.

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/

A) Enable AWS CloudTrail and use it for auditing. AWS CloudTrail provides a record of API calls and can be used to audit changes made to EC2 instances and security groups. By analyzing CloudTrail logs, the solutions architect can track who provisioned oversized instances or modified security groups without proper approval. D) Enable AWS Config and create rules for auditing and compliance purposes. AWS Config can record the configuration changes made to resources like EC2 instances and security groups. The solutions architect can create AWS Config rules to monitor for non-compliant changes, like launching certain instance types or opening security group ports without permission. AWS Config would alert on any violations of these rules.

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.

This option is the most efficient because it uses AWS Storage Gateway, which is a service that connects an on-premises software appliance with cloud-based storage to provide seamless integration with data security features between your on-premises IT environment and the AWS storage infrastructure1. It also uses a stored volume gateway, which is a type of volume gateway that stores your primary data locally and asynchronously backs up point-in-time snapshots of your data to Amazon S32. It also runs the Storage Gateway software application on premises and maps the gateway storage volumes to on-premises storage, which enables you to use your existing storage hardware and network infrastructure. It also mounts the gateway storage volumes to provide local access to the data, which ensures that your data is available for low latency access on premises while also getting backed up to AWS. This solution meets the requirement of maintaining local access to all the data while it is backed up on AWS and ensuring that the data backed up on AWS is automatically and securely transferred. Option A is less efficient because it uses AWS Snowball, which is a physical device that lets you transfer large amounts of data into and out of AWS3. However, this does not provide a periodic backup solution, as it requires manual handling and shipping of the device. It also configures on-premises systems to mount the Snowball S3 endpoint to provide local access to the data, which could introduce additional complexity and latency. Option B is less efficient because it uses AWS Snowball Edge, which is a physical device that has onboard storage and compute capabilities for select AWS capabilities. However, this does not provide a periodic backup solution, as it requires manual handling and shipping of the device. It also uses the Snowball Edge file interface to provide on-premises systems with local access to the data, which could introduce additional complexity and latency. Option C is less efficient because it uses AWS Storage Gateway and configures a cached volume gateway, which is a type of volume gateway that stores your primary data in Amazon S3 and retains a copy of frequently accessed data subsets locally. However, this does not provide local access to all the data, as only some data subsets are cached locally. It also configures a percentage of data to cache locally, which could incur higher costs and complexity than using a stored volume gateway.

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 option is the most efficient because it sets an overall password policy for the entire AWS account, which is a way to specify complexity requirements and mandatory rotation periods for IAM user passwords1. It also meets the requirement of setting a password policy for all new users, as the password policy applies to all IAM users in the account. This solution meets the requirement of setting specific complexity requirements and mandatory rotation periods for IAM user passwords. Option B is less efficient because it sets a password policy for each IAM user in the AWS account, which is not possible as password policies can only be set at the account level. Option C is less efficient because it uses third-party vendor software to set password requirements, which is not necessary as IAM provides a built-in way to set password policies. Option D is less efficient because it attaches an Amazon CloudWatch rule to the Create_newuser event to set the password with the appropriate requirements, which is not possible as CloudWatch rules cannot modify IAM user passwords.

Enabling Amazon Elastic Block Store (Amazon EBS) fast snapshot restore on a snapshot allows you to quickly create a new Amazon Machine Image (AMI) from a snapshot, which can help reduce the initialization latency when provisioning new instances. Once the AMI is provisioned, you can replace the AMI in the Auto Scaling group with the new AMI. This will ensure that new instances are launched from the updated AMI and are able to meet the increased demand quickly.

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

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

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

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/vpc-endpoints-dynamodb.html

A VPC endpoint for DynamoDB enables Amazon EC2 instances in your VPC to use their private IP addresses to access DynamoDB with no exposure to the public internet. Your EC2 instances do not require public IP addresses, and you don't need an internet gateway, a NAT device, or a virtual private gateway in your VPC. You use endpoint policies to control access to DynamoDB. Traffic between your VPC and the AWS service does not leave the Amazon network.

1. database shows no signs of being overloaded. CPU, memory, and disk access metrics are all low==>A and C out. We cannot only add nodes instance or add read replica, because database workload is totally fine, very low. 2. "least operational overhead"==>B out, because b need to configure lambda. 3. ROS proxy: Shares infrequently used connections; High availability with failover; Drives increased efficiency==>proxy can leverage failover to redirect traffic from timeout rds instance to healthy rds instance. So D is right.

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/

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.

https://aws.amazon.com/blogs/networking-and-content-delivery/deliver-your-apps-dynamic-content-using-amazon-cloudfront-getting-started-template/

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

Reserved is cheaper than on demand the company has. And it's meet the availabilty (HA) requirement as to spot instance that can be disrupted at any time. PRICING BELOW. On-Demand: 0% There’s no commitment from you. You pay the most with this option. Reserved : 40%-60%1-year or 3-year commitment from you. You save money from that commitment. Spot 50%-90% Ridiculously inexpensive because there’s no commitment from the AWS side.

A -> We can configure CloudFront to require HTTPS from clients (enhanced security) https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/using-https-viewers-to-cloudfront.html D - > storing static website on S3 provides scalability and less operational overhead, then configuration of Application LB and EC2 instances (hence E is out)

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/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."

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

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.

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

This solution meets the requirement of migrating a Windows-based application that requires the use of a shared Windows file system attached to multiple Amazon EC2 Windows instances that are deployed across multiple Availability Zones. Amazon FSx for Windows File Server provides fully managed shared storage built on Windows Server, and delivers a wide range of data access, data management, and administrative capabilities. It supports the Server Message Block (SMB) protocol and can be mounted to EC2 Windows instances across multiple Availability Zones.

Option A is incorrect because AWS Storage Gateway in volume gateway mode provides cloud-backed storage volumes that can be mounted as iSCSI devices from on-premises application servers, but it does not support SMB protocol or EC2 Windows instances. Option C is incorrect because Amazon Elastic File System (Amazon EFS) provides a scalable and elastic NFS file system for Linux-based workloads, but it does not support SMB protocol or EC2 Windows instances. Option D is incorrect because Amazon Elastic Block Store (Amazon EBS) provides persistent block storage volumes for use with EC2 instances, but it does not support SMB protocol or attaching multiple instances to the same volume.

References:

• https://aws.amazon.com/fsx/windows/
• https://docs.aws.amazon.com/fsx/latest/WindowsGuide/using-file-shares.html

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

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

In a typical development environment, dev and test databases are mostly utilized for 8 hours a day and sit idle when not in use. However, the databases are billed for the compute and storage costs during this idle time. To reduce the overall cost, Amazon RDS allows instances to be stopped temporarily. While the instance is stopped, you’re charged for storage and backups, but not for the DB instance hours. Please note that a stopped instance will automatically be started after 7 days. This post presents a solution using AWS Lambda and Amazon EventBridge that allows you to schedule a Lambda function to stop and start the idle databases with specific tags to save on compute costs. The second post presents a solution that accomplishes stop and start of the idle Amazon RDS databases using AWS Systems Manager.

https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles.html https://docs.aws.amazon.com/IA M/latest/UserGuide/id_users.html

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

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://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

https://docs.aws.amazon.com/sns/latest/dg/sns-dead-letter-queues.html

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://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-ec2-placementgroup.html

"A cluster placement group is a logical grouping of instances within a single Availability Zone that benefit from low network latency, high network throughput"

https://aws.amazon.com/cn/blogs/compute/cost-optimization-and-resilience-eks-with-spot-instances/

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

https://docs.aws.amazon.com/rekognition/latest/dg/moderation.html?pg=ln &sec=ft

https://docs.aws.amazon.com/rekognition/latest/dg/a2i-rekognition.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

https://docs.aws.amazon.com/kinesisanalytics/l atest/dev/what-is.html

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

https://aws.amazon.com/blogs/big-data/top-10-performance-tuning-tips-for-amazon-athena/

This solution meets the requirements of measuring the effectiveness of marketing campaigns by performing batch processing on csv files of sales data and storing the results in an Amazon S3 bucket once every hour. An AWS duo ETL process can use services such as AWS Glue or AWS Data Pipeline to extract data from S3, transform it into a more efficient format such as Apache Parquet, and load it back into S3. Apache Parquet is a columnar storage format that can improve the query performance and reliability of Athena by reducing the amount of data scanned, improving compression ratio, and enabling predicate pushdown.

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.

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/

Cloudfront for rapid response and s3 to minimize infrastructure.

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.

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

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/

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

Q: What does Amazon RDS manage on my behalf?

Amazon RDS manages the work involved in setting up a relational database: from provisioning the infrastructure capacity you request to installing the database software. Once your database is up and running, Amazon RDS automates common administrative tasks such as performing backups and patching the software that powers your database. With optional Multi-AZ deployments, Amazon RDS also manages synchronous data replication across Availability Zones with automatic failover.

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

Amazon Athena is the best choice for running one-time queries on streaming data. Although Amazon Kinesis Data Analytics provides an easy and familiar standard SQL language to analyze streaming data in real-time, it is designed for continuous queries rather than one-time queries[1]. On the other hand, Amazon Athena is a serverless interactive query service that allows querying data in Amazon S3 using SQL. It is optimized for ad-hoc querying and is ideal for running one-time queries on streaming data[2].AWS Lake Formation uses as a central place to have all your data for analytics purposes (E). Athena integrate perfect with S3 and can makes queries (A).

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/

ElastiCache can help speed up the read performance of the database by caching frequently accessed data, reducing latency and allowing the application to access the data more quickly. This solution requires minimal modifications to the current architecture, as ElastiCache can be used in conjunction with the existing Amazon RDS for MySQL database.

https://aws.amazon.com/certificate-manager/ :

"With AWS Certificate Manager, you can quickly request a certificate, deploy it on ACM-integrated AWS resources, such as Elastic Load Balancers, Amazon CloudFront distributions, and APIs on API Gateway, and let AWS Certificate Manager handle certificate renewals. It also enables you to create private certificates for your internal resources and manage the certificate lifecycle centrally."

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

Queue has Limited throughput (300 msg/s without batching, 3000 msg/s with batching whereby up-to 10 msg per batch operation; Msg duplicates not allowed in the queue (exactly-once delivery); Msg order is preserved (FIFO); Queue name must end with .fifo

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/

For standard accelerators, 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, which increases the availability of your applications. Endpoints for standard accelerators can be Network Load Balancers, Application Load Balancers, Amazon EC2 instances, or Elastic IP addresses that are located in one AWS Region or multiple Regions.

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

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.

Amazon S3 is a highly scalable and durable object storage service that can store and retrieve any amount of data from anywhere on the web1. Users can configure the application to upload images directly from each user’s browser to Amazon S3 through the use of a presigned URL. A presigned URL is a URL that gives access to an object in an S3 bucket for a limited time and with a specific action, such as uploading an object2. Users can generate a presigned URL programmatically using the AWS SDKs or AWS CLI. By using a presigned URL, users can reduce coupling within the application and improve website performance, as they do not need to send the images to the web server first.

AWS Lambda is a serverless compute service that runs code in response to events and automatically manages the underlying compute resources3. Users can configure S3 Event Notifications to invoke an AWS Lambda function when an image is uploaded. S3 Event Notifications is a feature that allows users to receive notifications when certain events happen in an S3 bucket, such as object creation or deletion. Users can configure S3 Event Notifications to invoke a Lambda function that resizes the image and stores it back in the same or a different S3 bucket. This way, users can offload the image resizing task from the web server to Lambda.

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

https://docs.aws.amazon.com/systems-manager/latest/userguide/setup-launch-managed-instance.html

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.

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.

To ensure that the Lambda function ingests all data in the future despite occasional network connectivity issues, the following actions should be taken:

• Create an Amazon Simple Queue Service (SQS) queue and subscribe it to the SNS topic. This allows for decoupling of the notification and processing, so that even if the processing Lambda function fails, the message remains in the queue for further processing later.
• Modify the Lambda function to read from the SQS queue instead of directly from SNS. This decoupling allows for retries and fault tolerance and ensures that all messages are processed by the Lambda function.

Amazon S3 is a highly scalable and durable object storage service that can store and retrieve any amount of data from anywhere on the web1. Users can configure the application to upload images directly from each user’s browser to Amazon S3 through the use of a presigned URL. A presigned URL is a URL that gives access to an object in an S3 bucket for a limited time and with a specific action, such as uploading an object2. Users can generate a presigned URL programmatically using the AWS SDKs or AWS CLI. By using a presigned URL, users can reduce coupling within the application and improve website performance, as they do not need to send the images to the web server first.

AWS Lambda is a serverless compute service that runs code in response to events and automatically manages the underlying compute resources3. Users can configure S3 Event Notifications to invoke an AWS Lambda function when an image is uploaded. S3 Event Notifications is a feature that allows users to receive notifications when certain events happen in an S3 bucket, such as object creation or deletion. Users can configure S3 Event Notifications to invoke a Lambda function that resizes the image and stores it back in the same or a different S3 bucket. This way, users can offload the image resizing task from the web server to Lambda.

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

"The Object Lock legal hold operation enables you to place a legal hold on an object version. Like setting a retention period, a legal hold prevents an object version from being overwritten or deleted. However, a legal hold doesn't have an associated retention period and remains in effect until removed." https://docs.aws.amazon.com/AmazonS3/latest/userguide/batch-ops-legal-hold.html

The destination of your Kinesis Data Firehose delivery stream. Kinesis Data Firehose can send data records to various destinations, including Amazon Simple Storage Service (Amazon S3), Amazon Redshift, Amazon OpenSearch Service, and any HTTP endpoint that is owned by you or any of your third-party service providers. The following are the supported destinations:

* Amazon OpenSearch Service

* Amazon S3

* Datadog

* Dynatrace

* Honeycomb

* HTTP Endpoint

* Logic Monitor

* MongoDB Cloud

* New Relic

* Splunk

* Sumo Logic

https://docs.aws.amazon.com/firehose/latest/dev/create-name.html

https://aws.amazon.com/kinesis/data-streams/

Amazon Kinesis Data Streams (KDS) is a massively scalable and durable real-time data streaming service. KDS can continuously capture gigabytes of data per second from hundreds of thousands of sources such as website clickstreams, database event streams, financial transactions, social media feeds, IT logs, and location-tracking events.

To reduce the cost of running the tests without reducing the compute and memory attributes of the Amazon RDS for MySQL DB instance, the development team can stop the instance when tests are completed and restart it when required. Stopping the DB instance when not in use can help save costs because customers are only charged for storage while the DB instance is stopped. During this time, automated backups and automated DB instance maintenance are suspended. When the instance is restarted, it retains the same configurations, security groups, and DB parameter groups as when it was stopped.

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

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

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://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_MySQL.Replication.ReadReplicas.html

https://docs.aws.amazon.com/eventbridge/latest/userguide/resource-based-policies-eventbridge.html#l ambda-permissions

using AWS ECS on AWS Fargate since they requirements are for scalability and availability without having to provision and manage the underlying infrastructure to run the containerized workload. https://docs.aws.amazon.com/AmazonECS/latest/userguide/what-is-fargate.html

To provide single sign-on (SSO) across all the company's accounts while continuing to manage users and groups in its on-premises self-managed Microsoft Active Directory, the solution is to enable AWS Single Sign-On (SSO) from the AWS SSO console and create a one-way forest trust or a one-way domain trust to connect the company's self-managed Microsoft Active Directory with AWS SSO by using AWS Directory Service for Microsoft Active Directory. This solution is described in the AWS documentation

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://docs.aws.amazon.com/AmazonS3/latest/userguide/privatelink-interface-endpoints.html#types-of-vpc-endpoints-for-s3

https://docs.aws.amazon.com/vpc/latest/userguide/vpc-endpoints-s3.html

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

https://aws.amazon.com/blogs/security/how-to-replicate-secrets-aws-secrets-m anager-multiple-regions/

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

https://docs.aws.amazon.com/systems-manager/latest/userguide/about-windows-app-patching.html

https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lock-overview.html

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."

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/solutions/implementations/aws-streaming-data-solution-for-amazon-kinesis/

https://aws.amazon.com/kinesis/data- firehose/features/?nc=sn&loc=2#:~:text=into%20Amazon%20S3%2C%20Amazon%20Redshift%2C%20Amazon%20OpenSearch%20Service%2C%20Kinesis,Delivery%20streams

To meet the requirements of detecting and alerting the administrators when PII is shared and automating remediation with the least development effort, the best approach would be to use Amazon S3 bucket as a secure transfer point and scan the objects in the bucket with Amazon Macie. Amazon Macie is a fully managed data security and data privacy service that uses machine learning and pattern matching to discover and protect sensitive data stored in Amazon S3. It can be used to classify sensitive data, monitor access to sensitive data, and automate remediation actions.

In this scenario, after uploading the files to the Amazon S3 bucket, the objects can be scanned for PII by Amazon Macie, and if it detects any PII, it can trigger an Amazon Simple Notification Service (SNS) notification to alert the administrators to remove the objects containing PII. This approach requires the least development effort, as Amazon Macie already has pre-built data classification rules that can detect PII in various formats.

Hence, option B is the correct answer.

References:

• Amazon Macie User Guide: https://docs.aws.amazon.com/macie/latest/userguide/what-is-macie.html
• AWS Well-Architected Framework - Security Pillar: https://docs.aws.amazon.com/wellarchitected/latest/security-pillar/welcome.html

https://aws.amazon.com/cn/blogs/security/how-to-connect-to-aws-secre ts-manager-service-within-a-virtual-private-cloud/

https://aws.amazon.com/blogs/security/rotate-amazon-rds-database-creden tials-automatically-with-aws-secrets-manager/

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..

Static content can be cached at Cloud front Edge locations from S3 and dynamic content EC2 behind the ALB whose performance can be improved by Global Accelerator whose one endpoint is ALB and other Cloud front. So with regards to custom domain name endpoint is web application is R53 alias records for the custom domain point to web application https://aws.amazon.com/blogs/networking-and-content-d elivery/improving-availability-and-performance-for-application-load-balancers-using-one-click-integration-with-aws-global-accelerator/

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

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://docs.aws.amazon.com/filegateway/latest/filefsxw/what-is-file-fsxw.html

To meet the requirements of the company to have access to both AWS and on-premises file storage with minimum latency, a hybrid cloud architecture can be used. One solution is to deploy and configure Amazon FSx for Windows File Server on AWS, which provides fully managed Windows file servers. The on-premises file data can be moved to the FSx File Gateway, which can act as a bridge between on-premises and AWS file storage. The cloud workloads can be configured to use FSx for Windows File Server on AWS, while the on-premises workloads can be configured to use the FSx File Gateway. This solution minimizes operational overhead and requires no significant changes to the existing file access patterns. The connectivity between on-premises and AWS can be established using an AWS Site-to-Site VPN connection.

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

"Typically, you configure buckets to be Requester Pays buckets when you want to share data but not incur charges associated with others accessing the data. For example, you might use Requester Pays buckets when making available large datasets, such as zip code directories, reference data, geospatial information, or web crawling data." https://docs.aws.amazon.com/Am azonS3/latest/userguide/RequesterPaysBuckets.html

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/sqs/features/

By routing incoming requests to Amazon SQS, the company can decouple the job requests from the processing instances. This allows them to scale the number of instances based on the size of the queue, providing more resources when needed. Additionally, using an Auto Scaling group based on the queue size will automatically scale the number of instances up or down depending on the workload. Updating the software to read from the queue will allow it to process the job requests in a more efficient manner, improving the performance of the system.

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

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.

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://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ec2-capacity-reservations.html

Reserve instances: You will have to pay for the whole term (1 year or 3years) which is not cost effective

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

AWS Organizations is a service that helps users centrally manage and govern multiple AWS accounts. It allows users to create organizational units (OUs) to group accounts based on business needs or other criteria. It also allows users to define and attach service control policies (SCPs) to OUs or accounts to restrict the actions that can be performed by the accounts1. By using AWS Organizations, the solution can centrally restrict the creation of AWS resources in the development accounts.

A. Develop AWS Systems Manager templates that use an approved EC2 creation process. Use the approved Systems Manager templates to provision EC2 instances. This solution will not meet the requirement of the least development effort, as it involves developing and maintaining custom templates for EC2 creation, and relying on the staff to use the approved templates instead of enforcing a restriction2.

C. Configure an Amazon EventBridge rule that invokes an AWS Lambda function when an EC2 instance is created. Stop disallowed EC2 instance types. This solution will not meet the requirement of the least development effort, as it involves writing custom code for Lambda functions, and handling events and errors for EC2 creation3.

D. Set up AWS Service Catalog products for the staff to create the allowed EC2 instance types En-sure that staff can deploy EC2 instances only by using the Service Catalog products. This solution will not meet the requirement of the least development effort, as it involves setting up and managing Service Catalog products for EC2 creation, and ensuring that staff can only use Service Catalog products instead of enforcing a restriction.

Reference URL: https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_scps.html

https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/vpc-endpoints-dynamodb.html

https://aws.amazon.com/about-aws/whats-new/2019/09/amazon-eks-adds-support-to-assign-iam-permissions-to-kubernetes-service-accounts/

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

https://aws.amazon.com/blogs/compute/microservice-delivery-with-amazon-ecs-and-application-load-balancers/

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.

AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. You can use Lambda to create and test microservices that are written in Python or other supported languages. Lambda scales automatically to handle the number of requests per second. You only pay for the compute time you consume. Lambda also integrates with other AWS services, such as Amazon API Gateway, Amazon S3, Amazon DynamoDB, and Amazon SQS, to enable event-driven architectures. Lambda has minimal infrastructure and operational overhead, as you do not need to manage servers, operating systems, patches, or scaling policies.

The other options are not serverless solutions and require more infrastructure and operational support. They also do not scale automatically to handle the number of requests per second. A Spot Fleet is a collection of EC2 instances that run on spare capacity at low prices. However, Spot Instances can be interrupted by AWS at any time, which can affect the availability and performance of your microservice. AWS Elastic Beanstalk is a service that automates the deployment and management of web applications on EC2 instances. However, you still need to provision, configure, and monitor the underlying EC2 instances and load balancers. Amazon EKS is a service that runs Kubernetes on AWS. However, you still need to create, configure, and manage the EC2 instances that form the Kubernetes cluster and nodes. You also need to install and update the Kubernetes software and tools.

References:

• What is AWS Lambda?
• Building Lambda functions with Python
• Create a layer for a Lambda Python function
• AWS Lambda – Function in Python
• How do I call my AWS Lambda function from a local python script?

To use an SSL/TLS certificate that is issued by an external CA, the certificate must be imported to AWS Certificate Manager (ACM). ACM can send a notification when the certificate is nearing expiration, but it cannot automatically rotate the certificate. Therefore, the certificate must be rotated manually by importing a new certificate and applying it to the ALB.

References:

• Importing Certificates into AWS Certificate Manager
• Renewing and Rotating Imported Certificates
• Using an ACM Certificate with an Application Load Balancer

This answer is correct because it provides redundancy for the VPN connection between the Management VPC and the data center. If one customer gateway device or one VPN tunnel becomes unavailable, the traffic can still flow over the second customer gateway device and the second VPN tunnel. This way, the single point of failure in the VPN connection is mitigated.

References:

• https://docs.aws.amazon.com/vpn/latest/s2svpn/vpn-redundant-connection.html
• https://www.trendmicro.com/cloudoneconformity/knowledge-base/aws/VPC/vpn-tunnel-redundancy.html

Client-side encryption is a method of encrypting data before uploading it to Amazon S3. It allows users to manage the encryption process, encryption keys, and related tools1. By using client-side encryption, the solution can ensure that the data is encrypted at rest and in transit, as Amazon S3 will not have access to the encryption keys or the unencrypted data2.

To migrate the DNS hosting service to a more resilient managed DNS service on AWS, the company should use Amazon Route 53, which is a highly available and scalable cloud DNS web service. Route 53 can host public DNS records for the company’s domain name and provide reliable and secure DNS resolution. To rapidly migrate the DNS hosting service, the company should create a public hosted zone for the domain name in Route 53, which is a container for the domain’s DNS records. Then, the company should import the zone file containing the domain records hosted by the previous provider, which is a text file that defines the DNS records for the domain. This way, the company can quickly transfer the existing DNS records to Route 53 without manually creating them. After importing the zone file, the company should update the domain registrar to use the name servers that Route 53 assigns to the hosted zone. This will ensure that DNS queries for the domain name are routed to Route 53 and resolved by the imported records.

This approach allows users to upload files directly to S3 without passing through the application servers, reducing the load on the application and improving scalability. It leverages the client-side capabilities to handle the file uploads and offloads the processing to S3.

The most suitable solution for the company’s compliance policy is to enable the restricted-ssh AWS Config managed rule and generate an Amazon Simple Notification Service (Amazon SNS) notification when a noncompliant rule is created. This solution has the least operational overhead because it uses a predefined rule that is already available in AWS Config, which is a service that enables users to assess, audit, and evaluate the configurations of their AWS resources. The restricted-ssh rule checks whether security groups that are in use have inbound rules that allow SSH from 0.0.0.0/0 addresses, and reports them as noncompliant1. Users can configure the rule to send notifications to an Amazon SNS topic when a noncompliant change occurs, and subscribe to the topic to receive alerts via email, SMS, or other methods2.

The other options are not correct because they either have more operational overhead or do not meet the requirements. Writing an AWS Lambda script that monitors security groups for SSH being open to 0.0.0.0/0 addresses and creates a notification every time it finds one is not correct because it requires custom code development and maintenance, which adds complexity and cost to the solution. Creating an IAM role with permissions to globally open security groups and network ACLs, and creating an Amazon SNS topic to generate a notification every time the role is assumed by a user is not correct because it does not prevent or detect the creation of noncompliant rules by other users or roles, and it does not address the existing rules that may violate the policy. Configuring a service control policy (SCP) that prevents non-administrative users from creating or editing security groups, and creating a notification in the ticketing system when a user requests a rule that needs administrator permissions is not correct because it does not provide an automated solution for the policy enforcement and notification, and it may limit the flexibility and productivity of the users.

References:

• restricted-ssh - AWS Config
• Getting Notifications When Your Resources Change - AWS Config

The solution that meets the requirements with the least operational overhead is to migrate the web tier to Amazon EC2 instances in public subnets, migrate the application tier to EC2 instances in private subnets, and migrate the database tier to Amazon RDS for MySQL in private subnets. This solution allows the company to migrate its three-tier application to AWS by making minimal changes to the architecture, as it preserves the same web, application, and database tiers and uses the same MySQL database engine. The solution also provides a database solution that can restore data to a specific point in time, as Amazon RDS for MySQL supports automated backups and point-in-time recovery. This solution also reduces the operational overhead by using managed services such as Amazon EC2 and Amazon RDS, which handle tasks such as provisioning, patching, scaling, and monitoring.

The other solutions do not meet the requirements as well as the first one because they either involve more changes to the architecture, do not provide point-in-time recovery, or do not follow best practices for security and availability. Migrating the database tier to Amazon Aurora MySQL would require changing the database engine and potentially modifying the application code to ensure compatibility. Migrating the web tier and the application tier to public subnets would expose them to more security risks and reduce their availability in case of a subnet failure. Migrating the database tier to public subnets would also compromise its security and performance. References:

• Migrate Your Application Database to Amazon RDS
• Amazon RDS for MySQL
• Amazon Aurora MySQL
• Amazon VPC

This solution meets the requirements because it allows the company to use a single Direct Connect connection to connect to multiple VPCs in different Regions using a Direct Connect gateway. A Direct Connect gateway is a globally available resource that enables you to connect your on-premises network to VPCs in any AWS Region, except the AWS China Regions. You can associate a Direct Connect gateway with a transit gateway or a virtual private gateway in each Region. By routing traffic from the virtual private gateways of the VPCs to the Direct Connect gateway, you can enable inter-Region and on-premises connectivity for your VPCs. This solution is scalable because you can add more VPCs in different Regions to the Direct Connect gateway without creating additional connections. This solution also reduces operational overhead because you do not need to manage multiple VPN appliances, VPN connections, or VPC peering connections.

References:

• Direct Connect gateways
• Inter-Region VPC peering

This solution meets the requirements most cost-effectively because it leverages the serverless and event-driven capabilities of AWS Lambda and Amazon EventBridge. AWS Lambda allows you to run code without provisioning or managing servers, and you pay only for the compute time you consume. Amazon EventBridge is a serverless event bus service that lets you connect your applications with data from various sources and routes that data to targets such as AWS Lambda. By using Amazon EventBridge, you can create a rule that triggers a Lambda function to run the program when reports are requested, and you can also schedule the rule to run during the last week of each month. This way, you can generate reports in the least amount of time and pay only for the resources you use.

References:

• AWS Lambda
• Amazon EventBridge

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.

it allows the company to migrate the on-premises database to a managed AWS service that supports auto scaling capabilities and has the least administrative overhead. Amazon Aurora Serverless v2 is a configuration of Amazon Aurora that automatically scales compute capacity based on workload demand. It can scale from hundreds to hundreds of thousands of transactions in a fraction of a second. Amazon Aurora Serverless v2 also supports MySQL-compatible databases and AWS Direct Connect connectivity. References:

• Amazon Aurora Serverless v2
• Connecting to an Amazon Aurora DB Cluster

To meet the requirements of the use case in a cost-effective way, the following steps are recommended:

• Deploy an AWS Storage Gateway on premises in Amazon S3 File Gateway mode. This will allow the company to write the .csv files generated by the devices to an SMB file share, which will be stored as objects in Amazon S3 buckets. AWS Storage Gateway is a hybrid cloud storage service that integrates on-premises environments with AWS storage. Amazon S3 File Gateway mode provides a seamless way to connect to Amazon S3 and access a virtually unlimited amount of cloud storage1.
• Set up an AWS Glue crawler to create a table based on the data that is in Amazon S3. This will enable the company to use standard SQL to query the data stored in Amazon S3 buckets. AWS Glue is a serverless data integration service that simplifies data preparation and analysis. AWS Glue crawlers can automatically discover and classify data from various sources, and create metadata tables in the AWS Glue Data Catalog2. The Data Catalog is a central repository that stores information about data sources and how to access them3.
• Set up Amazon Athena to query the data that is in Amazon S3. This will provide the company analysts with a serverless and interactive query service that can analyze data directly in Amazon S3 using standard SQL. Amazon Athena is integrated with the AWS Glue Data Catalog, so users can easily point Athena at the data source tables defined by the crawlers. Amazon Athena charges only for the queries that are run, and offers a pay-per-query pricing model, which makes it a cost-effective option for periodic queries4.

The other options are not correct because they are either not cost-effective or not suitable for the use case. Deploying an AWS Storage Gateway on premises in Amazon FSx File Gateway mode is not correct because this mode provides low-latency access to fully managed Windows file shares in AWS, which is not required for the use case. Setting up an Amazon EMR cluster with EMR File System (EMRFS) to query the data that is in Amazon S3 is not correct because this option involves setting up and managing a cluster of EC2 instances, which adds complexity and cost to the solution. Setting up an Amazon Redshift cluster to query the data that is in Amazon S3 is not correct because this option also involves provisioning and managing a cluster of nodes, which adds overhead and cost to the solution.

References:

• What is AWS Storage Gateway?
• What is AWS Glue?
• AWS Glue Data Catalog
• What is Amazon Athena?

https://aws.amazon.com/rds/aurora/serverless/

The number of instances in your Auto Scaling group can be driven by how long it takes to process a message and the acceptable amount of latency (queue delay). The solution is to use a backlog per instance metric with the target value being the acceptable backlog per instance to maintain.

To back up EC2 instances and RDS DB instances in a separate Region with the least operational overhead, AWS Backup is a simple and cost-effective solution. AWS Backup can copy EC2 backups and RDS backups to another Region automatically and securely. AWS Backup also supports backup policies, retention rules, and monitoring features.

References:

• What Is AWS Backup?
• Cross-Region Backup

An Application Load Balancer (ALB) is a type of Elastic Load Balancer (ELB) that distributes incoming application traffic across multiple targets, such as EC2 instances, containers, Lambda functions, and IP addresses, in multiple Availability Zones1. An ALB can be internet-facing or internal. An internet-facing ALB has a public DNS name that clients can use to send requests over the internet1. An internal ALB has a private DNS name that clients can use to send requests within a VPC1. This solution meets the requirements of the question because:

• It allows external internet traffic to connect to the web server on ports 80 and 443, as the ALB listens for requests on these ports and forwards them to the EC2 instance in the private subnet1.
• It does not violate the corporate security mandate, as the EC2 instance is launched in a private subnet and does not have a public IP address or a route to an internet gateway2.
• It reduces the operational overhead, as the ALB is a fully managed service that handles the tasks of load balancing, health checking, scaling, and security1.

Amazon S3 Glacier is a storage class that provides secure, durable, and extremely low-cost storage for data archiving and long-term backup. It is designed for data that is rarely accessed and for which retrieval times of several hours are suitable1. By storing the video archives in Amazon S3 Glacier, the solution can minimize costs.

Amazon S3 Glacier offers three options for data retrieval: Expedited, Standard, and Bulk. Expedited retrievals typically return data in 1–5 minutes and are suitable for Active Archive use cases. Standard retrievals typically complete within 3–5 hours and are suitable for less urgent needs. Bulk retrievals typically complete within 5–12 hours and are the lowest-cost retrieval option2. By using Expedited retrievals, the solution can meet the requirement of restoring the files in a maximum of five minutes.

B. Store the video archives in Amazon S3 Glacier and use Standard retrievals. This solution will not meet the requirement of restoring the files in a maximum of five minutes, as Standard retrievals typically complete within 3–5 hours.

C. Store the video archives in Amazon S3 Standard-Infrequent Access (S3 Standard-IA). This solution will not meet the requirement of minimizing costs, as S3 Standard-IA is a storage class that provides low-cost storage for data that is accessed less frequently but requires rapid access when needed. It has a higher storage cost than S3 Glacier.

D. Store the video archives in Amazon S3 One Zone-Infrequent Access (S3 One Zone-IA). This solution will not meet the requirement of minimizing costs, as S3 One Zone-IA is a storage class that provides low-cost storage for data that is accessed less frequently but requires rapid access when needed. It has a higher storage cost than S3 Glacier.

Reference URL: https://aws.amazon.com/s3/glacier/

By having customers create an IAM role with the necessary permissions in their own accounts, the company can use AWS Identity and Access Management (IAM) to establish cross-account access. The trust policy allows the company's AWS account to assume the customer's IAM role temporarily, granting access to the specified resources (EC2 instances and CloudWatch metrics) within the customer's account. This approach follows the principle of least privilege, as the company only requests the necessary permissions and does not require long-term access keys or user credentials from the customers.

AWS Organizations is a service that helps users centrally manage and govern multiple AWS accounts. It allows users to create organizational units (OUs) to group accounts based on business needs or other criteria. It also allows users to define and attach service control policies (SCPs) to OUs or accounts to restrict the actions that can be performed by the accounts1. By creating a new organization in AWS Organizations with all features turned on, the solution can consolidate and manage the new AWS accounts for different business units.

AWS IAM Identity Center (formerly known as AWS Single Sign-On) is a service that provides single sign-on access for all of your AWS accounts and cloud applications. It connects with Microsoft Active Directory through AWS Directory Service to allow users in that directory to sign in to a personalized AWS access portal using their existing Active Directory user names and passwords. From the AWS access portal, users have access to all the AWS accounts and cloud applications that they have permissions for2. By setting up IAM Identity Center in the organization and integrating it with the company’s corporate directory service, the solution can authenticate access to these AWS accounts using a centralized corporate directory service.

B. Set up an Amazon Cognito identity pool. Configure AWS 1AM Identity Center (AWS Single Sign-On) to accept Amazon Cognito authentication. This solution will not meet the requirement of authenticating access to these AWS accounts by using a centralized corporate directory service, as Amazon Cognito is a service that provides user sign-up, sign-in, and access control for web and mobile applications, not for corporate directory services3.

C. Configure a service control policy (SCP) to manage the AWS accounts. Add AWS 1AM Identi-ty Center (AWS Single Sign-On) to AWS Directory Service. This solution will not work, as SCPs are used to restrict the actions that can be performed by the accounts in an organization, not to manage the accounts themselves1. Also, IAM Identity Center cannot be added to AWS Directory Service, as it is a separate service that connects with Microsoft Active Directory through AWS Directory Service2.

D. Create a new organization in AWS Organizations. Configure the organization’s authentication mechanism to use AWS Directory Service directly. This solution will not work, as AWS Organizations does not have an authentication mechanism that can use AWS Directory Service directly. AWS Organizations relies on IAM Identity Center to provide single sign-on access for the accounts in an organization.

Reference URL: https://docs.aws.amazon.com/organizations/latest/userguide/orgs_integrate_services.html

This answer is the most secure and recommended option for securing the root user of a new AWS account. The root user is the identity that has complete access to all AWS services and resources in the account. It is accessed by signing in with the email address and password that were used to create the account. To protect the root user credentials from unauthorized use, AWS advises the following best practices:

• Create IAM users for daily administrative tasks. IAM users are identities that you create in your account that have specific permissions to access AWS resources. You can create individual IAM users for yourself and for others who need access to your account. You can also assign IAM users to IAM groups that have a set of policies that grant permissions to perform common tasks. By using IAM users instead of the root user, you can follow the principle of least privilege and reduce the risk of compromising your account.
• Enable multi-factor authentication (MFA) on the root user. MFA is a security feature that requires users to prove their identity by providing two pieces of information: their password and a code from a device that only they have access to. By enabling MFA on the root user, you can add an extra layer of protection to your account and prevent unauthorized access even if your password is compromised.
• Limit the tasks you perform with the root user account. You should use the root user only for tasks that require root user credentials, such as changing your account settings, closing your account, or managing consolidated billing. For a complete list of tasks that require root user credentials, see Tasks that require root user credentials. For all other tasks, you should use IAM users or roles that have the appropriate permissions.

References:

• AWS account root user
• Root user best practices for your AWS account
• Tasks that require root user credentials

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

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/

Amazon Aurora Serverless v2 is a cost-effective solution that can automatically scale the database capacity up and down based on the application’s needs. It can handle unpredictable traffic spikes without requiring any provisioning or management of database instances. It is compatible with PostgreSQL and offers high performance, availability, and durability1. References: 1: AWS Ramp-Up Guide: Architect2, page 312: AWS Certified Solutions Architect - Associate exam guide3, page 9.

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

This solution meets the requirements because it allows the company to track and manage its cloud spending by using cost allocation tags to assign costs to different departments, creating usage budgets to set spending limits, and adding alert thresholds to receive notifications when the spending reaches a certain percentage of the budget. This way, the company can monitor its experimental workloads and avoid overspending on the cloud.

References:

• Using Cost Allocation Tags
• Creating an AWS Budget
• Creating an Alert for an AWS Budget

This option is the most secure and simple way to encrypt the secrets that are stored in Amazon EKS. AWS Key Management Service (AWS KMS) is a service that allows you to create and manage encryption keys that can be used to encrypt your data. Amazon EKS KMS secrets encryption is a feature that enables you to use a KMS key to encrypt the secrets that are stored in the Kubernetes etcd key-value store. This provides an additional layer of protection for your sensitive data, such as passwords, tokens, and keys. You can create a new KMS key or use an existing one, and then enable the Amazon EKS KMS secrets encryption on the Amazon EKS cluster. You can also use IAM policies to control who can access or use the KMS key.

Option A is not correct because using AWS Secrets Manager to manage, rotate, and store all secrets in Amazon EKS is not necessary or efficient. AWS Secrets Manager is a service that helps you securely store, retrieve, and rotate your secrets, such as database credentials, API keys, and passwords. You can use it to manage secrets that are used by your applications or services outside of Amazon EKS, but it is not designed to encrypt the secrets that are stored in the Kubernetes etcd key-value store. Moreover, using AWS Secrets Manager would incur additional costs and complexity, and it would not leverage the native Kubernetes secrets management capabilities.

Option C is not correct because using the Amazon EBS Container Storage Interface (CSI) driver as an add-on does not encrypt the secrets that are stored in Amazon EKS. The Amazon EBS CSI driver is a plugin that allows you to use Amazon EBS volumes as persistent storage for your Kubernetes pods. It is useful for providing durable and scalable storage for your applications, but it does not affect the encryption of the secrets that are stored in the Kubernetes etcd key-value store. Moreover, using the Amazon EBS CSI driver would require additional configuration and resources, and it would not provide the same level of security as using a KMS key.

Option D is not correct because creating a new AWS KMS key with the alias aws/ebs and enabling default Amazon EBS volume encryption for the account does not encrypt the secrets that are stored in Amazon EKS. The alias aws/ebs is a reserved alias that is used by AWS to create a default KMS key for your account. This key is used to encrypt the Amazon EBS volumes that are created in your account, unless you specify a different KMS key. Enabling default Amazon EBS volume encryption for the account is a setting that ensures that all new Amazon EBS volumes are encrypted by default. However, these features do not affect the encryption of the secrets that are stored in the Kubernetes etcd key-value store. Moreover, using the default KMS key or the default encryption setting would not provide the same level of control and security as using a custom KMS key and enabling the Amazon EKS KMS secrets encryption feature. References:

• Encrypting secrets used in Amazon EKS
• What Is AWS Key Management Service?
• What Is AWS Secrets Manager?
• Amazon EBS CSI driver
• Encryption at rest

AWS Backup is a fully managed service that enables users to centralize and automate the backup of data across AWS services. It can create and manage backup plans that specify the frequency and retention period of backups. It can also assign backup resources to backup vaults, which are containers that store backup data1. By using AWS Backup, the solution can ensure that the RDS backups are consistent, restorable, and retained for a minimum period of 2 years.

B. Configure a backup window for the RDS DB instances for daily snapshots. Assign a snapshot retention policy of 2 years to each RDS DB instance. Use Amazon Data Lifecycle Manager (Amazon DLM) to schedule snapshot deletions. This solution will not meet the requirement of ensuring that the backups are consistent and restorable, as Amazon DLM is not compatible with RDS snapshots and cannot be used to schedule snapshot deletions2.

C. Configure database transaction logs to be automatically backed up to Amazon CloudWatch Logs with an expiration period of 2 years. This solution will not meet the requirement of ensuring that the backups are consistent and restorable, as database transaction logs are not sufficient to restore a database to a point in time. They only capture the changes made to the database, not the full state of the database3.

D. Configure an AWS Database Migration Service (AWS DMS) replication task. Deploy a replication instance, and configure a change data capture (CDC) task to stream database changes to Amazon S3 as the target. Configure S3 Lifecycle policies to delete the snapshots after 2 years. This solution will not meet the requirement of ensuring that the backups are consistent and restorable, as AWS DMS is a service that helps users migrate databases to AWS, not back up databases. It also requires additional resources and configuration, such as replication instances and CDC tasks.

Reference URL: https://docs.aws.amazon.com/aws-backup/latest/devguide/whatisbackup.html

These options are the best solutions because they allow the company to run the application with Docker containers in the AWS Cloud using a managed service that scales automatically and does not require any infrastructure to manage. By using AWS Fargate, the company can launch and run containers without having to provision, configure, or scale clusters of EC2 instances. Fargate allocates the right amount of compute resources for each container and scales them up or down as needed. By using Amazon ECS or Amazon EKS, the company can choose the container orchestration platform that suits its needs. Amazon ECS is a fully managed service that integrates with other AWS services and simplifies the deployment and management of containers. Amazon EKS is a managed service that runs Kubernetes on AWS and provides compatibility with existing Kubernetes tools and plugins.

C. Provision an Amazon API Gateway API Connect the API to AWS Lambda to run the containers. This option is not feasible because AWS Lambda does not support running Docker containers directly. Lambda functions are executed in a sandboxed environment that is isolated from other functions and resources. To run Docker containers on Lambda, the company would need to use a custom runtime or a wrapper library that emulates the Docker API, which can introduce additional complexity and overhead.

D. Use Amazon Elastic Container Service (Amazon ECS) with Amazon EC2 worker nodes. This option is not optimal because it requires the company to manage the EC2 instances that host the containers. The company would need to provision, configure, scale, patch, and monitor the EC2 instances, which can increase the operational overhead and infrastructure costs.

E. Use Amazon Elastic Kubernetes Service (Amazon EKS) with Amazon EC2 worker nodes. This option is not ideal because it requires the company to manage the EC2 instances that host the containers. The company would need to provision, configure, scale, patch, and monitor the EC2 instances, which can increase the operational overhead and infrastructure costs.

References:

• 1 AWS Fargate - Amazon Web Services
• 2 Amazon Elastic Container Service - Amazon Web Services
• 3 Amazon Elastic Kubernetes Service - Amazon Web Services
• 4 AWS Lambda FAQs - Amazon Web Services

B. Use the Trusted Advisor recommendations from the consolidated billing account to see all RDS instance checks at the same time.

The consolidated billing account has access to all the other AWS accounts that use consolidated billing. Using the Trusted Advisor recommendations from the consolidated billing account will allow the finance team to see all RDS instance checks for all accounts at the same time.

C. Review the Trusted Advisor check for Amazon RDS Reserved Instance Optimization.

The Trusted Advisor check for Amazon RDS Reserved Instance Optimization provides recommendations for purchasing reserved instances to reduce RDS costs. By reviewing this check, the finance team can identify which RDS instances can be converted to reserved instances to save costs.

This solution meets the following requirements:

• It is operationally efficient, as it only requires one activation of the cost allocation tag and one creation of the cost report from the management account, which has access to all the member accounts’ data and billing preferences.
• It is consistent, as it uses the AWS-defined cost allocation tag named department, which is automatically applied to resources when the company creates tags using the tagging policy enforced by AWS Organizations. This ensures that the tag name and value are the same across all the resources and accounts, and avoids any discrepancies or errors that might arise from user-defined tags.
• It is informative, as it creates one cost report in Cost Explorer grouping by the tag name, and filters by EC2. This allows the accounting team to see the breakdown of EC2 consumption and costs by department, regardless of the AWS account. The team can also use other features of Cost Explorer, such as charts, filters, and forecasts, to analyze and optimize the spending.

References:

• Using AWS cost allocation tags - AWS Billing
• User-defined cost allocation tags - AWS Billing
• Cost Tagging and Reporting with AWS Organizations

This answer is correct because it meets the requirements of hosting a scalable web application that can handle large data transfers from different geographic regions. Amazon EC2 provides scalable compute capacity for hosting web applications. Auto Scaling can automatically adjust the number of EC2 instances based on the demand and traffic patterns. Amazon CloudFront is a content delivery network (CDN) that can cache static and dynamic content at edge locations closer to the users, reducing latency and improving performance. CloudFront can also use S3 Transfer Acceleration to speed up the transfers between S3 buckets and CloudFront edge locations.

References:

• https://docs.aws.amazon.com/autoscaling/ec2/userguide/what-is-amazon-ec2-auto-scaling.html
• https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/Introduction.html
• https://aws.amazon.com/s3/transfer-acceleration/

https://docs.aws .amazon.com/awscloudtrail/latest/userguide/best-practices-security.html#:~:text=The%20CloudTrail%20trail,time%20has%20passed.

Joining the FSx for Windows File Server file system to the on-premises Active Directory will allow the company to use the existing Active Directory groups to restrict access to the file shares, folders, and files after the move to AWS. This option allows the company to continue using their existing access controls and management structure, making the transition to AWS more seamless.

This option is the most cost-effective solution because it leverages the Spot Instances, which are unused EC2 instances that are available at up to 90% discount compared to On-Demand prices. Spot Instances can be interrupted by AWS when the demand for On-Demand instances increases, but since the batch jobs are fault-tolerant and can be reprocessed by another instance, this is not a major issue. By using a launch template, the company can specify the configuration of the Spot Instances, such as the instance type, the operating system, and the user data. By using an Auto Scaling group, the company can automatically scale the number of Spot Instances based on the CPU usage, which reflects the load of the batch jobs. This way, the company can optimize the performance and the cost of the EC2 instances for the nightly batch jobs.

A. Purchase a 1-year Savings Plan for Amazon EC2 that covers the instance family of the Auto Scaling group that the batch job uses. This option is not optimal because it requires a commitment to a consistent amount of compute usage per hour for a one-year term, regardless of the instance type, size, region, or operating system. This can limit the flexibility and scalability of the Auto Scaling group and result in overpaying for unused compute capacity. Moreover, Savings Plans do not provide a capacity reservation, which means the company still needs to reserve capacity with On-Demand Capacity Reservations and pay lower prices with Savings Plans.

B. Purchase a 1-year Reserved Instance for the specific instance type and operating system of the instances in the Auto Scaling group that the batch job uses. This option is not ideal because it requires a commitment to a specific instance configuration for a one-year term, which can reduce the flexibility and scalability of the Auto Scaling group and result in overpaying for unused compute capacity. Moreover, Reserved Instances do not provide a capacity reservation, which means the company still needs to reserve capacity with On-Demand Capacity Reservations and pay lower prices with Reserved Instances.

D. Create a new launch template for the Auto Scaling group Increase the instance size Set a policy to scale out based on CPU usage. This option is not cost-effective because it does not take advantage of the lower prices of Spot Instances. Increasing the instance size can improve the performance of the batch jobs, but it can also increase the cost of the On-Demand instances. Moreover, scaling out based on CPU usage can result in launching more instances than needed, which can also increase the cost of the system.

References:

• 1 Spot Instances - Amazon Elastic Compute Cloud
• 2 Launch templates - Amazon Elastic Compute Cloud
• 3 Auto Scaling groups - Amazon EC2 Auto Scaling
• [4] Savings Plans - Amazon EC2 Reserved Instances and Other AWS Reservation Models

This option is the most cost-effective and simple way to enable SFTP access to the S3 data lake. AWS Transfer Family is a fully managed service that supports secure file transfers over SFTP, FTPS, and FTP protocols. You can create an SFTP-enabled server with a public endpoint and associate it with your S3 bucket. You can also use AWS Identity and Access Management (IAM) roles and policies to control access to your S3 data lake. The service scales automatically to handle any volume of file transfers and provides high availability and durability. You do not need to provision, manage, or patch any servers or load balancers.

Option B is not correct because Amazon S3 File Gateway is not an SFTP server. It is a hybrid cloud storage service that provides a local file system interface to S3. You can use it to store and retrieve files as objects in S3 using standard file protocols such as NFS and SMB. However, it does not support SFTP protocol, and it requires deploying a file gateway appliance on-premises or on EC2.

Option C is not cost-effective or scalable because it requires launching and managing an EC2 instance in a private subnet and setting up a VPN connection for the new partner. This would incur additional costs for the EC2 instance, the VPN connection, and the data transfer. It would also introduce complexity and security risks to the solution. Moreover, it would require running a cron job script on the EC2 instance to upload files to the S3 data lake, which is not efficient or reliable.

Option D is not cost-effective or scalable because it requires launching and managing multiple EC2 instances in a private subnet and placing a NLB in front of them. This would incur additional costs for the EC2 instances, the NLB, and the data transfer. It would also introduce complexity and security risks to the solution. Moreover, it would require running a cron job script on the EC2 instances to upload files to the S3 data lake, which is not efficient or reliable. References:

• What Is AWS Transfer Family?
• What Is Amazon S3 File Gateway?
• What Is Amazon EC2?
• [What Is Amazon Virtual Private Cloud?]
• [What Is a Network Load Balancer?]

The solution that will meet the requirement of ensuring that all data that is written to the EBS volumes is encrypted at rest is B. Create the EBS volumes as encrypted volumes and attach the encrypted EBS volumes to the EC2 instances. When you create an EBS volume, you can specify whether to encrypt the volume. If you choose to encrypt the volume, all data written to the volume is automatically encrypted at rest using AWS-managed keys. You can also use customer-managed keys (CMKs) stored in AWS KMS to encrypt and protect your EBS volumes. You can create encrypted EBS volumes and attach them to EC2 instances to ensure that all data written to the volumes is encrypted at rest.

To restrict inbound traffic from the ALB to the EC2 instances, the security group for the EC2 instances should only allow traffic that comes from the security group for the ALB. This way, the EC2 instances can only receive requests from the ALB and not from any other source inside or outside the private subnet.

References:

• Security Groups for Your Application Load Balancers
• Security Groups for Your VPC

AWS DataSync is a service that makes it easy to move large amounts of data between AWS storage services and on-premises storage systems. AWS DataSync can copy files from an S3 bucket to an EFS file system and another S3 bucket continuously, as well as overwrite only the files that have changed in the source. This solution will meet the requirements with the least operational overhead, as it does not require any code development or manual intervention.

References:

• 4 explains how to create AWS DataSync locations for different storage services.
• 5 describes how to create and configure AWS DataSync tasks for data transfer.
• 6 discusses the different transfer modes that AWS DataSync supports.

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

This answer is correct because it meets the requirements of accessing a shared file system that is highly durable, can recover data to another AWS Region, and can provide a mount target in each Availability Zone within a Region. Amazon FSx for NetApp ONTAP is a fully managed service that provides enterprise-grade data management and storage for your Windows and Linux applications. You can use Amazon FSx for NetApp ONTAP to create file systems that span multiple Availability Zones within an AWS Region, providing high availability and durability. You can also use AWS Backup to manage the replication of your file systems to another AWS Region, with a recovery point objective (RPO) of 8 hours or less. AWS Backup is a fully managed backup service that automates and centralizes backup of data over AWS services. You can use AWS Backup to create backup policies and monitor activity for your AWS resources in one place.

References:

• https://docs.aws.amazon.com/fsx/latest/ONTAPGuide/what-is.html
• https://docs.aws.amazon.com/aws-backup/latest/devguide/whatisbackup.html

The solution that will improve the performance of the data tier is to deploy an Amazon ElastiCache for Redis cluster in front of the existing DB instance and modify the game to use Redis. This solution will enable the game to store and retrieve the location data of the players in a fast and scalable way, as Redis is an in-memory data store that supports geospatial data types and commands. By using ElastiCache for Redis, the game can reduce the load on the RDS for PostgreSQL DB instance, which is not optimized for high-frequency updates and queries of location data. ElastiCache for Redis also supports replication, sharding, and auto scaling to handle the increasing user base of the game.

The other solutions are not as effective as the first one because they either do not improve the performance, do not support geospatial data, or do not leverage caching. Taking a snapshot of the existing DB instance and restoring it with Multi-AZ enabled will not improve the performance of the data tier, as it only provides high availability and durability, but not scalability or low latency. Migrating from Amazon RDS to Amazon OpenSearch Service with OpenSearch Dashboards will not improve the performance of the data tier, as OpenSearch Service is mainly designed for full-text search and analytics, not for real-time location tracking. OpenSearch Service also does not support geospatial data types and commands natively, unlike Redis. Deploying Amazon DynamoDB Accelerator (DAX) in front of the existing DB instance and modifying the game to use DAX will not improve the performance of the data tier, as DAX is only compatible with DynamoDB, not with RDS for PostgreSQL. DAX also does not support geospatial data types and commands.

References:

• Amazon ElastiCache for Redis
• Geospatial Data Support - Amazon ElastiCache for Redis
• Amazon RDS for PostgreSQL
• Amazon OpenSearch Service
• Amazon DynamoDB Accelerator (DAX)

Amazon SES is a cost-effective and scalable email service that enables businesses to send and receive email using their own email addresses and domains. Configuring the web instance to send email through Amazon SES is a simple and effective solution that can reduce the time spent resolving complex email delivery issues and minimize operational overhead.

To resolve the issue of slow page loads for a rapidly growing e-commerce website hosted on AWS, a solutions architect can take the following two actions:

1. Set up an Amazon CloudFront distribution

2. Create a read replica for the RDS DB instance

Configuring an Amazon Redshift cluster is not relevant to this issue since Redshift is a data warehousing service and is typically used for the analytical processing of large amounts of data.

Hosting the dynamic web content in Amazon S3 may not necessarily improve performance since S3 is an object storage service, not a web application server. While S3 can be used to host static web content, it may not be suitable for hosting dynamic web content since S3 doesn't support server-side scripting or processing.

Configuring a Multi-AZ deployment for the RDS DB instance will improve high availability but may not necessarily improve performance.

A NAT gateway is a type of network address translation (NAT) device that enables instances in a private subnet to connect to the internet or other AWS services, but prevents the internet from initiating connections with those instances1. A NAT gateway is a managed service that requires minimal operational maintenance and can handle up to 45 Gbps of bursty traffic1. A NAT gateway is suitable for scenarios where EC2 instances in private subnets need to communicate with a license server over the internet, such as the three-tier web application in the scenario1.

To meet the requirements of the scenario, the solutions architect should provision a NAT gateway in a public subnet. The solutions architect should also modify each private subnet’s route table with a default route that points to the NAT gateway1. This way, the EC2 instances that run in private subnets can access the license server over the internet through the NAT gateway.

This option is the most efficient because it uses a predictive scaling policy for the Auto Scaling group, which is a type of scaling policy that uses machine learning to predict capacity requirements based on historical data from CloudWatch1. It also configures the policy to scale based on forecast, which enables the Auto Scaling group to adjust its capacity in advance of traffic changes. It also sets the scaling metric to CPU utilization and the target value for the metric to 60%, which aligns with the baseline CPU utilization that is noted on each run. It also sets the instances to pre-launch 30 minutes before the jobs run, which ensures that enough capacity is provisioned before the weekly scripted batch jobs start. This solution meets the requirement of provisioning the capacity 30 minutes before the jobs run with the least operational overhead. Option A is less efficient because it uses a dynamic scaling policy for the Auto Scaling group, which is a type of scaling policy that adjusts your Auto Scaling group’s capacity in response to changing demand2. However, this does not provide a way to provision the capacity 30 minutes before the jobs run, as it only reacts to changing traffic. Option B is less efficient because it uses a scheduled scaling policy for the Auto Scaling group, which is a type of scaling policy that lets you scale your Auto Scaling group based on a schedule that you create3. However, this does not provide a way to scale based on forecast or CPU utilization, as it only scales based on predefined metrics and policies. Option D is less efficient because it uses an Amazon EventBridge event to invoke an AWS Lambda function when the CPU utilization metric value for the Auto Scaling group reaches 60%, which is a way to trigger serverless functions based on events. However, this does not provide a way to provision the capacity 30 minutes before the jobs run, as it only reacts to changing traffic.

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

This is the purpose of bookmarks: "AWS Glue tracks data that has already been processed during a previous run of an ETL job by persisting state information from the job run. This persisted state information is called a job bookmark. Job bookmarks help AWS Glue maintain state information and prevent the reprocessing of old data." https://docs.aws.amazon.com/glue/latest/dg/monitor-continuations.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.

it allows the company to create read replicas of its RDS database and reduce the load on the database tier. By creating read replicas, the company can offload read traffic from the primary database instance to one or more replicas. By configuring the reports to use the new read replicas, the company can improve performance and availability of its database tier. References:

• Working with Read Replicas
• Read Replicas for Amazon RDS for SQL Server

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.

Creating a peering connection between the VPCs allows the application's EC2 instances to communicate with the ElastiCache cluster directly and efficiently. This is the most cost-effective solution as it does not involve creating additional resources such as a Transit VPC, and it does not incur additional costs for traffic passing through the Transit VPC. Additionally, it is also more secure as it allows you to configure a more restrictive security group rule to allow inbound connection from only the application's security group.

This answer is correct because it meets the requirements of running the ML models as independent microservices that can handle irregular and unpredictable usage patterns. By directing the requests from the API into an Amazon SQS queue, the company can decouple the request processing from the model execution, and ensure that no requests are lost due to spikes in demand. By deploying the models as Amazon ECS services that read from the queue, the company can leverage containers to isolate and package each model as a microservice, and fetch the model data from S3 at startup. By enabling AWS Auto Scaling on Amazon ECS for both the cluster and copies of the service based on the queue size, the company can automatically scale up or down the number of EC2 instances in the cluster and the number of tasks in each service to match the demand and optimize performance.

References:

• https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/welcome.html
• https://docs.aws.amazon.com/AmazonECS/latest/developerguide/Welcome.html
• https://docs.aws.amazon.com/autoscaling/ec2/userguide/autoscaling-ecs.html

This option is the only solution that meets the requirements because it allows the company to encrypt the data with its own encryption keys and tools outside the AWS Cloud. By encrypting the data at the company’s data center before storing the data in the S3 bucket, the company can ensure that the data is encrypted in transit and at rest, and that the company has full control over the encryption keys and processes. This option also avoids the need to use any AWS encryption services or features, which may not be compatible with the company’s security policies or compliance standards.

A. Encrypt the data in the S3 bucket with server-side encryption (SSE) that uses an AWS Key Management Service (AWS KMS) customer managed key. This option does not meet the requirements because it does not allow the company to manage the encryption keys outside the AWS Cloud. Although the company can create and use its own customer managed key in AWS KMS, the key is still stored and managed by AWS KMS, which is a service within the AWS Cloud. Moreover, the company still needs to use the AWS encryption features and APIs to encrypt and decrypt the data in the S3 bucket, which may not be compatible with the company’s security policies or compliance standards.

B. Encrypt the data in the S3 bucket with server-side encryption (SSE) that uses an AWS Key Management Service (AWS KMS) AWS managed key. This option does not meet the requirements because it does not allow the company to manage the encryption keys outside the AWS Cloud. In this option, the company uses the default AWS managed key in AWS KMS, which is created and managed by AWS on behalf of the company. The company has no control over the key rotation, deletion, or recovery policies. Moreover, the company still needs to use the AWS encryption features and APIs to encrypt and decrypt the data in the S3 bucket, which may not be compatible with the company’s security policies or compliance standards.

C. Encrypt the data in the S3 bucket with the default server-side encryption (SSE). This option does not meet the requirements because it does not allow the company to manage the encryption keys outside the AWS Cloud. In this option, the company uses the default server-side encryption with Amazon S3 managed keys (SSE-S3), which is applied to every bucket in Amazon S3. The company has no visibility or control over the encryption keys, which are managed by Amazon S3. Moreover, the company still needs to use the AWS encryption features and APIs to encrypt and decrypt the data in the S3 bucket, which may not be compatible with the company’s security policies or compliance standards.

References:

• 1 Protecting data with encryption - Amazon Simple Storage Service
• 2 Protecting data with server-side encryption - Amazon Simple Storage Service
• 3 Protecting data by using client-side encryption - Amazon Simple Storage Service
• 4 AWS Key Management Service Concepts - AWS Key Management Service

This solution meets the requirements because it requires the least amount of infrastructure management and guarantees exactly-once delivery for application messaging. AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. You only pay for the compute time you consume. Lambda scales automatically with the size of your workload. Amazon SQS FIFO queues are designed to ensure that messages are processed exactly once, in the exact order that they are sent. FIFO queues have high availability and deliver messages in a strict first-in, first-out order. You can use Amazon SQS to decouple and scale microservices, distributed systems, and serverless applications. References: AWS Lambda, Amazon SQS FIFO queues

https://docs.aws.amazon.com/kms/latest/developerguide/key-policy-modifying-external-accounts. html

There's no need to create another custom AWS KMS key. https://aws.amazon.com/premiumsupport/knowledge-center/aurora-share-encrypted-snapshot/ Give target account access to the custom AWS KMS key within the source account 1. Log in to the source account, and go to the AWS KMS console in the same Region as the DB cluster snapshot. 2. Select Customer-managed keys from the navigation pane. 3. Select your custom AWS KMS key (ALREADY CREATED) 4. From the Other AWS accounts section, select Add another AWS account, and then enter the AWS account number of your target account. Then: Copy and share the DB cluster snapshot

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.

https://docs.aws.amazon.com/apigateway/latest/developerguide/apigateway-integrate-with-cognito.html

To control access to the REST API and reduce development efforts, the company can use an Amazon Cognito user pool authorizer in API Gateway. This will allow Amazon Cognito to validate each request and ensure that only authenticated users can access the API. This solution has the LEAST operational overhead, as it does not require the company to develop and maintain any additional infrastructure or code.

https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.AuroraMySQL.html

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/prescriptive-guidance/latest/dynamodb-hierarchical-data-model/introduction.html

Create an Amazon Elastic File System (Amazon EFS) file system. Mount the EFS file system on all web servers. To meet the requirements of providing a shared file store for Linux-based web servers without making changes to the application, using an Amazon EFS file system is the best solution. Amazon EFS is a managed NFS file system service that provides shared access to files across multiple Linux-based instances, which makes it suitable for this use case. Amazon S3 is not ideal for this scenario since it is an object storage service and not a file system, and it requires additional tools or libraries to mount the S3 bucket as a file system. Amazon CloudFront can be used to improve content delivery performance but is not necessary for this requirement. Additionally, Amazon EBS volumes can only be mounted to one instance at a time, so it is not suitable for sharing files across multiple instances.

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.