Amazon Web Services SAP-C02 Exam Questions Free Practice Test

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Questions # 76:

A company is running an event ticketing platform on AWS and wants to optimize the platform's cost-effectiveness. The platform is deployed on Amazon Elastic Kubernetes Service (Amazon EKS) with Amazon EC2 and is backed by an Amazon RDS for MySQL DB instance. The company is developing new application features to run on Amazon EKS with AWS Fargate.

The platform experiences infrequent high peaks in demand. The surges in demand depend on event dates.

Which solution will provide the MOST cost-effective setup for the platform?

Options:

Purchase Standard Reserved Instances for the EC2 instances that the EKS cluster uses in its baseline load. Scale the cluster with Spot Instances to handle peaks. Purchase 1-year All Upfront Reserved Instances for the database to meet predicted peak load for the year.

Purchase Compute Savings Plans for the predicted medium load of the EKS cluster. Scale the cluster with On-Demand Capacity Reservations based on event dates for peaks. Purchase 1-year No Upfront Reserved Instances for the database to meet the predicted base load. Temporarily scale out database read replicas during peaks.

Purchase EC2 Instance Savings Plans for the predicted base load of the EKS cluster. Scale the cluster with Spot Instances to handle peaks. Purchase 1-year All Upfront Reserved Instances for the database to meet the predicted base load. Temporarily scale up the DB instance manually during peaks.

Purchase Compute Savings Plans for the predicted base load of the EKS cluster. Scale the cluster with Spot Instances to handle peaks. Purchase 1-year All Upfront Reserved Instances for the database to meet the predicted base load. Temporarily scale up the DB instance manually during peaks.

Expert Solution

Questions # 77:

A company is developing a new service that will be accessed using TCP on a static port A solutions architect must ensure that the service is highly available, has redundancy across Availability Zones, and is accessible using the DNS name myservice.com, which is publicly accessible The service must use fixed address assignments so other companies can add the addresses to their allow lists.

Assuming that resources are deployed in multiple Availability Zones in a single Region, which solution will meet these requirements?

Options:

Create Amazon EC2 instances with an Elastic IP address for each instance Create a Network Load Balancer (NLB) and expose the static TCP port Register EC2instances with the NLB Create a new name server record set named my service com, and assign the Elastic IP addresses of the EC2 instances to the record set Provide the Elastic IP addresses of the EC2 instances to the other companies to add to their allow lists

Create an Amazon ECS cluster and a service definition for the application Create and assign public IP addresses for the ECS cluster Create a Network Load Balancer (NLB) and expose the TCP port Create a target group and assign the ECS cluster name to the NLB Create a new A record set named my service com and assign the public IP addresses of the ECS cluster to the record set Provide the public IP addresses of the ECS cluster to the other com

Create Amazon EC2 instances for the service Create one Elastic IP address for each Availability Zone Create a Network Load Balancer (NLB) and expose the assigned TCP port Assign the Elastic IP addresses to the NLB for each Availability Zone Create a target group and register the EC2 instances with the NLB Create a new A (alias) record set named my service com, and assign the NLB DNS name to the record set.

Create an Amazon ECS cluster and a service definition for the application Create and assign public IP address for each host in the cluster Create an Application Load Balancer (ALB) and expose the static TCP port Create a target group and assign the ECS service definition name to the ALB Create a new CNAME record set and associate the public IP addresses to the record set Provide the Elastic IP addresses of the Amazon EC2 instances to the ot

Expert Solution

Questions # 78:

A company is using AWS Organizations to manage multiple accounts Due to regulatory requirements, the company wants to restrict specific member accounts to certain AWS Regions, where they are permitted to deploy resources The resources in the accounts must be tagged enforced based on a group standard and centrally managed with minimal configuration.

What should a solutions architect do to meet these requirements'?

Options:

Create an AWS Config rule in the specific member accounts to limit Regions and apply a tag policy.

From the AWS Billing and Cost Management console in the management account, disable Regions for the specific member accounts and apply a tag policy on the root.

Associate the specific member accounts with the root Apply a tag policy and an SCP using conditions to limit Regions.

Associate the specific member accounts with a new OU. Apply a tag policy and an SCP using conditions to limit Regions.

Expert Solution

Questions # 79:

Question:

A company runs a Linux app on Amazon EKS usingM6iEC2 instances under a Savings Plan that is about to expire. They want toreduce costsafter expiration.

Options:

Rebuild containers forARM64architecture.

Rebuild containers for container compatibility (invalid/unclear).

Migrate EKS nodes toGraviton(e.g., C7g, M7g).

Replace nodes with latestx86_64instances.

Purchase new Savings Plan for Graviton instance family.

Purchase new Savings Plan for x86_64 instances.

Expert Solution

Questions # 80:

A company is implementing a serverless architecture by using AWS Lambda functions that need to access a Microsoft SQL Server DB instance on Amazon RDS. The company has separate environments for development and production, including a clone of the database system.

The company's developers are allowed to access the credentials for the development database. However, the credentials for the production database must be encrypted with a key that only members of the IT security team's IAM user group can access. This key must be rotated on a regular basis.

What should a solutions architect do in the production environment to meet these requirements?

Options:

Store the database credentials in AWS Systems Manager Parameter Store by using a SecureString parameter that is encrypted by an AWS Key Management Service (AWS KMS) customer managed key. Attach a role to each Lambda function to provide access to the SecureString parameter. Restrict access to the Securestring parameter and the customer managed key so that only the IT security team can access the parameter and the key.

Encrypt the database credentials by using the AWS Key Management Service (AWS KMS) default Lambda key. Store the credentials in the environment variables of each Lambda function. Load the credentials from the environment variables in the Lambda code. Restrict access to the KMS key o that only the IT security team can access the key.

Store the database credentials in the environment variables of each Lambda function.Encrypt the environment variables by using an AWS Key Management Service (AWS KMS) customer managed key. Restrict access to the customer managed key so that only the IT security team can access the key.

Store the database credentials in AWS Secrets Manager as a secret that is associated with an AWS Key Management Service (AWS KMS) customermanaged key. Attach a role to each Lambda function to provide access to the secret. Restrict access to the secret and the customer managed key so that only the IT security team can access the secret and the key.

Expert Solution

Questions # 81:

A solutions architect is redesigning a three-tier application that a company hosts onpremises. The application provides personalized recommendations based on user profiles. The company already has an AWS account and has configured a VPC to host the application.

The frontend is a Java-based application that runs in on-premises VMs. The company hosts a personalization model on a physical application server and uses TensorFlow to implement the model. The personalization model uses artificial intelligence and machine learning (AI/ML). The company stores user information in a Microsoft SQL Server database. The web application calls the personalization model, which reads the user profiles from the database and provides recommendations.

The company wants to migrate the redesigned application to AWS.

Which solution will meet this requirement with the LEAST operational overhead?

Options:

Use AWS Server Migration Service (AWS SMS) to migrate the on-premises physical application server and the web application VMs to AWS. Use AWS Database Migration Service (AWS DMS) to migrate the SQL Server database to Amazon RDS for SQL Server.

Export the personalization model. Store the model artifacts in Amazon S3. Deploy the model to Amazon SageMaker and create an endpoint. Host the Java application in AWS Elastic Beanstalk. Use AWS Database Migration Service {AWS DMS) to migrate the SQL Server database to Amazon RDS for SQL Server.

Use AWS Application Migration Service to migrate the on-premises personalization model and VMs to Amazon EC2 instances in Auto Scaling groups. Use AWS Database Migration Service (AWS DMS) to migrate the SQL Server database to an EC2 instance.

Containerize the personalization model and the Java application. Use Amazon Elastic Kubernetes Service (Amazon EKS) managed node groups to deploy the model and the application to Amazon EKS Host the node groups in a VPC. Use AWS Database Migration Service (AWS DMS) to migrate the SQL Server database to Amazon RDS for SQL Server.

Expert Solution

Answer

Explanation

Amazon SageMaker is a fully managed machine learning service that allows users to build, train, and deploy machine learning models quickly and easily1. Users can export their existing TensorFlow models and store the model artifacts in Amazon S3, a highly scalable and durable object storage service2. Users can then deploy the model to Amazon SageMaker and create an endpoint that can be invoked by the web application to provide recommendations3. This way, the solution can leverage the AI/ML capabilities of Amazon SageMaker without having to rewrite the personalization model.

AWS Elastic Beanstalk is a service that allows users to deploy and manage web applications without worrying about the infrastructure that runs those applications. Users can host their Java application in AWS Elastic Beanstalk and configure it to communicate with the Amazon SageMaker endpoint. This way, the solution can reduce the operational overhead of managing servers, load balancers, scaling, and application health monitoring.

AWS Database Migration Service (AWS DMS) is a service that helps users migrate databases to AWS quickly and securely. Users can use AWS DMS to migrate their SQL Server database to Amazon RDS for SQL Server, a fully managed relational database service that offers high availability, scalability, security, and compatibility. This way, the solution canreduce the operational overhead of managing database servers, backups, patches, and upgrades.

Option A is incorrect because using AWS Server Migration Service (AWS SMS) to migrate the on-premises physical application server and the web application VMs to AWS is not cost-effective or scalable. AWS SMS is a service that helps users migrate on-premises workloads to AWS. However, for this use case, migrating the physical application server and the web application VMs to AWS will not take advantage of the AI/ML capabilities of Amazon SageMaker or the managed services of AWS Elastic Beanstalk and Amazon RDS.

Option C is incorrect because using AWS Application Migration Service to migrate the on-premises personalization model and VMs to Amazon EC2 instances in Auto Scaling groups is not cost-effective or scalable. AWS Application Migration Service is a service that helps users migrate applications from on-premises or other clouds to AWS without making any changes to their applications. However, for this use case, migrating the personalization model and VMs to EC2 instances will not take advantage of the AI/ML capabilities of Amazon SageMaker or the managed services of AWS Elastic Beanstalk and Amazon RDS.

Option D is incorrect because containerizing the personalization model and the Java application and using Amazon Elastic Kubernetes Service (Amazon EKS) managed node groups to deploy them to Amazon EKS is not necessary or cost-effective. Amazon EKS is a service that allows users to run Kubernetes on AWS without needing to install, operate, and maintain their own Kubernetes control plane or nodes. However, for this use case, containerizing and deploying the personalization model and the Java application will not take advantage of the AI/ML capabilities of Amazon SageMaker or the managed services of AWS Elastic Beanstalk. Moreover, using S3 Glacier Deep Archive as a storage class for images will incur a high retrieval fee and latency for accessing them.

Questions # 82:

A company has automated the nightly retraining of its machine learning models by using AWS Step Functions. The workflow consists of multiple steps that use AWS Lambda Each step can fail for various reasons and any failure causes a failure of the overall workflow

A review reveals that the retraining has failed multiple nights in a row without the company noticing the failure A solutions architect needs to improve the workflow so that notifications are sent for all types of failures in the retraining process

Which combination of steps should the solutions architect take to meet these requirements? (Select THREE)

Options:

Create an Amazon Simple Notification Service (Amazon SNS) topic with a subscription of type "Email" that targets the team's mailing list.

Create a task named "Email" that forwards the input arguments to the SNS topic

Add a Catch field all Task Map. and Parallel states that have a statement of "Error Equals": [ “States. ALL”] and "Next": "Email".

Add a new email address to Amazon Simple Email Service (Amazon SES). Verify the email address.

Create a task named "Email" that forwards the input arguments to the SES email address

Add a Catch field to all Task Map, and Parallel states that have a statement of "Error Equals": [ "states. Runtime”] and "Next": "Email".

Expert Solution

Questions # 83:

A company is changing the way that it handles patching of Amazon EC2 instances in its application account. The company currently patches instances over the internet by using a NAT gateway in a VPC in the application account. The company has EC2 instances set up as a patch source repository in a dedicated private VPC in a core account. The company wants to use AWS Systems Manager Patch Manager and the patch source repository in the core account to patch the EC2 instances in the application account. The company must prevent all EC2 instances in the application account from accessing the internet. The EC2 instances in the application account need to access Amazon S3, where the application data is stored. These EC2 instances need connectivity to Systems Manager and to the patch source repository in the private VPC in the core account. Which solution will meet these requirements?

Options:

Create a network ACL that blocks outbound traffic on port 80. Associate the network ACL with all subnets in the application account. In the application account and the core account, deploy one EC2 instance that runs a custom VPN server. Create a VPN tunnel to access the private VPC. Update the route table in the application account.

Create private VIFs for Systems Manager and Amazon S3. Delete the NAT gateway from the VPC in the application account. Create a transit gateway to access the patch source repository EC2 instances in the core account. Update the route table in the core account.

Create VPC endpoints for Systems Manager and Amazon S3. Delete the NAT gateway from the VPC in the application account. Create a VPC peering connection to access the patch source repository EC2 instances in the core account. Update the route tables in both accounts.

Create a network ACL that blocks inbound traffic on port 80. Associate the network ACL with all subnets in the application account. Create a transit gateway to access the patch source repository EC2 instances in the core account. Update the route tables in both accounts.

Expert Solution

Answer

Explanation

Option C is the correct and most efficient solution, aligning with AWS best practices for secure and private connectivity:

Create VPC Endpoints for Systems Manager and Amazon S3:

Systems Manager VPC Endpoints: By creating interface VPC endpoints for Systems Manager (com.amazonaws.region.ssm, com.amazonaws.region.ec2messages, and com.amazonaws.region.ssmmessages), the EC2 instances can communicate with Systems Manager services without requiring internet access. This setup ensures that patching operations can be conducted securely within the AWS network.

Amazon S3 VPC Endpoint: A gateway VPC endpoint for Amazon S3 (com.amazonaws.region.s3) allows EC2 instances to access S3 buckets privately. This is essential for accessing application data stored in S3 without traversing the public internet.

[Reference: docs.aws.amazon.com, Delete the NAT Gateway:, Removing the NAT gateway ensures that EC2 instances in the application account cannot access the internet, satisfying the requirement to prevent internet access. This action enhances the security posture by eliminating a potential vector for unauthorized outbound traffic., Create a VPC Peering Connection:, Establishing a VPC peering connection between the application account's VPC and the core account's private VPC enables direct, private communication between the EC2 instances in both accounts. This setup allows the application account's EC2 instances to access the patch source repository hosted in the core account securely., Reference: docs.aws.amazon.com, Update Route Tables in Both Accounts:, After setting up the VPC peering connection, it's crucial to update the route tables in both VPCs to allow traffic to flow between them. This configuration ensures that the EC2 instances in the application account can reach the patch source repository in the core account and vice versa., Why Other Options Are Incorrect:, Option A: Implementing a custom VPN solution introduces unnecessary complexity and operational overhead. Additionally, merely blocking outbound traffic on port 80 does not comprehensively prevent internet access, as other ports (e.g., 443 for HTTPS) remain open., Option B: Creating private virtual interfaces (VIFs) is typically associated with AWS Direct Connect, which is not applicable in this scenario. Moreover, using a transit gateway, while feasible, is more complex and may be unnecessary for this use case., Option D: Blocking inbound traffic on port 80 does not prevent outbound internet access. Furthermore, employing a transit gateway adds complexity and cost, which may not be justified given the requirements., Conclusion:, Option C provides a secure, efficient, and cost-effective solution that meets all the specified requirements:, Prevents EC2 instances from accessing the internet., Enables access to Amazon S3 and Systems Manager services via VPC endpoints., Facilitates secure communication with the patch source repository in the core account through VPC peering., This approach leverages AWS's native networking features to maintain a secure and private environment for patch management operations., ]

Questions # 84:

A company is running several applications in the AWS Cloud. The applications are specific to separate business units in the company. The company is running the components of the applications in several AWS accounts that are in an organization in AWS Organizations. Every cloud resource in the company's organization has a tag that is named BusinessUnit. Every tag already has the appropriate value of the business unit name. The company needs to allocate its cloud costs to different business units. The company also needs to visualize the cloud costs for each business unit. Which solution will meet these requirements?

Options:

In the organization's management account, create a cost allocation tag that is named BusinessUnit. Also in the management account, create an Amazon S3 bucket and an AWS Cost and Usage Report (AWS CUR). Configure the S3 bucket as the destination for the AWS CUR. From the management account, query the AWS CUR data by using Amazon Athena. Use Amazon QuickSight for visualization.

In each member account, create a cost allocation tag that is named BusinessUnit. In the organization's management account, create an Amazon S3 bucket and an AWS Cost and Usage Report (AWS CUR). Configure the S3 bucket as the destination for the AWS CUR. Create an Amazon CloudWatch dashboard for visualization.

In the organization's management account, create a cost allocation tag that is named BusinessUnit. In each member account, create an Amazon S3 bucket and an AWS Cost and Usage Report (AWS CUR). Configure each S3 bucket as the destination for its respective AWS CUR. In the management account, create an Amazon CloudWatch dashboard for visualization.

In each member account, create a cost allocation tag that is named BusinessUnit. Also in each member account, create an Amazon S3 bucket and an AWS Cost and Usage Report (AWS CUR). Configure each S3 bucket as the destination for its respective AWS CUR. From the management account, query the AWS CUR data by using Amazon Athena. Use Amazon QuickSight for visualization.

Expert Solution

Questions # 85:

A company is using Amazon OpenSearch Service to analyze data. The company loads data into an OpenSearch Service cluster with 10 data nodes from an Amazon S3 bucket that uses S3 Standard storage. The data resides in the cluster for 1 month for read-only analysis. After 1 month, the company deletes the index that contains the data from the cluster. For compliance purposes, the company must retain a copy of all input data.

The company is concerned about ongoing costs and asks a solutions architect to recommend a new solution.

Which solution will meet these requirements MOST cost-effectively?

Options:

Replace all the data nodes with UltraWarm nodes to handle the expected capacity. Transition the input data from S3 Standard to S3 Glacier Deep Archive when the company loads the data into the cluster.

Reduce the number of data nodes in the cluster to 2 Add UltraWarm nodes to handle the expected capacity. Configure the indexes to transition to UltraWarm when OpenSearch Service ingests the data. Transition the input data to S3 Glacier Deep Archive after 1 month by using an S3 Lifecycle policy.

Reduce the number of data nodes in the cluster to 2. Add UltraWarm nodes to handle the expected capacity. Configure the indexes to transition to UltraWarm when OpenSearch Service ingests the data. Add cold storage nodes to the cluster Transition the indexes from UltraWarm to cold storage. Delete the input data from the S3 bucket after 1 month by using an S3 Lifecycle policy.

Reduce the number of data nodes in the cluster to 2. Add instance-backed data nodes to handle the expected capacity. Transition the input data from S3 Standard to S3 Glacier Deep Archive when the company loads the data into the cluster.

Expert Solution

Questions # 86:

A company needs to modernize an application and migrate the application to AWS. The application stores user profile data as text in a single table in an on-premises MySQL database.

After the modernization, users will use the application to upload video files that are up to 4 GB in size. Other users must be able to download the video files from the application. The company needs a video storage solution that provides rapid scaling. The solution must not affect application performance.

Which solution will meet these requirements?

Options:

Migrate the database to Amazon Aurora PostgreSQL by using AWS DMS. Store the videos as base64-encoded strings in a TEXT column in the database.

Migrate the database to Amazon DynamoDB by using AWS DMS with AWS SCT. Store the videos as objects in Amazon S3. Store the S3 key in the corresponding DynamoDB item.

Migrate the database to Amazon Keyspaces by using AWS DMS with AWS SCT. Store the videos as objects in Amazon S3. Store the S3 object identifier in the corresponding Amazon Keyspaces entry.

Migrate the database to Amazon DynamoDB by using AWS DMS with AWS SCT. Store the videos as base64-encoded strings in the corresponding DynamoDB item.

Expert Solution

Answer

Explanation

The modernized application needs to store and serve video files up to 4 GB. Large binary content should not be stored directly in a database because it negatively affects database performance, scaling, and backup/restore times. The standard AWS pattern is to store large objects in Amazon S3 and keep only references (such as keys or URLs) in the database.

User profile data is simple, text-based, and currently lives in a single table. This is a good fit for a key-value or document-style data model such as Amazon DynamoDB, which provides fully managed horizontal scaling and predictable performance at scale.

Option B migrates the profile table to DynamoDB using AWS DMS with AWS Schema Conversion Tool (SCT). Video files are stored as objects in Amazon S3, which is designed for large, durable, and highly scalable object storage. The DynamoDB item stores only the S3 key that corresponds to each user’s video, keeping the database small and responsive. S3 can scale rapidly and independently of the database, and offloads the heavy I/O load of large objects away from the transactional store, so overall application performance is not negatively impacted by video storage or retrieval.

Option A stores the videos as base64-encoded strings in a TEXT column in a relational database. Storing multi-gigabyte objects directly in a relational database table leads to large row sizes, larger indexes, longer backup times, and degraded performance as the table grows. This does not meet the requirement to avoid affecting application performance.

Option C uses Amazon Keyspaces (for Apache Cassandra) as the profile store and S3 for video. While storing videos in S3 is correct, Keyspaces is typically chosen when there is already a Cassandra-based workload or a need for Cassandra-compatible interfaces. For a simple single-table user profile store being migrated from MySQL, DynamoDB is the more natural, managed choice and aligns better with AWS migration and modernization guidance.

Option D stores the videos as base64-encoded strings in DynamoDB items. DynamoDB has a maximum item size of 400 KB, which is far smaller than the 4 GB video size requirement. This makes option D technically infeasible.

Therefore, migrating user profile data to DynamoDB and storing video files in Amazon S3, with S3 keys stored in the corresponding DynamoDB items (option B), provides scalable video storage and protects application performance.

[References:AWS guidance on storing large binary objects in Amazon S3 and storing only references in databases for scalable architectures.AWS best practices for using Amazon DynamoDB as a scalable key-value store for user profiles and metadata.]

Questions # 87:

A solutions architect is designing an AWS account structure for a company that consists of multiple teams. All the teams will work in the same AWS Region. The company needs a VPC that is connected to the on-premises network. The company expects less than 50 Mbps of total traffic to and from the on-premises network.

Which combination of steps will meet these requirements MOST cost-effectively? (Select TWO.)

Options:

Create an AWS Cloud Formation template that provisions a VPC and the required subnets. Deploy the template to each AWS account.

Create an AWS Cloud Formation template that provisions a VPC and the required subnets. Deploy the template to a shared services account Share the subnets by using AWS Resource Access Manager.

Use AWS Transit Gateway along with an AWS Site-to-Site VPN for connectivity to the on-premises network. Share the transit gateway by using AWS Resource Access Manager.

Use AWS Site-to-Site VPN for connectivity to the on-premises network.

Use AWS Direct Connect for connectivity to the on-premises network.

Expert Solution

Questions # 88:

A company is deploying a new cluster for big data analytics on AWS. The cluster will run across many Linux Amazon EC2 instances that are spread across multiple Availability Zones.

All of the nodes in the cluster must have read and write access to common underlying file storage. The file storage must be highly available, must be resilient, must be compatible with the Portable Operating System Interface (POSIX). and must accommodate high levels of throughput.

Which storage solution will meet these requirements?

Options:

Provision an AWS Storage Gateway file gateway NFS file share that is attached to an Amazon S3 bucket. Mount the NFS file share on each EC2 instance in the duster.

Provision a new Amazon Elastic File System (Amazon EFS) file system that uses General Purpose performance mode. Mount the EFS file system on each EC2 instance in the cluster.

Provision a new Amazon Elastic Block Store (Amazon EBS) volume that uses the io2 volume type. Attach the EBS volume to all of the EC2 instances in the cluster.

Provision a new Amazon Elastic File System (Amazon EFS) file system that uses Max I/O performance mode. Mount the EFS file system on each EC2 instance in the cluster.

Expert Solution

Questions # 89:

Question:

A solutions architect is importing a VM from an on-premises environment by using the Amazon EC2 VM Import feature. The imported instance has a public IP and runs in a public subnet in a VPC. However, the instance doesnot appearin the AWS Systems Manager (SSM) console as a managed instance.

Which combination of steps should the architect take to resolve the issue? (Select TWO.)

Options:

Verify that Systems Manager Agent is installed on the instance and is running.

Verify that the instance is assigned an appropriate IAM role for Systems Manager.

Verify the existence of a VPC endpoint on the VPC.

Verify that the AWS Application Discovery Agent is configured.

Verify the correct configuration of service-linked roles for Systems Manager.

Expert Solution

Questions # 90:

A company collects air quality data from sensors. The company plans to use the MQTT protocol to send the data to AWS IoT Core. The company will process the data and then will store the data in an Amazon Aurora database.

During periods of low air quality, sensors will send data more frequently. The company must buffer the data during these periods to make sure that no data is lost before the data is processed and stored.

Which solution will meet these requirements?

Options:

Create an Amazon Kinesis data stream. Create an AWS IoT rule action and set the data stream as the target. Create an AWS Step Functions state machine that is invoked by the data stream. Use the state machine to process and store the data.

Create an Amazon Kinesis data stream. Create an AWS IoT rule action and set the data stream as the target. Create an application that runs on an Amazon ECS cluster with the AWS Fargate launch type. Configure the application to read data from the data stream, process the data, and store the data.

Create an Amazon SQS queue. Create an AWS IoT rule action and set the SQS queue as the target. Create an AWS Step Functions state machine that is invoked by the SQS queue. Use the state machine to process and store the data.

Create an Amazon SNS topic. Create an AWS IoT rule action and set the SNS topic as the target. Create an application that runs on an Amazon ECS cluster with the AWS Fargate launch type. Configure the application to read data from the SNS topic, process the data, and store the data.

Expert Solution

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