Amazon Web Services SAP-C02 Exam Questions Free Practice Test

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Questions # 31:

A company runs an loT application in the AWS Cloud. The company has millions of sensors that collect data from houses in the United States. The sensors use the MOTT protocol to connect and send data to a custom MQTT broker. The MQTT broker stores the data on a single Amazon EC2 instance. The sensors connect to the broker through the domain named iot.example.com. The company uses Amazon Route 53 as its DNS service. The company stores the data in Amazon DynamoDB.

On several occasions, the amount of data has overloaded the MOTT broker and has resulted in lost sensor data. The company must improve the reliability of the solution.

Which solution will meet these requirements?

Options:

Create an Application Load Balancer (ALB) and an Auto Scaling group for the MOTT broker. Use the Auto Scaling group as the target for the ALB. Update the DNS record in Route 53 to an alias record. Point the alias record to the ALB. Use the MQTT broker to store the data.

Set up AWS loT Core to receive the sensor data. Create and configure a custom domain to connect to AWS loT Core. Update the DNS record in Route 53 to point to the AWS loT Core Data-ATS endpoint. Configure an AWS loT rule to store the data.

Create a Network Load Balancer (NLB). Set the MQTT broker as the target. Create an AWS Global Accelerator accelerator. Set the NLB as the endpoint for the accelerator. Update the DNS record in Route 53 to a multivalue answer record. Set the Global Accelerator IP addresses as values. Use the MQTT broker to store the data.

Set up AWS loT Greengrass to receive the sensor data. Update the DNS record in Route 53 to point to the AWS loT Greengrass endpoint. Configure an AWS loT rule to invoke an AWS Lambda function to store the data.

Expert Solution

Questions # 32:

A company use an organization in AWS Organizations to manage multiple AWS accounts. The company hosts some applications in a VPC in the company ' s snared services account. The company has attached a transit gateway to the VPC in the Shared services account.

The company is developing a new capability and has created a development environment that requires access to the applications that are in the snared services account. The company intends to delete and recreate resources frequently in the development account. The company also wants to give a development team the ability to recreate the team ' s connection to the shared services account as required.

Which solution will meet these requirements?

Options:

Create a transit gateway in the development account. Create a transit gateway peering request to the shared services account. Configure the snared services transit gateway to automatically accept peering connections.

Turn on automate acceptance for the transit gateway in the shared services account. Use AWS Resource Access Manager (AWS RAM) to share the transit gateway resource in the shared services account with the development account. Accept the resource in tie development account. Create a transit gateway attachment in the development account.

Turn on automate acceptance for the transit gateway in the shared services account. Create a VPC endpoint. Use the endpoint policy to grant permissions on the VPC endpoint for the development account. Configure the endpoint service to automatically accept connection requests. Provide the endpoint details to the development team.

Create an Amazon EventBridge rule to invoke an AWS Lambda function that accepts the transit gateway attachment value the development account makes an attachment request. Use AWS Network Manager to store. The transit gateway in the shared services account with the development account. Accept the transit gateway in the development account.

Expert Solution

Questions # 33:

A company has a sales system that stores transactions as .csv files in an Amazon S3 bucket. The S3 bucket is configured to use S3 Intelligent-Tiering. Most of the .csv files are between 64 KB and 100 KB in size. All rows and columns of the .csv files must be read when the data is processed. The company must keep the data for 5 years.

The company stores several million xsv files every day. The company must minimize the cost of storing and querying the xsv files.

Which solution will meet these requirements?

Options:

Create an AWS Glue job to convert the .csv files into Apache Parquet format. Use Amazon S3 to invoke the AWS Glue job every time a .csv file arrives.

Create an AWS Glue job to compress the .csv files. Schedule the AWS Glue job every hour to compress the files for the previous hour into one .csv file.

Create an AWS Lambda function to convert the .csv files into Apache Parquet format. Use Amazon S3 to invoke the Lambda function every time a .csv file arrives.

Create an AWS Lambda function to compress the .csv files. Use Amazon S3 to invoke the Lambda function every time a .csv file arrives.

Expert Solution

Questions # 34:

A team of data scientists is using Amazon SageMaker instances and SageMaker APIs to train machine learning (ML) models. The SageMaker instances are deployed in a

VPC that does not have access to or from the internet. Datasets for ML model training are stored in an Amazon S3 bucket. Interface VPC endpoints provide access to Amazon S3 and the SageMaker APIs.

Occasionally, the data scientists require access to the Python Package Index (PyPl) repository to update Python packages that they use as part of their workflow. A solutions architect must provide access to the PyPI repository while ensuring that the SageMaker instances remain isolated from the internet.

Which solution will meet these requirements?

Options:

Create an AWS CodeCommit repository for each package that the data scientists need to access. Configure code synchronization between the PyPl repositoryand the CodeCommit repository. Create a VPC endpoint for CodeCommit.

Create a NAT gateway in the VPC. Configure VPC routes to allow access to the internet with a network ACL that allows access to only the PyPl repositoryendpoint.

Create a NAT instance in the VPC. Configure VPC routes to allow access to the internet. Configure SageMaker notebook instance firewall rules that allow access to only the PyPI repository endpoint.

Create an AWS CodeArtifact domain and repository. Add an external connection for public:pypi to the CodeArtifact repository. Configure the Python client touse the CodeArtifact repository. Create a VPC endpoint for CodeArtifact.

Expert Solution

Questions # 35:

A company is migrating internal business applications to Amazon EC2 and Amazon RDS in a VPC. The migration requires connecting the cloud-based applications to the on-premises internal network. The company wants to set up an AWS 5ite-to-5ite VPN connection. The company has created two separate customer gateways. The gateways are configured for static routing and have been assigned distinct public IP addresses.

Which solution will meet these requirements?

Options:

Create one virtual private gateway. Associate the virtual private gateway with the VPC. Enable route propagation for the virtual private gateway in all VPC route tables. Create two Site-to-Slte VPN connections with two tunnels for each connection. Configure the Site-to-Slte VPN connections to use the virtual private gateway and to use separate customer gateways.

Create one customer gateway. Associate the customer gateway with the VPC. Enable route propagation for the customer gateway in all VPC route tables. Create two Site-to-Site VPN connections with two tunnels for each connection. Configure the Site-to-Site VPN connections to use the customer gateway.

Create two virtual private gateways. Associate the virtual private gateways with the VPC. Enable route propagation for both customer gateways in all VPC route tables. Create two Site-to-Site VPN connections with two tunnels for each connection. Configure the Site-to-Site VPN connections to use separate virtual private gateways and separate customer gateways.

Create two virtual private gateways. Associate the virtual private gateways with the VPC. Enable route propagation for both customer gateways in all VPC route tables. Create four Site-to-Site VPN connections with one tunnel for each connection. Configure the Site-to-Site VPN connections into groups of two. Configure each group to connect to separate customer gateways and separate virtual private gateways.

Expert Solution

Questions # 36:

An international delivery company hosts a delivery management system on AWS. Drivers use the system to upload confirmation of delivery. Confirmation includes the recipient ' s signature or a photo of the package with the recipient. The driver ' s handheld device uploads signatures and photos through FTP to a single Amazon EC2 instance. Each handheld device saves a file in a directory based on the signed-in user, and the file name matches the delivery number. The EC2 instance then adds metadata to the file after querying a central database to pull delivery information. The file is then placed in Amazon S3 for archiving.

As the company expands, drivers report that the system is rejecting connections. The FTP server is having problems because of dropped connections and memory issues. In response to these problems, a system engineer schedules a cron task to reboot the EC2 instance every 30 minutes. The billing team reports that files are not always in the archive and that the central system is not always updated.

A solutions architect needs to design a solution that maximizes scalability to ensure that the archive always receives the files and that systems are always updated. The handheld devices cannot be modified, so the company cannot deploy a new application.

Which solution will meet these requirements?

Options:

Create an AMI of the existing EC2 instance. Create an Auto Scaling group of EC2 instances behind an Application Load Balancer. Configure the Auto Scaling group to have a minimum of three instances.

Use AWS Transfer Family to create an FTP server that places the files in Amazon Elastic File System (Amazon EFS). Mount the EFS volume to the existing EC2 instance. Point the EC2 instance to the new path for file processing.

Use AWS Transfer Family to create an FTP server that places the files in Amazon S3. Use an S3 event notification through Amazon Simple Notification Service (Amazon SNS) to invoke an AWS Lambda function. Configure the Lambda function to add the metadata and update the delivery system.

Update the handheld devices to place the files directly in Amazon S3. Use an S3 eventnotification through Amazon Simple Queue Service (Amazon SQS) to invoke an AWS Lambda function. Configure the Lambda function to add the metadata and update the delivery system.

Expert Solution

Questions # 37:

A solutions architect has deployed a web application that serves users across two AWS Regionsunder a custom domain The application uses Amazon Route 53 latency-based routing The solutions architect has associated weighted record sets with a pair of web servers in separate Availability Zones for each Region

The solutions architect runs a disaster recovery scenario When all the web servers in one Region are stopped. Route 53 does not automatically redirect users to the other Region

Which of the following are possible root causes of this issue1? (Select TWO)

Options:

The weight for the Region where the web servers were stopped is higher than the weight for the other Region.

One of the web servers in the secondary Region did not pass its HTTP health check

Latency resource record sets cannot be used in combination with weighted resource record sets

The setting to evaluate target health is not turned on for the latency alias resource record set that is associated with the domain in the Region where the web servers were stopped.

An HTTP health check has not been set up for one or more of the weighted resource record sets associated with the stopped web servers

Expert Solution

Questions # 38:

Question:

A company runs workloads on EC2 inmultiple VPCsin a single Region. They also have anon-premises DNS server(via Direct Connect). All EC2 instances must resolve internal.company.com usingprivate communication.

What should a solutions architect do? (Select THREE.)

Options:

Create an Amazon Route 53inbound endpointin all workload VPCs.

Create a Route 53outbound endpointin one VPC.

Create a Route 53forwarding ruleto forward internal.company.com to the on-prem DNS.

Create a Route 53 rule with theSystemtype.

Associate the rule with all VPCs.

Associate the rule only with the VPC that has the outbound endpoint.

Expert Solution

Questions # 39:

A company uses AWS Organizations to manage its development environment. Each development team at the company has its own AWS account Each account has a single VPC and CIDR blocks that do not overlap.

The company has an Amazon Aurora DB cluster in a shared services account All the development teams need to work with live data from the DB cluster

Which solution will provide the required connectivity to the DB cluster with the LEAST operational overhead?

Options:

Create an AWS Resource Access Manager (AWS RAM) resource share tor the DB cluster. Share the DB cluster with all the development accounts

Create a transit gateway in the shared services account Create an AWS Resource Access Manager (AWS RAM) resource share for the transit gateway Share the transit gateway with all the development accounts Instruct the developers to accept the resource share Configure networking.

Create an Application Load Balancer (ALB) that points to the IP address of the DB cluster Create an AWS PrivateLink endpoint service that uses the ALB Add permissions to allow each development account to connect to the endpoint service

Create an AWS Site-to-Site VPN connection in the shared services account Configure networking Use AWS Marketplace VPN software in each development account to connect to the Site-to-Site VPN connection

Expert Solution

Answer

Explanation

Create a Transit Gateway:

In the shared services account, create a new AWS Transit Gateway. This serves as a central hub to connect multiple VPCs, simplifying the network topology and management.

Configure Transit Gateway Attachments:

Attach the VPC containing the Aurora DB cluster to the transit gateway. This allows the shared services VPC to communicate through the transit gateway.

Create Resource Share with AWS RAM:

Use AWS Resource Access Manager (AWS RAM) to create a resource share for the transit gateway. Share this resource with all development accounts. AWS RAM allows you to securely share your AWS resources across AWS accounts without needing to duplicate them.

Accept Resource Shares in Development Accounts:

Instruct each development team to log into their respective AWS accounts and accept the transit gateway resource share. This step is crucial for enabling cross-account access to the shared transit gateway.

Configure VPC Attachments in Development Accounts:

Each development account needs to attach their VPC to the shared transit gateway. This allows their VPCs to route traffic through the transit gateway to the Aurora DB cluster in the shared services account.

Update Route Tables:

Update the route tables in each VPC to direct traffic intended for the Aurora DB cluster through the transit gateway. This ensures that network traffic is properly routed between the development VPCs and the shared services VPC.

Using a transit gateway simplifies the network management and reduces operational overhead by providing a scalable and efficient way to interconnect multiple VPCs across different AWS accounts.

References

AWS Database Blog on RDS Proxy for Cross-Account Access【48】.

AWS Architecture Blog on Cross-Account and Cross-Region Aurora Setup【49】.

DEV Community on Managing Multiple AWS Accounts with Organizations【51】.

Questions # 40:

A company has application services that have been containerized and deployed on multiple Amazon EC2 instances with public IPs. An Apache Kafka cluster has been deployed to the EC2 instances. A PostgreSQL database has been migrated to Amazon RDS for PostgreSQL. The company expects a significant increase of orders on its platform when a new version of its flagship product is released.

What changes to the current architecture will reduce operational overhead and support the product release?

Options:

Create an EC2 Auto Scaling group behind an Application Load Balancer. Create additional read replicas for the DB instance. Create Amazon Kinesis data streams and configure the application services to use the data streams. Store and serve static content directly from Amazon S3.

Create an EC2 Auto Scaling group behind an Application Load Balancer. Deploy theDB instance in Multi-AZ mode and enable storage auto scaling. Create Amazon Kinesis data streams and configure the application services to use the data streams. Store and serve static content directly from Amazon S3.

Deploy the application on a Kubernetes cluster created on the EC2 instances behind an Application Load Balancer. Deploy the DB instance in Multi-AZ mode and enable storage auto scaling. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.

Deploy the application on Amazon Elastic Kubernetes Service (Amazon EKS) with AWS Fargate and enable auto scaling behind an Application Load Balancer. Create additional read replicas for the DB instance. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.

Expert Solution

Answer

Explanation

The correct answer is D. Deploy the application on Amazon Elastic Kubernetes Service (Amazon EKS) with AWS Fargate and enable auto scaling behind an Application Load Balancer. Create additional read replicas for the DB instance. Create an Amazon Managed Streaming for Apache Kafka cluster and configure the application services to use the cluster. Store static content in Amazon S3 behind an Amazon CloudFront distribution.

Option D meets the requirements of the scenario because it allows you to reduce operational overhead and support the product release by using the following AWS services and features:

Amazon Elastic Kubernetes Service (Amazon EKS) is a fully managed service that allows you to run Kubernetes applications on AWS without needing to install, operate, or maintain your own Kubernetes control plane. You can use Amazon EKS to deploy your containerized application services on a Kubernetes cluster that is compatible with your existing tools and processes.

AWS Fargate is a serverless compute engine that eliminates the need to provision and manage servers for your containers. You can use AWS Fargate as the launch type for your Amazon EKS pods, which are the smallest deployable units of computing in Kubernetes. You can also enable auto scaling for your pods, which allows you to automatically adjust the number of pods based on the demand or custom metrics.

An Application Load Balancer (ALB) is a load balancer that distributes traffic across multiple targets in multiple Availability Zones using HTTP or HTTPS protocols. You can use an ALB to balance the load across your Amazon EKS pods and provide high availability and fault tolerance for your application.

Amazon RDS for PostgreSQL is a fully managed relational database service that supports the PostgreSQL open source database engine. You can create additional read replicas for your DB instance, which are copies of your primary DB instance that can handle read-only queries and improve performance. You can also useread replicas to scale out beyond the capacity of a single DB instance for read-heavy workloads.

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that makes it easy to build and run applications that use Apache Kafka to process streaming data. Apache Kafka is an open source platform for building real-time data pipelines and streaming applications. You can use Amazon MSK to create and manage a Kafka cluster that is highly available, secure, and compatible with your existing Kafka applications. You can also configure your application services to use the Amazon MSK cluster as a source or destination of streaming data.

Amazon S3 is an object storage service that offers high durability, availability, and scalability. You can store static content such as images, videos, or documents in Amazon S3 buckets, which are containers for objects. You can also serve static content directly from Amazon S3 using public URLs or presigned URLs.

Amazon CloudFront is a fast content delivery network (CDN) service that securely delivers data, videos, applications, and APIs to customers globally with low latency and high transfer speeds. You can use Amazon CloudFront to create a distribution that caches static content from your Amazon S3 bucket at edge locations closer to your users. This can improve the performance and user experience of your application.

Option A is incorrect because creating an EC2 Auto Scaling group behind an ALB would not reduce operational overhead as much as using AWS Fargate with Amazon EKS, as you would still need to manage EC2 instances for your containers. Creating additional read replicas for the DB instance would not provide high availability or fault tolerance in case of a failure of the primary DB instance, unlike deploying the DB instance in Multi-AZ mode. Creating Amazon Kinesis data streams would not be compatible with your existing Apache Kafka applications, unlike using Amazon MSK.

Option B is incorrect because creating an EC2 Auto Scaling group behind an ALB would not reduce operational overhead as much as using AWS Fargate with Amazon EKS, as you would still need to manage EC2 instances for your containers. Creating Amazon Kinesis data streams would not be compatible with your existing Apache Kafka applications, unlike using Amazon MSK. Storing and serving static content directly from Amazon S3 would not provide optimal performance and user experience, unlike using Amazon CloudFront.

Option C is incorrect because deploying the application on a Kubernetes cluster created on the EC2 instances behind an ALB would not reduce operational overhead as much as using AWS Fargate with Amazon EKS, as you would still need to manage EC2 instances and Kubernetes control plane for your containers. Using Amazon API Gateway to interact with the application would add an unnecessary layer of complexity and cost to your architecture, as you would need to create and maintain an API gateway that proxies requests to your ALB.

Questions # 41:

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 # 42:

A company is developing a web application that runs on Amazon EC2 instances in an Auto Scaling group behind a public-facing Application Load Balancer (ALB). Only users from a specific country are allowed to access the application. The company needs the ability to log the access requests that have been blocked. The solution should require the least possible maintenance.

Which solution meets these requirements?

Options:

Create an IPSet containing a list of IP ranges that belong to the specified country. Create an AWS WAF web ACL. Configure a rule to block any requests that do not originate from an IP range in theIPSet. Associate the rule with the web ACL. Associate the web ACL with the ALB.

Create an AWS WAF web ACL. Configure a rule to block any requests that do not originate from the specified country. Associate the rule with the web ACL. Associate the web ACL with the ALB.

Configure AWS Shield to block any requests that do not originate from the specified country. Associate AWS Shield with the ALB.

Create a security group rule that allows ports 80 and 443 from IP ranges that belong to the specified country. Associate the security group with the ALB.

Expert Solution

Questions # 43:

A company developed a pilot application by using AWS Elastic Beanstalk and Java. To save costs during development, the company ' s development team deployed the application into a single-instance environment. Recent tests indicate that the application consumes more CPU than expected. CPU utilization is regularly greater than 85%, which causes some performance bottlenecks.

A solutions architect must mitigate the performance issues before the company launches the application to production.

Which solution will meet these requirements with the LEAST operational overhead?

Options:

Create a new Elastic Beanstalk application. Select a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the maximum CPU utilization is over 85% for 5 minutes.

Create a second Elastic Beanstalk environment. Apply the traffic-splitting deployment policy. Specify a percentage of incoming traffic to direct to the new environment in the average CPU utilization is over 85% for 5 minutes.

Modify the existing environment ' s capacity configuration to use a load-balanced environment type. Select all Availability Zones. Add a scale-out rule that will run if the average CPU utilization is over 85% for 5 minutes.

Select the Rebuild environment action with the load balancing option Select an Availability Zones Add a scale-out rule that will run if the sum CPU utilization is over 85% for 5 minutes.

Expert Solution

Questions # 44:

A financial services company receives a regular data feed from its credit card servicing partner Approximately 5.000 records are sent every 15 minutes in plaintext, delivered over HTTPS directly into an Amazon S3 bucket with server-side encryption. This feed contains sensitive credit card primary account number (PAN) data The company needs to automatically mask the PAN before sending the data to another S3 bucket for additional internal processing. The company also needs to remove and merge specific fields, and then transform the record into JSON format Additionally, extra feeds are likely to be added in the future, so any design needs to be easily expandable.

Which solutions will meet these requirements?

Options:

Trigger an AWS Lambda function on file delivery that extracts each record and writes it to an Amazon SQS queue. Trigger another Lambda function when new messages arrive in the SQS queue to process the records, writing the results to a temporary location in Amazon S3. Trigger a final Lambda function once the SQS queue is empty to transform the records into JSON format and send the results to another S3 bucket for internal processing.

Trigger an AWS Lambda function on file delivery that extracts each record and writes it to an Amazon SQS queue. Configure an AWS Fargate container application to automatically scale to a single instance when the SQS queue contains messages. Have the application process each record, and transform the record into JSON format. When the queue is empty, send the results to another S3bucket for internal processing and scale down the AWS Fargate i

Create an AWS Glue crawler and custom classifier based on the data feed formats and build a table definition to match. Trigger an AWS Lambda function on file delivery to start an AWS Glue ETL job to transform the entire record according to the processing and transformation requirements. Define the output format as JSON. Once complete, have the ETL job send the results to another S3 bucket for internal processing.

Create an AWS Glue crawler and custom classifier based upon the data feed formats and build a table definition to match. Perform an Amazon Athena query on file delivery to start an Amazon EMR ETL job to transform the entire record according to the processing and transformation requirements. Define the output format as JSON. Once complete, send the results to another S3 bucket for internal processing and scale down the EMR cluster.

Expert Solution

Questions # 45:

A company hosts a software as a service (SaaS) solution on AWS. The solution has an Amazon API Gateway API that serves an HTTPS endpoint. The API uses AWS Lambda functions for compute. The Lambda functions store data in an Amazon Aurora Serverless VI database.

The company used the AWS Serverless Application Model (AWS SAM) to deploy the solution. The solution extends across multiple Availability Zones and has nodisaster recovery (DR) plan.

A solutions architect must design a DR strategy that can recover the solution in another AWS Region. The solution has an R TO of 5 minutes and an RPO of 1 minute.

What should the solutions architect do to meet these requirements?

Options:

Create a read replica of the Aurora Serverless VI database in the target Region. Use AWS SAM to create a runbook to deploy the solution to the target Region. Promote the read replica to primary in case of disaster.

Change the Aurora Serverless VI database to a standard Aurora MySQL global database that extends across the source Region and the target Region. Use AWS SAM to create a runbook to deploy the solution to the target Region.

Create an Aurora Serverless VI DB cluster that has multiple writer instances in the target Region. Launch the solution in the target Region. Configure the two Regional solutions to work in an active-passive configuration.

Change the Aurora Serverless VI database to a standard Aurora MySQL global database that extends across the source Region and the target Region. Launch the solution in the target Region. Configure the two Regional solutions to work in an active-passive configuration.

Expert Solution

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