Free Amazon Web Services SAA-C03 Practice Exam with Questions & Answers | Set: 4

Deploy Amazon API Gateway as an HTTPS endpoint and AWS Lambda to process and save the messages to an Amazon DynamoDB table. This option provides a highly available and scalable solution that can easily handle large amounts of data. It also integrates with other AWS services, making it easier to analyze and visualize the data for the security team.

The best option is to use AWS CloudTrail to find the desired information. AWS CloudTrail is a service that enables governance, compliance, operational auditing, and risk auditing of AWS account activities. CloudTrail can be used to log all changes made to resources in an AWS account, including changes made by IAM users, EC2 instances, AWS management console, andother AWS services. By using CloudTrail, the solutions architect can identify the IAM user who made the configuration changes to the security group rules.

UESTION NO: 549

A company has a three-tier environment on AWS that ingests sensor data from its users' devices The traffic flows through a Network Load Balancer (NIB) then to Amazon EC2 instances for the web tier and finally to EC2 instances for the application tier that makes database calls

What should a solutions architect do to improve the security of data in transit to the web tier?

A. Configure a TLS listener and add the server certificate on the NLB

B. Configure AWS Shield Advanced and enable AWS WAF on the NLB

C. Change the load balancer to an Application Load Balancer and attach AWS WAF to it

D. Encrypt the Amazon Elastic Block Store (Amazon EBS) volume on the EC2 instances using AWS Key Management Service (AWS KMS)

Answer: A

A: How do you protect your data in transit?

Best Practices:

Implement secure key and certificate management: Store encryption keys and certificates securely and rotate them at appropriate time intervals while applying strict access control; for example, by using a certificate management service, such as AWS Certificate Manager (ACM).

Enforce encryption in transit: Enforce your defined encryption requirements based on appropriate standards and recommendations to help you meet your organizational, legal, and compliance requirements.

Automate detection of unintended data access: Use tools such as GuardDuty to automatically detect attempts to move data outside of defined boundaries based on data classification level, for example, to detect a trojan that is copying data to an unknown or untrusted network using the DNS protocol.

Authenticate network communications: Verify the identity of communications by using protocols that support authentication, such as Transport Layer Security (TLS) or IPsec.

https://wa.aws.amazon.com/wat.question.SEC_9.en.html

This answer is correct because it provides a resilient and durable replacement for the on-premises file share that is compatible with Windows IIS web servers. Amazon FSx for Windows File Server is a fully managed service that provides shared file storage built on Windows Server. It supports the SMB protocol and integrates with Microsoft Active Directory, which enables seamless access and authentication for Windows-based applications. Amazon FSx for Windows File Server also offers the following benefits:

Resilience: Amazon FSx for Windows File Server can be deployed in multiple Availability Zones, which provides high availability and failover protection. It also supports automatic backups and restores, as well as self-healing features that detect and correct issues.

Durability: Amazon FSx for Windows File Server replicates data within and across Availability Zones, and stores data on highly durable storage devices. It also supports encryption at rest and in transit, as well as file access auditing and data deduplication.

Performance: Amazon FSx for Windows File Server delivers consistent sub-millisecond latencies and high throughput for file operations. It also supports SSD storage, native Windows features such as Distributed File System (DFS) Namespaces and Replication, and user-driven performance scaling.

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

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

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

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

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

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

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

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

https://docs.aws.amazon.com/AmazonECS/latest/developerguide/Welcome.html

1. Relational database: RDS

2. Container-based applications: ECS

"Amazon ECS enables you to launch and stop your container-based applications by using simple API calls. You can also retrieve the state of your cluster from a centralized service and have access to many familiar Amazon EC2 features."

3. Little manual intervention: Fargate

You can run your tasks and services on a serverless infrastructure that is managed by AWS Fargate. Alternatively, for more control over your infrastructure, you can run your tasks and services on a cluster of Amazon EC2 instances that you manage.

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.

AWS WAF is a web application firewall that lets you monitor the HTTP and HTTPS requests that are forwarded to your protected web application resources. You can protect the following resource types:

Amazon CloudFront distribution

Amazon API Gateway REST API

Application Load Balancer

AWS AppSync GraphQL API

Amazon Cognito user pool

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

• Launching instances within a single AZ and using a cluster placement group provides the lowest network latency and highest bandwidth between instances. This maximizes performance for an in-memory database and high-throughput application.

• Communications between instances in the same AZ and placement group are free, minimizing data transfer charges. Inter-AZ and public IP traffic can incur charges.

• A cluster placement group enables the instances to be placed close together within the AZ, allowing the high network throughput required. Partition groups span AZs, reducing bandwidth.

• Auto Scaling across zones could launch instances in AZs that increase data transfer charges. It may reduce network throughput, impacting performance.

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

This option is the most efficient because it uses AWS Key Management Service (AWS KMS), which is a service that makes it easy for you to create and manage cryptographickeys and control their use across a wide range of AWS services and with your applications running on AWS1. It also uses AWS KMS to encrypt the EBS volumes and Aurora database storage at rest, which provides data protection by encrypting your data with encryption keys that youmanage23. It also uses AWS Certificate Manager (ACM), which is a service that lets you easily provision, manage, and deploy public and private Secure Sockets Layer/Transport Layer Security (SSL/TLS) certificates for use with AWS services and your internal connected resources. It also attaches an ACM certificate to the ALB to encrypt data in transit, which provides data protection by enabling SSL/TLS encryption for connections between clients and the load balancer. Thissolution meets the requirement of encrypting all data for the application at rest and in transit. Option A is less efficient because it uses AWS KMS certificates on the ALB to encrypt data in transit, which is not possible as AWS KMS does not provide certificates but only keys. It also uses AWS Certificate Manager (ACM) to encrypt the EBS volumes and Aurora database storage at rest, which is not possible as ACM does not provide encryption but only certificates. Option B is less efficient because it uses the AWS root account to log in to the AWS Management Console, which is not recommended as it has unrestricted access to all resources in your account. It also uploads the company’s encryption certificates, which is not necessary as ACM can provide certificates for free. It also selects the option to turn on encryption for all data at rest and in transit for the account, which is not possible as encryption settings are specific to each service and resource. Option D is less efficient because it uses BitLocker to encrypt all data at rest, which is a Windows feature that provides encryption for volumes on Windows servers. However, this does not provide encryption for Aurora database storage at rest, as Auroraruns on Linux servers. It also imports the company’s TLS certificate keys to AWS KMS, which is not necessary as ACM can provide certificates for free. It also attaches the KMS keys to the ALB to encrypt data in transit, which is not possible as ALB requires certificates and not keys.

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

Using AWS Lambda with Amazon API Gateway - AWS Lambda

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

AWS Lambda FAQs

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

https://aws.amazon.com/blogs/networking-and-content-delivery/adding-http-security-headers-using-lambdaedge-and-amazon-cloudfront/

Amazon CloudFront is a global content delivery network (CDN) service that can securely deliver web content, videos, and APIs at scale. It integrates with Cognito for authentication and with Lambda@Edge for authorization, making it an ideal choice for serving web content globally. Lambda@Edge is a service that lets you run AWS Lambda functions globally closer to users, providing lower latency and faster response times. It can also handle authorization logic at the edge to secure content in CloudFront. For this scenario, Lambda@Edge can provide authorization for the web application while leveraging the low-latency benefit of running at the edge.

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 trackingscaling policy issuitable 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.

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

This option is the most efficient because it uses provisioned mode, which is a read/write capacity mode for processing reads and writes on your tables that lets you specify how much read and writethroughput you expect your application to perform1. It also specifies the read capacity units (RCUs) and write capacity units (WCUs), which are the amount of data your application needs to read or write per second. It also meets the requirement of staying at or below its forecasted budget for DynamoDB, as provisioned mode has lower costs than on-demand mode for predictable workloads. This solution meets the requirement of collecting data from a large number of participants who use wearable devices with a constant and predictable data workload. Option A is less efficient because it uses provisioned mode and DynamoDB Standard-Infrequent Access (DynamoDB Standard-IA), which is a storage class for infrequently accessed items that require milliseconds latency2. However, this does not meet the requirement of collecting data from a large number of participants who use wearable devices with a constant and predictable data workload, as DynamoDB Standard-IA is more suitable for items that are accessed less frequently than once every 30 days. Option C is less efficient because it uses on-demand mode, which is a read/write capacity mode that lets you pay only for what you use by automatically adjusting your table’s capacity in response to changing demand3. However, this does not meet the requirement of staying at or below its forecasted budget for DynamoDB, ason-demand mode has higher costs than provisioned mode for predictable workloads. Option D is less efficient because it uses on-demand mode and specifies the RCUs and WCUs with reserved capacity, which is a way to reserve read and write capacity for your tables in exchange for discounted hourly rates. However, this does not meet the requirement of staying at or below its forecasted budget for DynamoDB, as on-demand mode has higher costs than provisioned mode for predictable workloads. Also, specifying RCUs and WCUs with reserved capacity is not possible with on-demand mode, as it only applies to provisioned mode.

Auto scaling storage RDS will ease storage issues and migrating Oracle Pl/Sql to Aurora is cumbersome. Also Aurora has auto storage scaling by default.https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PIOPS.StorageTypes.html#USER_PIOPS.Autoscaling

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.

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

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

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

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

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