SAP-C02 Exam Dumps - Amazon Web Services AWS Certified Professional Questions and Answers

https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/AWSHowTo.cloudwatch.html Elastic Beanstalk automatically uses Amazon CloudWatch to help you monitor your application and environment status. You can navigate to the Amazon CloudWatch console to see your dashboard and get an overview of all of your resources as well as your alarms. You can also choose to view more metrics or add custom metrics.

Migrating the containers that run the application to AWS Fargate for Amazon Elastic Container Service (Amazon ECS) will meet the requirement of not administering the Docker hosting environment. AWS Fargate is a serverless compute engine that runs containerswithout requiring any infrastructure management3. Creating an Amazon Elastic File System (Amazon EFS) file system and adding a volume to the Fargate task definition to point to the EFS file system will meet the requirement of low-latency storage that will automatically scale throughput to meet increased demand. Amazon EFS is a fully managed file system service that provides shared access to data from multiple containers, supports NFSv4 protocol, and offers consistent performance and high availability4. Amazon EFS also supports automatic scaling of throughput based on the amount of data stored in the file system5.

https://aws.amazon.com/about-aws/whats-new/2017/11/aws-lambda-supports-traffic-shifting-and-phased-deployments-with-aws-codedeploy/

Option B is correct because creating an IAM role in the application account that has permissions to access the secrets and creating an IAM role in the DBA account that has permissions to assume the role in the application account eliminates the need to manually share the secrets. This approach uses cross-account IAM roles to grant access to the secrets in the application account. The database administrators canassume the role in the application account from their EC2 instance in the DBA account and retrieve the secrets without having to store them locally or share them manually2

Option Ais the most lightweight and scalable approach. By updating the VPC’sDHCP options set, you automatically configure all EC2 instances to use your on-premises NTP server. No extra software or infrastructure is required.

VPC DHCP Options Docs

The correct answer is C. This option uses AWS CloudTrail to create a trail in the organization’s management account that applies to all accounts in the organization. This way, the company can centrally manage and audit all API calls to AWS resources across multiple accounts and regions. The company also needs to create a new Amazon S3 bucket with versioning turned on to store the logs. Versioning helps protect against accidental or malicious deletion of log files by keeping multiple versions of each object in the bucket. The company also needs to enable MFA delete and encryption on the S3 bucket to further enhance the security and durability of the data store.

Option A is incorrect because it uses an existing S3 bucket in the organization’s management account to store the logs. This may not be optimal for regulatory compliance, as the existing bucket may have different permissions, encryption settings, or lifecycle policies than a dedicated bucket for CloudTrail logs.

Option B is incorrect because it requires creating a new CloudTrail trail in each member account of the organization. This adds operational overhead and complexity, as the company would need to manage multiple trails and S3 buckets across multiple accounts and regions.

Option D is incorrect because it requires configuring Amazon SNS to send log-file delivery notifications to an external management system that will track the logs. This adds unnecessary complexity and cost, as CloudTrail already provides log-file integrity validation and log-file digest delivery features that can help verify the authenticity and integrity of log files.

https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_accounts_access.html#orgs_manage_accounts_access-cross-account-role "When you create a member account using the AWS Organizations console, AWS Organizations automatically creates an IAM role named OrganizationAccountAccessRole in the account" you need OrganizationAccountAccessRole in member account to create an read-only role and use role from security team to assume this read-only role.

The workload uses EC2 Spot Instances, which are subject to capacity availability constraints. Using a single instance type significantly increases the risk of launch failures when Spot capacity for that instance type is constrained. This directly impacts application reliability and increases user wait times.

Attribute-based instance type selection allows Auto Scaling to choose from multiple compatible instance types based on defined requirements such as vCPU count, memory, and architecture. This improves the probability that Spot capacity is available at launch time because Auto Scaling can select from a broader pool of instance types instead of a single one.

Option D correctly applies attribute-based instance type selection within a new version of the existing launch template. Auto Scaling groups are designed to work with launch templates, and updating the template version is the modern and recommended approach. This change increases Spot placement flexibility and reliability without altering application behavior or introducing additional infrastructure.

Option A is incorrect because launch configurations are an older construct and do not support attribute-based instance type selection. They are also not recommended for new or updated Auto Scaling designs.

Option B does not address the root cause of Spot launch failures. Simply using a larger instance type may actually reduce available Spot capacity and worsen reliability.

Option C increases the number of placement groups, but placement groups do not solve Spot capacity shortages. They influence instance placement for networking or latency characteristics, not Spot availability across instance types.

Therefore, updating the launch template to use attribute-based instance type selection is the most effective way to improve reliability for a Spot-based Auto Scaling workload.

Comprehensive and Detailed Explanation From Exact Extract:

B is correct because Amazon FSx for Lustre provides a high-performance, POSIX-compliant file system that can be directly linked with Amazon S3 using data repository integration. This allows the EC2-based processing engine (which requires POSIX file operations) to read/write files through a mounted Lustre file system while automatically importing objects from S3 and exporting results back to S3 using Lustre’s S3 integration policies. This satisfies all requirements: POSIX file access, no need to change the application to use the S3 API, and automated synchronization for both inputs and outputs.

Why the other options are incorrect:

A: DataSync is designed for scheduled or task-based data transfers. It does not provide a mounted POSIX file system interface for the application to read/write “in place,” and the “without an agent” requirement is not a fit for an EC2-hosted POSIX workflow that needs continuous file semantics.

C: Amazon EFS is POSIX and mountable, but “data repository associations to S3” is not an EFS capability in the way described. EFS does not provide native bidirectional automatic sync with S3 using import/export policies like FSx for Lustre’s S3 integration.

D: S3 File Gateway provides a file interface backed by S3, but keeping cache coherent with explicit RefreshCache calls is operationally complex and not truly “automatic synchronization” in the sense required. It also introduces caching behaviors that can complicate immediate availability expectations.

The company should create a second target group that is referenced by the ALB. The company should deploy the new logic to EC2 instances in this new target group. The company should update the ALB listener rule to use weighted target groups. The company should configure ALB target group stickiness. This solution will meet the requirements because weighted target groups are a feature that enables you to distribute traffic across multiple target groups using a single listener rule. You can specify a weight for each target group, which determines the percentage of requests that are routed to that target group. For example, if you specify two target groups, each with a weight of 10, each target group receives half the requests1. By creating a second target group and deploying the new logic to EC2 instances in this new target group, the company can have two versions of its business logic running in parallel. By updating the ALB listener rule to use weighted target groups,the company can control how much traffic is sent to each version. By configuring ALB target group stickiness, the company can ensure that a customer uses the same version of the business logic during the testing window. Target group stickiness is a feature that enables you to bind a user’s session to a specific target within a target group for the duration of the session2.

The other options are not correct because:

Creating a second ALB and deploying the new logic to a set of EC2 instances in a new Auto Scaling group would not be as cost-effective or simple as using weighted target groups. A second ALB would incur additional charges and require more configuration and management. Updating the Route 53 record to use weighted routing would not ensure that a customer uses the same version of the business logic during the testing window, as DNS caching could affect how requests are routed.

Creating a new launch configuration for the Auto Scaling group and replacing it on the Auto Scaling group would not allow for gradual traffic shifting between versions. A launch configuration is a template that an Auto Scaling group uses to launch EC2 instances. You can specify information such as the AMI ID, instance type, key pair, security groups, and block device mapping for your instances3. However, replacing the launch configuration on an Auto Scaling group would affect all instances in that group, not just 10% of customers.

Creating a second Auto Scaling group and changing the ALB routing algorithm to least outstanding requests (LOR) would not allow for controlled traffic shifting between versions. A second Auto Scaling group would require more configuration and management. The LOR routing algorithm is a feature that enables you to route traffic based on how quickly targets respond to requests. The load balancer selects a target from the target group with the fewest outstanding requests4. However, this algorithm does not take into account customer sessions or weights.

https://aws.amazon.com/es/blogs/industries/how-to-monitor-alert-and-remediate-non-compliant-hipaa-findings-on-aws/

https://aws.amazon.com/solutions/implementations/git-to-s3-using-webhooks/

https://medium.com/mindorks/building-webhook-is-easy-using-aws-lambda-and-api-gateway-56f5e5c3a596

Because MSK has Maximum number of client connections 1000 per second and the company has 10,000 sensors, the MSK likely will not be able to handle all connectionshttps://docs.aws.amazon.com/msk/latest/developerguide/limits.html

Automating the process of increasing service quotas for Amazon EC2 instances in new AWS accounts with minimal operational overhead can be effectively achieved by using Amazon EventBridge, Amazon SNS, and AWS Lambda. An EventBridge rule can detect the creation of a new account and trigger an SNS topic, which in turn invokes a Lambda function. This function can then programmatically request a service quota increase for EC2 instances using the AWS Service Quotas API. This approach streamlines the process, reduces manual intervention, and ensures that new accounts are automatically configured with the desired service quotas.

Amazon EventBridge Documentation: Provides guidance on setting up event rules for detecting AWS account creation.

AWS Lambda Documentation: Details how to create and configure Lambda functions to perform automated tasks, such as requesting service quota increases.

AWS Service Quotas Documentation: Offers information on managing and requesting increases for AWS service quotas programmatically.

The data scientists’ EC2 instances in a separate account must access S3 data in a controlled way that satisfies the policy: only authorized networks may access the IoT data. “Authorized networks” in this context means traffic must originate from approved VPCs and must not traverse the public internet.

First, traffic from the EC2 instances to S3 must stay on the AWS network without using public endpoints. A gateway VPC endpoint for S3 in the data scientists’ VPC (option A) allows EC2 instances in that VPC to reach S3 over private connectivity. When using a gateway VPC endpoint, the route tables of the subnets associated with the endpoint automatically route S3 traffic through the endpoint. This ensures that access to S3 is from an authorized network (the VPC) instead of from the public internet.

Second, access must be constrained such that only calls made through the intended S3 access mechanism are allowed. The data lake bucket already has an S3 access point. S3 access points can be restricted by policy and can be referenced in bucket policies through the s3:DataAccessPointArn condition key. By using an S3 bucket policy that allows s3:GetObject only when s3:DataAccessPointArn matches the expected access point ARN (option E), the company can enforce that all valid access uses the approved access point configuration. Combined with the access point’s own network configuration and the VPC endpoint, access is limited to authorized networks.

Option B, blocking public access on the access point, is a good general security practice but does not by itself guarantee that access is restricted to authorized VPC networks. The main enforcement must be through VPC endpoints and bucket/access point policies.

Option C denies s3:GetObject when s3:DataAccessPointArn is a valid access point ARN, which is the opposite of what is required. This would prevent intended access via the access point rather than allow it.

Option D is not correct because gateway VPC endpoints for S3 are configured via endpoint associations with route tables, not by directly routing to an access point in the route table. Traffic to S3 is routed to the VPC endpoint, and the endpoint plus S3 policies determine access.

Therefore, creating a gateway VPC endpoint for S3 in the data scientists’ VPC (option A) and using a bucket policy condition on s3:DataAccessPointArn to allow access only through the authorized access point (option E) together meet the requirement of secure, network-restricted access from authorized networks.