SAP-C02 Exam Dumps - AWS Certified Solutions Architect - Professional

The best solution is to provision a new Amazon Elastic File System (Amazon EFS) file system that uses Max I/O performance mode and mount the EFS file system on each EC2 instance in the cluster. Amazon EFS is a fully managed, scalable, and elastic file storage service that supports the POSIX standard and can be accessed by multiple EC2 instances concurrently. Amazon EFS offers two performance modes: General Purpose and Max I/O. Max I/O mode is designed for highly parallelized workloads that can tolerate higher latencies than the General Purpose mode. Max I/O mode provides higher levels of aggregate throughput and operations per second, which are suitable for big data analytics applications. This solution meets all the requirements of the company. References: Amazon EFS Documentation, Amazon EFS performance modes

The correct answer is A.

A. This solution meets the requirements because it allows the company to create different usage plans for each customer, with different request quotas and time periods. The usage plans can be associated with API keys, which can be distributed to the users of each customer. The API Gateway REST API can invoke the Lambda function using a proxy integration, which passes the request data to the function as input and returns the function output as the response.This solution is scalable, secure, and cost-effective12

B. This solution is incorrect because API Gateway HTTP APIs do not support usage plans or API keys.These features are only available for REST APIs3

C. This solution is incorrect because it does not provide a way to enforce request quotas for each customer. Lambda function aliases can be used to create different versions of the function, but they do not have any quota mechanism.Moreover, this solution exposes the Lambda function URLs directly to the customers, which is not secure or recommended4

D. This solution is incorrect because it does not provide a way to differentiate between customers or users. AWS WAF rate-based rules can be used to limit requests based on IP addresses, but they do not support any other criteria such as user agents or headers.Moreover, this solution adds unnecessary complexity and cost by using an ALB and a VPC56

Connect the IoT sensors to AWS IoT Core. Set a rule to invoke an AWS Lambda function to parse the information and save a .csv file to Amazon S3. Use AWS Glue to catalog the files. Use Amazon Athena and Amazon QuickSight for analysis. This solution meets the requirement of faster analysis and cost optimization by using AWS IoT Core to collect data from the IoT sensors in real-time and then using AWS Glue and Amazon Athena for efficient data analysis.

This solution involves connecting the loT sensors to the AWS loT Core, setting a rule to invoke an AWS Lambda function to parse the information, and saving a .csv file to Amazon S3. AWS Glue can be used to catalog the files and Amazon Athena and Amazon QuickSight can be used for analysis. This solution will enable faster and more cost-effective data analysis.

This solution is in line with the official Amazon Textbook and Resources for the AWS Certified Solutions Architect - Professional certification. In particular, the book states that: “AWS IoT Core can be used to ingest and process the data, AWS Lambda can be used to process and transform the data, and Amazon S3 can be used to store the data. AWS Glue can be used to catalog and access the data, Amazon Athena can be used to query the data, and Amazon QuickSight can be used to visualize the data.” (Source:https://d1.awsstatic.com/training-and-certification/docs-sa-pro/AWS_Certified_Solutions_Architect_Professional_Exam_Guide_EN_v1.5.pdf)

The company has many S3 buckets and many identities across multiple AWS accounts. It currently uses S3 bucket policies for granular authorization. As requirements grow, the bucket policies have become very large and have hit the maximum size limits. The company needs a way to express granular, identity-based access to S3 resources without relying on increasingly complex bucket policies.

AWS provides S3 Access Grants to centrally manage S3 data access based on identities. S3 Access Grants integrate with IAM Identity Center and external identity providers such as Microsoft Entra ID (formerly Azure AD). With S3 Access Grants, you define grants that associate specific identities or groups (from IAM Identity Center) with permissions on specific S3 buckets, prefixes, or objects. Access Grants maintain a mapping between identities and S3 resources without requiring large, per-bucket policies.

Option A describes exactly this approach. You create an S3 Access Grant configuration associated with the IAM Identity Center instance that is already integrated with the company’s IdP. You then define S3 Access Grants for the various user groups according to business requirements, specifying the appropriate S3 buckets and prefixes. When users access S3 through AWS tools that support S3 Access Grants, temporary credentials are issued that reflect the grants. This centralizes authorization management, reduces the size and complexity of S3 bucket policies, and minimizes operational overhead because you manage permissions per identity group rather than constantly editing long bucket policies.

Option B uses S3 access points and Object Lambda Access Points with a Lambda function for data filtering. This is more suitable for content transformation or redaction rather than primary authorization management. It adds operational complexity by requiring custom Lambda code and Object Lambda configuration, and it does not directly solve the problem of large bucket policies for fine-grained permissions.

Option C uses per-bucket S3 access points with attached policies. While access points can simplify some aspects of access control and allow per-application policies, using many access points with detailed policies can still lead to significant policy complexity. It also does not take advantage of the existing IAM Identity Center integration and does not centrally align permissions with identity groups.

Option D uses AWS Organizations service control policies (SCPs). SCPs are intended to define high-level guardrails and maximum permissions at the account or organizational unit level, not detailed, per-bucket or per-prefix access control for individual users or groups. Using SCPs to express granular S3 bucket permissions would be complex, hard to maintain, and not aligned with the purpose of SCPs.

Therefore, using S3 Access Grants integrated with IAM Identity Center (option A) provides a centralized, identity-aware, low-overhead way to manage granular S3 access without hitting S3 bucket policy size limits.

The best solution is to store the database credentials for both environments in AWS Secrets Manager with distinct key entry for the QA environment and the production environment. AWS Secrets Manager is a web service that can securely store, manage, and retrieve secrets, such as database credentials. AWS Secrets Manager also supports automatic rotation of secrets by using Lambda functions or built-in rotation templates. By storing the database credentials for both environments in AWS Secrets Manager, the company can avoid exposing credentials within application code and rotate passwords automatically. By providing a reference to the Secrets Manager key as an environment variable for the Lambda functions, the company can easily access the credentials from the code by using the AWS SDK. This solution meets all the requirements of the company.

https://aws.amazon.com/blogs/database/amazon-dynamodb-auto-scaling-performance-and-cost-optimization-at-any-scale/ " As you can see, there are compelling reasons to use DynamoDB auto scaling with actively changing traffic. Auto scaling responds quickly and simplifies capacity management, which lowers costs by scaling your table’s provisioned capacity and reducing operational overhead. "

" This operation can be called only from the organization ' s management account. Member accounts can remove themselves with LeaveOrganization instead. " https://docs.aws.amazon.com/organizations/latest/APIReference/API_RemoveAccountFromOrganization.html