HIGH-QUALITY CERTIFICATION SAA-C03 SAMPLE QUESTIONS - 100% PASS-RATE SOURCE OF SAA-C03 EXAM

High-quality Certification SAA-C03 Sample Questions - 100% Pass-Rate Source of SAA-C03 Exam

High-quality Certification SAA-C03 Sample Questions - 100% Pass-Rate Source of SAA-C03 Exam

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100% Pass SAA-C03 - Certification Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam Sample Questions

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Amazon AWS Certified Solutions Architect - Associate (SAA-C03) Exam Sample Questions (Q897-Q902):

NEW QUESTION # 897
A company hosts a three-tier web application in the AWS Cloud. A Multi-AZ Amazon RDS for MySQL server forms the database layer. Amazon ElastiCache forms the cache layer. The company wants a caching strategy that adds or updates data in the cache when a customer adds an item to the database. The data in the cache must always match the data in the database.
Which solution will meet these requirements?

  • A. Implement the adding TTL caching strategy.
  • B. Implement the lazy loading caching strategy
  • C. Implement the write-through caching strategy.
  • D. Implement the AWS AppConfig caching strategy.

Answer: C

Explanation:
A write-through caching strategy adds or updates data in the cache whenever data is written to the database.
This ensures that the data in the cache is always consistent with the data in the database. A write-through caching strategy also reduces the cache miss penalty, as data is always available in the cache when it is requested. However, a write-through caching strategy can increase the write latency, as data has to be written to both the cache and the database. A write-through caching strategy is suitable for applications that require high data consistency and low read latency.
A lazy loading caching strategy only loads data into the cache when it is requested, and updates the cache when there is a cache miss. This can result in stale data in the cache, as data is not updated in the cache when it is changed in the database. A lazy loading caching strategy is suitable for applications that can tolerate some data inconsistency and have a low cache miss rate.
An adding TTL caching strategy assigns a time-to-live (TTL) value to each data item in the cache, and removes the data from the cache when the TTL expires. This can help prevent stale data in the cache, as data is periodically refreshed from the database. However, an adding TTL caching strategy can also increase the cache miss rate, as data can be evicted from the cache before it is requested. An adding TTL caching strategy is suitable for applications that have a high cache hit rate and can tolerate some data inconsistency.
An AWS AppConfig caching strategy is not a valid option, as AWS AppConfig is a service that enables customers to quickly deploy validated configurations to applications of any size and scale. AWS AppConfig does not provide a caching layer for web applications.
References: Caching strategies - Amazon ElastiCache, Caching for high-volume workloads with Amazon ElastiCache


NEW QUESTION # 898
A company is running a microservices application on Amazon EC2 instances. The company wants to migrate the application to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster for scalability. The company must configure the Amazon EKS control plane with endpoint private access set to true and endpoint public access set to false to maintain security compliance The company must also put the data plane in private subnets. However, the company has received error notifications because the node cannot join the cluster.
Which solution will allow the node to join the cluster?

  • A. Grant the required permission in AWS Identity and Access Management (1AM) to the AmazonEKSNodeRole 1AM role.
  • B. Create interface VPC endpoints to allow nodes to access the control plane.
  • C. Allow outbound traffic in the security group of the nodes.
  • D. Recreate nodes in the public subnet Restrict security groups for EC2 nodes

Answer: B

Explanation:
Kubernetes API requests within your cluster's VPC (such as node to control plane communication) use the private VPC endpoint. https://docs.aws.amazon.com/eks/latest/userguide/cluster-endpoint.html


NEW QUESTION # 899
A company's application Is having performance issues The application staleful and needs to complete m-memory tasks on Amazon EC2 instances. The company used AWS CloudFormation to deploy infrastructure and used the M5 EC2 Instance family As traffic increased, the application performance degraded Users are reporting delays when the users attempt to access the application.
Which solution will resolve these issues in the MOST operationally efficient way?

  • A. Replace the EC2 Instances with T3 EC2 instances that run in an Auto Scaling group. Made the changes by using the AWS Management Console.
  • B. Modify the CloudFormation templates to run the EC2 instances in an Auto Scaling group. Increase the desired capacity and the maximum capacity of the Auto Scaling group manually when an increase is necessary
  • C. Modify the CloudFormation templates. Replace the EC2 instances with R5 EC2 instances. Deploy the Amazon CloudWatch agent on the EC2 instances to generate custom application latency metrics for future capacity planning.
  • D. Modify the CloudFormation templates. Replace the EC2 instances with R5 EC2 instances. Use Amazon CloudWatch built-in EC2 memory metrics to track the application performance for future capacity planning.

Answer: C


NEW QUESTION # 900
A solutions architect is using Amazon S3 to design the storage architecture of a new digital media application.
The media files must be resilient to the loss of an Availability Zone Some files are accessed frequently while other files are rarely accessed in an unpredictable pattern. The solutions architect must minimize the costs of storing and retrieving the media files.
Which storage option meets these requirements?

  • A. S3 Standard
  • B. S3 One Zone-Infrequent Access (S3 One Zone-IA)
  • C. S3 Standard-Infrequent Access {S3 Standard-IA)
  • D. S3 Intelligent-Tiering

Answer: D

Explanation:
S3 Intelligent-Tiering - Perfect use case when you don't know the frequency of access or irregular patterns of usage.
Amazon S3 offers a range of storage classes designed for different use cases. These include S3 Standard for general-purpose storage of frequently accessed data; S3 Intelligent-Tiering for data with unknown or changing access patterns; S3 Standard-Infrequent Access (S3 Standard-IA) and S3 One Zone-Infrequent Access (S3 One Zone-IA) for long-lived, but less frequently accessed data; and Amazon S3 Glacier (S3 Glacier) and Amazon S3 Glacier Deep Archive (S3 Glacier Deep Archive) for long-term archive and digital preservation. If you have data residency requirements that can't be met by an existing AWS Region, you can use the S3 Outposts storage class to store your S3 data on-premises. Amazon S3 also offers capabilities to manage your data throughout its lifecycle. Once an S3 Lifecycle policy is set, your data will automatically transfer to a different storage class without any changes to your application.
https://aws.amazon.com/getting-started/hands-on/getting-started-using-amazon-s3-intelligent-tiering/?nc1=h_ls


NEW QUESTION # 901
A media company has an Amazon ECS Cluster, which uses the Fargate launch type, to host its news website. The application data are all stored in Amazon Keyspaces (for Apache Cassandra) with data-at-rest encryption enabled. The database credentials should be supplied using environment variables, to comply with strict security compliance. As the Solutions Architect, you have to ensure that the credentials are secure and that they cannot be viewed in plaintext on the cluster itself.
Which of the following is the most suitable solution in this scenario that you can implement with minimal effort?

  • A. Use the AWS Systems Manager Parameter Store to keep the database credentials and then encrypt them using AWS KMS. Create an IAM Role for your Amazon ECS task execution role (taskRoleArn) and reference it with your task definition, which allows access to both KMS and the Parameter Store. Within your container definition, specify secrets with the name of the environment variable to set in the container and the full ARN of the Systems Manager Parameter Store parameter containing the sensitive data to present to the container.
  • B. In the ECS task definition file of the ECS Cluster, store the database credentials to Amazon ECS Anywhere to centrally manage these sensitive data and securely transmit it to only those containers that need access to it. Allocate an IAM Role to the cluster to ensure that the passwords are only accessible by the ECS service tasks. Run the AWS IAM Access Analyzer to verify that the credentials can't be viewed in plaintext.
  • C. Store the database credentials in the ECS task definition file of the ECS Cluster and encrypt it with KMS. Store the task definition JSON file in Amazon Quantum Ledger Database (Amazon QLDB). Create an IAM role to the ECS task definition script that allows access to the Amazon QLDB and then pass the -
    -cli-input-json parameter when calling the ECS register-task-definition action. Reference the task definition JSON file in the Amazon QLDB which contains the database credentials.
  • D. Use the AWS Secrets Manager to store the database credentials and then encrypt them using AWS Certificate Manager (ACM). Create a resource-based policy for your Amazon ECS task execution role (taskRoleArn) and reference it with your task definition which allows access to both ACM and AWS Secrets Manager. Within your container definition, specify secrets with the name of the environment variable to set in the container and the full ARN of the Secrets Manager secret which contains the sensitive data, to present to the container.

Answer: A

Explanation:
Amazon ECS enables you to inject sensitive data into your containers by storing your sensitive data in either AWS Secrets Manager secrets or AWS Systems Manager Parameter Store parameters and then referencing them in your container definition. This feature is supported by tasks using both the EC2 and Fargate launch types.
Secrets can be exposed to a container in the following ways:
- To inject sensitive data into your containers as environment variables, use the secrets container definition parameter.
- To reference sensitive information in the log configuration of a container, use the container definition parameter.

Within your container definition, specify secrets with the name of the environment variable to set in the container and the full ARN of either the Secrets Manager secret or Systems Manager Parameter Store parameter containing the sensitive data to present to the container. The parameter that you reference can be from a different Region than the container using it, but must be from within the same account.
Hence, the correct answer is the option that says: Use the AWS Systems Manager Parameter Store to keep the database credentials and then encrypt them using AWS KMS. Create an IAM Role for your Amazon ECS task execution role (taskRoleArn) and reference it with your task definition, which allows access to both KMS and the Parameter Store. Within your container definition, specify secrets with the name of the environment variable to set in the container and the full ARN of the Systems Manager Parameter Store parameter containing the sensitive data to present to the container.
The option that says: In the ECS task definition file of the ECS Cluster, store the database credentials to Amazon ECS Anywhere to centrally manage these sensitive data and securely transmit it to only those containers that need access to it. Allocate an IAM Role to the cluster to ensure that the passwords are only accessible by the ECS service tasks. Run the AWS IAM Access Analyzer to verify that the credentials can't be viewed in plaintext is incorrect. Amazon Elastic Container Service (ECS) Anywhere is just a feature of Amazon ECS that enables you to easily run and manage container workloads on customer-managed infrastructure. This feature is not capable of storing any kind of credentials, let alone centrally manage your sensitive data. The recommended way to secure sensitive data in AWS is either through the use of Secrets Manager or Systems Manager Parameter Store. In addition, the AWS IAM Access Analyzer is primarily used to identify resources in your organization and accounts that are shared with an external entity, as well as to validate your IAM policies. This service can't verify if your database credentials are viewable in plaintext or not.
The option that says: Store the database credentials in the ECS task definition file of the ECS Cluster and encrypt it with KMS. Store the task definition JSON file in Amazon Quantum Ledger Database (Amazon QLDB). Create an IAM role to the ECS task definition script that allows access to the Amazon QLDB and then pass the --cli-input-json parameter when calling the ECS register-task-definition action.
Reference the task definition JSON file in the Amazon QLDB which contains the database credentials is incorrect. Amazon Quantum Ledger Database (QLDB) is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log. This service is not meant to store your sensitive database credentials.
The option that says: Use the AWS Secrets Manager to store the database credentials and then encrypt them using AWS Certificate Manager (ACM). Create a resource-based policy for your Amazon ECS task execution role (taskRoleArn) and reference it with your task definition which allows access to both ACM and AWS Secrets Manager. Within your container definition, specify secrets with the name of the environment variable to set in the container and the full ARN of the Secrets Manager secret which contains the sensitive data, to present to the container is incorrect. Although the use of Secrets Manager in securing sensitive data in ECS is valid, Amazon ECS doesn't support resource-based policies. An example of a resource-based policy is the S3 bucket policy. An ECS task assumes an execution role (IAM role) to be able to call other AWS services like AWS Secrets Manager on your behalf. In addition, you cannot encrypt database credentials using the AWS Certificate Manager (ACM) service. You have to use AWS KMS instead.
References:
https://docs.aws.amazon.com/AmazonECS/latest/developerguide/specifying-sensitive-data.html
https://aws.amazon.com/blogs/mt/the-right-way-to-store-secrets-using-parameter-store/
https://docs.aws.amazon.com/systems-manager/latest/userguide/systems-manager-parameter-store.htm l Check out these Amazon ECS and AWS Systems Manager Cheat Sheets:
https://tutorialsdojo.com/amazon-elastic-container-service-amazon-ecs/ https://tutorialsdojo.com/aws- systems-manager/


NEW QUESTION # 902
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