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最新的 AWS Certified Solutions Architect SAA-C03 免費考試真題 (Q817-Q822):

問題 #817
A company's reporting system delivers hundreds of .csv files to an Amazon S3 bucket each day. The company must convert these files to Apache Parquet format and must store the files in a transformed data bucket.
Which solution will meet these requirements with the LEAST development effort?

A. Create an Amazon EMR cluster with Apache Spark installed. Write a Spark application to transform the data. Use EMR File System (EMRFS) to write files to the transformed data bucket.
B. Use AWS Batch to create a job definition with Bash syntax to transform the data and output the data to the transformed data bucket. Use the job definition to submit a job. Specify an array job as the job type.
C. Create an AWS Lambda function to transform the data and output the data to the transformed data bucket. Configure an event notification for the S3 bucket. Specify the Lambda function as the destination for the event notification.
D. Create an AWS Glue crawler to discover the data. Create an AWS Glue extract, transform, and load (ETL) job to transform the data. Specify the transformed data bucket in the output step.

答案：D

解題說明：
Explanation
https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/three-aws-glue-etl-job-types-for-converting-d

問題 #818
A company that uses AWS needs a solution to predict the resources needed for manufacturing processes each month. The solution must use historical values that are currently stored in an Amazon S3 bucket The company has no machine learning (ML) experience and wants to use a managed service for the training and predictions.
Which combination of steps will meet these requirements? (Select TWO.)

A. Train an Amazon Forecast predictor by using the historical data in the S3 bucket.
B. Deploy an Amazon SageMaker model. Create a SageMaker endpoint for inference.
C. Use Amazon SageMaker to train a model by using the historical data in the S3 bucket.
D. Configure an AWS Lambda function with a function URL that uses Amazon SageMaker endpoints to create predictions based on the inputs.
E. Configure an AWS Lambda function with a function URL that uses an Amazon Forecast predictor to create a prediction based on the inputs.

答案：A,C

解題說明：
To predict the resources needed for manufacturing processes each month using historical values that are currently stored in an Amazon S3 bucket, a solutions architect should use Amazon SageMaker to train a model by using the historical data in the S3 bucket, and deploy an Amazon SageMaker model and create a SageMaker endpoint for inference. Amazon SageMaker is a fully managed service that provides an easy way to build, train, and deploy machine learning (ML) models. The solutions architect can use the built-in algorithms or frameworks provided by SageMaker, or bring their own custom code, to train a model using the historical data in the S3 bucket as input. The trained model can then be deployed to a SageMaker endpoint, which is a scalable and secure web service that can handle requests for predictions from the application. The solutions architect does not need to have any ML experience or manage any infrastructure to use SageMaker.

問題 #819
[Design High-Performing Architectures]
A company has deployed a web application on AWS. The company hosts the backend database on Amazon RDS for MySQL with a primary DB instance and five read replicas to supportscallng needs. The read replicas must lag no more than 1 second behind the primary DB instance. The database routinely runs scheduled stored procedures.
As traffic on the website increases, the replicas experince addtional lag during periods of peak load. A solutions architect must reduce the replication lag as much as possible. The solutin architect must minimize changes to the application code and must minimize ongoing operational overhead.
Which solution will meet these requirements?

A. Migrate the database to Amazon DynamicDB provision a large number of read capacity units(RCUs) to support the required throught, and configure on-demand capacity scaling. Replace the store procedures with DynamoDB streams
B. Migrate the database to a MySQL database that runs on Amazon EC2 instances. Choose large, compute optimized EC2 instances for all replica nodes. Maintain the stored procedures on the EC2 instances.
C. Deploy an Amazon ElasticCache for Redis cluster in front of the database. Modify the application to check the cache before the applicatin queries the database. Replace the stored procedures with AWS Lambda functions.
D. Migrate the database to Amazon Aurora MySQL. Replace the read replicas with Aurora Replicas, and configure Aurora Auto Scaling. Replace the store procedures with Aurora MySQL native functions.

答案：D

解題說明：
Option A is the most appropriate solution for reducing replication lag without significant changes to the application code and minimizing ongoing operational overhead. Migrating the database to Amazon Aurora MySQL allows for improved replication performance and higher scalability compared to Amazon RDS for MySQL. Aurora Replicas provide faster replication, reducing the replication lag, and Aurora Auto Scaling ensures that there are enough Aurora Replicas to handle the incoming traffic. Additionally, Aurora MySQL native functions can replace the stored procedures, reducing the load on the database and improving performance.

問題 #820
A company runs an on-premises application on a Kubernetes cluster. The company recently added millions of new customers. The company's existing on-premises infrastructure is unable to handle the large number of new customers. The company needs to migrate the on-premises application to the AWS Cloud.
The company will migrate to an Amazon Elastic Kubernetes Service (Amazon EKS) cluster. The company does not want to manage the underlying compute infrastructure for the new architecture on AWS.
Which solution will meet these requirements with the LEAST operational overhead?

A. Use AWS Fargate to supply compute capacity. Create a Fargate profile. Use the Fargate profile to deploy the application.
B. Use managed node groups with Karpenter to supply compute capacity. Deploy the application to the new EKS cluster.
C. Use managed node groups to supply compute capacity. Deploy the application to the new EKS cluster.
D. Use a self-managed node to supply compute capacity. Deploy the application to the new EKS cluster.

答案：A

解題說明：
AWS Fargate is a serverless compute engine for containers that works with Amazon EKS. With Fargate, you do not need to provision or manage EC2 instances or clusters. You simply define and deploy your pods, and Fargate automatically launches the required compute resources. This results in the lowest operational overhead because AWS manages the infrastructure. Fargate profiles allow you to specify which pods run on Fargate.
AWS Documentation Extract:
"AWS Fargate is a serverless, pay-as-you-go compute engine that lets you focus on building applications without managing servers. With Amazon EKS and Fargate, you only need to define your application's pods; Fargate provisions and manages the required compute resources for you." (Source: Amazon EKS documentation, AWS Fargate integration) Other options:
A: Self-managed nodes require you to manage EC2 instances.
B: Managed node groups reduce some overhead, but you are still responsible for patching and managing the EC2 instances.
D: Managed node groups with Karpenter automate scaling but do not remove the need to manage underlying instances.
Reference: AWS Certified Solutions Architect - Official Study Guide, EKS and Fargate Section.

問題 #821
A company wants to improve the availability and performance of its hybrid application. The application consists of a stateful TCP-based workload hosted on Amazon EC2 instances in different AWS Regions and a stateless UDP-based workload hosted on premises.
Which combination of actions should a solutions architect take to improve availability and performance?
(Select TWO.)

A. Configure a Network Load Balancer in each Region to address the EC2 endpoints. Configure a Network Load Balancer in each Region that routes to the on-premises endpoints.
B. Create an accelerator using AWS Global Accelerator. Add the load balancers as endpoints.
C. Configure a Network Load Balancer in each Region to address the EC2 endpoints. Configure an Application Load Balancer in each Region that routes to the on-premises endpoints.
D. Create an Amazon CloudFront distribution with an origin that uses Amazon Route 53 latency-based routing to route requests to the load balancers.
E. Configure two Application Load Balancers in each Region. The first will route to the EC2 endpoints.
and the second will route lo the on-premises endpoints.

答案：A,B

解題說明：
For improving availability and performance of the hybrid application, the following solutions are optimal:
AWS Global Accelerator (Option A): Global Accelerator provides high availability and improves performance by using the AWS global network to route user traffic to the nearest healthy endpoint (across AWS Regions). By adding the Network Load Balancers as endpoints, Global Accelerator ensures that traffic is routed efficiently to the closest endpoint, improving both availability and performance.
Network Load Balancer (Option D): The stateful TCP-based workload hosted on Amazon EC2 instances and the stateless UDP-based workload hosted on-premises are best served by Network Load Balancers (NLBs). NLBs are designed to handle TCP and UDP traffic with ultra-low latency and can route traffic to both EC2 and on-premises endpoints.
Option B (CloudFront and Route 53): CloudFront is better suited for HTTP/HTTPS workloads, not for TCP
/UDP-based applications.
Option C (ALB): Application Load Balancers do not support the stateless UDP-based workload, making NLBs the better choice for both TCP and UDP.
AWS References:
AWS Global Accelerator
Network Load Balancer

問題 #822
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