Practice Free SAA-C03 Exam Online Questions
A company is planning to use an Amazon DynamoDB table for data storage. The company is concerned about cost optimization. The table will not be used on most mornings. In the evenings, the read and write traffic will often be unpredictable. When traffic spikes occur, they will happen very quickly.
What should a solutions architect recommend?
- A . Create a DynamoDB table in on-demand capacity mode.
- B . Create a DynamoDB table with a global secondary index
- C . Create a DynamoDB table with provisioned capacity and auto scaling.
- D . Create a DynamoDB table in provisioned capacity mode, and configure it as a global table
A
Explanation:
Provisioned capacity is best if you have relatively predictable application traffic, run applications whose traffic is consistent, and ramps up or down gradually. On-demand capacity mode is best when you have unknown workloads, unpredictable application traffic and also if you only want to pay exactly for what you use. The on-demand pricing model is ideal for bursty, new, or unpredictable workloads whose traffic can spike in seconds or minutes, and when under-provisioned capacity would impact the user experience. https://docs.aws.amazon.com/wellarchitected/latest/serverless-applications-lens/capacity.html
A company hosts more than 300 global websites and applications. The company requires a platform to analyze more than 30 TB of clickstream data each day.
What should a solutions architect do to transmit and process the clickstream data?
- A . Design an AWS Data Pipeline to archive the data to an Amazon S3 bucket and run an Amazon EMR duster with the data to generate analytics
- B . Create an Auto Scaling group of Amazon EC2 instances to process the data and send it to an Amazon S3 data lake for Amazon Redshift to use tor analysis
- C . Cache the data to Amazon CloudFron: Store the data in an Amazon S3 bucket When an object is added to the S3 bucket, run an AWS Lambda function to process the data tor analysis.
- D . Collect the data from Amazon Kinesis Data Streams. Use Amazon Kinesis Data Firehose to transmit the data to an Amazon S3 data lake Load the data in Amazon Redshift for analysis
D
Explanation:
https://aws.amazon.com/es/blogs/big-data/real-time-analytics-with-amazon-redshift-streaming-ingestion/
A company stores call transcript files on a monthly basis. Users access the files randomly within 1 year of the call, but users access the files infrequently after 1 year. The company wants to optimize its solution by giving users the ability to query and retrieve files that are less than 1-year-old as quickly as possible. A delay in retrieving older files is acceptable.
Which solution will meet these requirements MOST cost-effectively?
- A . Store individual files with tags in Amazon S3 Glacier Instant Retrieval. Query the tags to retrieve the files from S3 Glacier Instant Retrieval.
- B . Store individual files in Amazon S3 Intelligent-Tiering. Use S3 Lifecycle policies to move the files to S3 Glacier Flexible Retrieval after 1 year. Query and retrieve the files that are in Amazon S3 by using Amazon Athena. Query and retrieve the files that are in S3 Glacier by using S3 Glacier Select.
- C . Store individual files with tags in Amazon S3 Standard storage. Store search metadata for each archive in Amazon S3 Standard storage. Use S3 Lifecycle policies to move the files to S3 Glacier Instant Retrieval after 1 year. Query and retrieve the files by searching for metadata from Amazon S3.
- D . Store individual files in Amazon S3 Standard storage. Use S3 Lifecycle policies to move the files to S3 Glacier Deep Archive after 1 year. Store search metadata in Amazon RDS. Query the files from Amazon RDS. Retrieve the files from S3 Glacier Deep Archive.
B
Explanation:
"For archive data that needs immediate access, such as medical images, news media assets, or genomics data, choose the S3 Glacier Instant Retrieval storage class, an archive storage class that delivers the lowest cost storage with milliseconds retrieval. For archive data that does not require immediate access but needs the flexibility to retrieve large sets of data at no cost, such as backup or disaster recovery use cases, choose S3 Glacier Flexible Retrieval (formerly S3 Glacier), with retrieval in minutes or free bulk retrievals in 5-12 hours." https://aws.amazon.com/about-aws/whats-new/2021/11/amazon-s3-glacier-instant-retrieval-storage-class/
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 . Recreate nodes in the public subnet Restrict security groups for EC2 nodes
- D . Allow outbound traffic in the security group of the nodes.
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
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 . 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.
- C . 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.
- D . 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.
B
Explanation:
https://docs.aws.amazon.com/prescriptive-guidance/latest/patterns/three-aws-glue-etl-job-types-for-converting-data-to-apache-parquet.html
AWS Glue is a serverless, fully managed ETL (Extract, Transform, and Load) service. It is specifically designed for data transformation tasks such as converting .csv files to Apache Parquet format. Using AWS Glue requires minimal development effort because it includes prebuilt transformations and integrates seamlessly with Amazon S3.
Option A: While Amazon EMR with Apache Spark offers extensive flexibility, it requires setting up and managing a cluster, writing custom Spark code, and handling resource scaling, which increases development effort compared to AWS Glue.
Option C: AWS Batch requires creating job definitions, specifying execution environments, and potentially writing custom scripts for the transformation process, which involves more setup compared to AWS Glue.
Option D: AWS Lambda could handle the transformation but is better suited for smaller-scale processing or real-time transformations. Handling hundreds of files daily with Lambda would require more complex orchestration and is not the most efficient solution for this scale of batch processing.
AWS Documentation
Reference: AWS Glue Overview
Transforming Data Using AWS Glue
A company hosts a frontend application that uses an Amazon API Gateway API backend that is integrated with AWS Lambda When the API receives requests, the Lambda function loads many libranes Then the Lambda function connects to an Amazon RDS database processes the data and returns the data to the frontend application. The company wants to ensure that response latency is as low as possible for all its users with the fewest number of changes to the company’s operations
Which solution will meet these requirements?
- A . Establish a connection between the frontend application and the database to make queries faster by bypassing the API
- B . Configure provisioned concurrency for the Lambda function that handles the requests
- C . Cache the results of the queries in Amazon S3 for faster retneval of similar datasets.
- D . Increase the size of the database to increase the number of connections Lambda can establish at one time
B
Explanation:
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.
https://docs.aws.amazon.com/lambda/latest/dg/services-apigateway.html
Using AWS Lambda with Amazon API Gateway – AWS Lambda https://docs.aws.amazon.com/lambda/latest/dg/services-apigateway.html
https://aws.amazon.com/lambda/faqs/
AWS Lambda FAQs
https://aws.amazon.com/lambda/faqs/
A global marketing company has applications that run in the ap-southeast-2 Region and the eu-west-
1 Region. Applications that run in a VPC in eu-west-1 need to communicate securely with databases that run in a VPC in ap-southeast-2.
Which network design will meet these requirements?
- A . Create a VPC peering connection between the eu-west-1 VPC and the ap-southeast-2 VPC. Create an inbound rule in the eu-west-1 application security group that allows traffic from the database server IP addresses in the ap-southeast-2 security group.
- B . Configure a VPC peering connection between the ap-southeast-2 VPC and the eu-west-1 VPC. Update the subnet route tables. Create an inbound rule in the ap-southeast-2 database security group that references the security group ID of the application servers in eu-west-1.
- C . Configure a VPC peering connection between the ap-southeast-2 VPC and the eu-west-1 VPC. Update the subnet route tables Create an inbound rule in the ap-southeast-2 database security group that allows traffic from the eu-west-1 application server IP addresses.
- D . Create a transit gateway with a peering attachment between the eu-west-1 VPC and the ap-southeast-2 VPC. After the transit gateways are properly peered and routing is configured, create an inbound rule in the database security group that references the security group ID of the application servers in eu-west-1.
C
Explanation:
"You cannot reference the security group of a peer VPC that’s in a different Region. Instead, use the CIDR block of the peer VPC." https://docs.aws.amazon.com/vpc/latest/peering/vpc-peering-security-groups.html
A company currently stores 5 TB of data in on-premises block storage systems. The company’s current storage solution provides limited space for additional data. The company runs applications on premises that must be able to retrieve frequently accessed data with low latency. The company requires a cloud-based storage solution.
Which solution will meet these requirements with the MOST operational efficiency?
- A . Use Amazon S3 File Gateway Integrate S3 File Gateway with the on-premises applications to store and directly retrieve files by using the SMB file system.
- B . Use an AWS Storage Gateway Volume Gateway with cached volumes as iSCSt targets.
- C . Use an AWS Storage Gateway Volume Gateway with stored volumes as iSCSI targets.
- D . Use an AWS Storage Gateway Tape Gateway. Integrate Tape Gateway with the on-premises applications to store virtual tapes in Amazon S3.
B
Explanation:
The company needs a cloud-based storage solution for frequently accessed data with low latency, while retaining their current on-premises infrastructure for some data storage. AWS Storage Gateway’s Volume Gateway with cached volumes is the most appropriate solution for this scenario.
AWS Storage Gateway – Volume Gateway (Cached Volumes):
Volume Gateway with cached volumes allows you to store frequently accessed data in the AWS Cloud while keeping the most recently accessed data cached locally on-premises. This ensures low-latency access to active data while providing scalability for the rest of the data in the cloud.
The cached volume option stores the primary data in Amazon S3 but caches frequently accessed data locally, ensuring fast access. This configuration is well-suited for applications that require fast access to frequently used data but can tolerate cloud-based storage for the rest.
Since the company is facing limited on-premises storage, cached volumes provide an ideal solution, as they reduce the need for additional on-premises storage infrastructure.
Why Not the Other Options?
Option A (S3 File Gateway): S3 File Gateway provides a file-based interface (SMB/NFS) for storing data directly in S3. While it is great for file storage, the company’s need for block-level storage with iSCSI targets makes Volume Gateway a better fit.
Option C (Volume Gateway – Stored Volumes): Stored volumes keep all the data on-premises and asynchronously back up to AWS. This would not address the company’s storage limitations since they would still need substantial on-premises storage.
Option D (Tape Gateway): Tape Gateway is designed for archiving and backup, not for frequently accessed low-latency data.
AWS
Reference: AWS Storage Gateway – Volume Gateway
A company is migrating its databases to Amazon RDS for PostgreSQL. The company is migrating its applications to Amazon EC2 instances. The company wants to optimize costs for long-running workloads.
Which solution will meet this requirement MOST cost-effectively?
- A . Use On-Demand Instances for the Amazon RDS for PostgreSQL workloads. Purchase a 1 year Compute Savings Plan with the No Upfront option for the EC2 instances.
- B . Purchase Reserved Instances for a 1 year term with the No Upfront option for the Amazon RDS for PostgreSQL workloads. Purchase a 1 year EC2 Instance Savings Plan with the No Upfront option for the EC2 instances.
- C . Purchase Reserved Instances for a 1 year term with the Partial Upfront option for the Amazon RDS for PostgreSQL workloads. Purchase a 1 year EC2 Instance Savings Plan with the Partial Upfront option for the EC2 instances.
- D . Purchase Reserved Instances for a 3 year term with the All Upfront option for the Amazon RDS for PostgreSQL workloads. Purchase a 3 year EC2 Instance Savings Plan with the All Upfront option for the EC2 instances.
A company has a production workload that is spread across different AWS accounts in various AWS Regions. The company uses AWS Cost Explorer to continuously monitor costs and usage. The company wants to receive notifications when the cost and usage spending of the workload is unusual.
Which combination of steps will meet these requirements? (Select TWO.)
- A . In the AWS accounts where the production workload is running, create a linked account budget by using Cost Explorer in the AWS Cost Management console
- B . In ys AWS accounts where the production workload is running, create a linked account monitor by using AWS Cost Anomaly Detection in the AWS Cost Management console
- C . In the AWS accounts where the production workload is running, create a Cost and Usage Report by using Cost Anomaly Detection in the AWS Cost Management console.
- D . Create a report and send email messages to notify the company on a weekly basis.
- E . Create a subscription with the required threshold and notify the company by using weekly summaries.
BE
Explanation:
AWS Cost Anomaly Detection allows you to create monitors that track the cost and usage of your AWS resources and alert you when there is an unusual spending pattern. You can create monitors based on different dimensions, such as AWS services, accounts, tags, or cost categories. You can also create alert subscriptions that notify you by email or Amazon SNS when an anomaly is detected. You can specify the threshold and frequency of the alerts, and choose to receive weekly summaries of your anomalies.
Reference URLs:
1 https://aws.amazon.com/aws-cost-management/aws-cost-anomaly-detection/
2 https://docs.aws.amazon.com/cost-management/latest/userguide/getting-started-ad.html
3 https://docs.aws.amazon.com/cost-management/latest/userguide/manage-ad.html