Practice Free SAA-C03 Exam Online Questions
A company is running a batch application on Amazon EC2 instances. The application consists of a backend with multiple Amazon RDS databases. The application is causing a high number of leads on the databases. A solutions architect must reduce the number of database reads while ensuring high availability.
What should the solutions architect do to meet this requirement?
- A . Add Amazon RDS read replicas
- B . Use Amazon ElastCache for Redis
- C . Use Amazon Route 53 DNS caching
- D . Use Amazon ElastiCache for Memcached
A
Explanation:
This solution meets the requirement of reducing the number of database reads while ensuring high availability for a batch application that consists of a backend with multiple Amazon RDS databases. Amazon RDS read replicas are copies of the primary database instance that can serve read-only traffic. You can create one or more read replicas for a primary database instance and connect to them using a special endpoint. Read replicas can improve the performance and availability of your application by offloading read queries from the primary database instance.
Option B is incorrect because using Amazon ElastiCache for Redis can provide a fast, in-memory data store that can cache frequently accessed data, but it does not support replication from Amazon RDS
databases.
Option C is incorrect because using Amazon Route 53 DNS caching can improve the performance and availability of DNS queries, but it does not reduce the number of database reads.
Option D is incorrect because using Amazon ElastiCache for Memcached can provide a fast, in-memory data store that can cache frequently accessed data, but it does not support replication from Amazon RDS databases.
Reference: https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_ReadRepl.html
A company wants to run its critical applications in containers to meet requirements tor scalability and availability. The company prefers to focus on maintenance of the critical applications. The company does not want to be responsible for provisioning and managing the underlying infrastructure that runs the containerized workload
What should a solutions architect do to meet those requirements?
- A . Use Amazon EC2 Instances, and Install Docker on the Instances
- B . Use Amazon Elastic Container Service (Amazon ECS) on Amazon EC2 worker nodes
- C . Use Amazon Elastic Container Service (Amazon ECS) on AWS Fargate
- D . Use Amazon EC2 instances from an Amazon Elastic Container Service (Amazon ECS)-op6mized Amazon Machine Image (AMI).
C
Explanation:
using AWS ECS on AWS Fargate since they requirements are for scalability and availability without having to provision and manage the underlying infrastructure to run the containerized workload. https://docs.aws.amazon.com/AmazonECS/latest/userguide/what-is-fargate.html
A company has an application that processes customer orders. The company hosts the application on an Amazon EC2 instance that saves the orders to an Amazon Aurora database. Occasionally when traffic is high: the workload does not process orders fast enough.
What should a solutions architect do to write the orders reliably to the database as quickly as possible?
- A . Increase the instance size of the EC2 instance when traffic is high. Write orders to Amazon Simple Notification Service (Amazon SNS). Subscribe the database endpoint to the SNS topic.
- B . Write orders to an Amazon Simple Queue Service (Amazon SQS) queue. Use EC2 instances in an Auto Scaling group behind an Application Load Balancer to read from the SQS queue and process orders into the database.
- C . Write orders to Amazon Simple Notification Service (Amazon SNS) Subscribe the database endpoint to the SNS topic Use EC2 instances in an Auto Scaling group behind an Application Load Balancer to read from the SNS topic.
- D . Write orders to an Amazon Simple Queue Service (Amazon SQS) queue when the EC2 instance reaches CPU threshold limits. Use scheduled scaling of EC2 instances in an Auto Scaling group behind an Application Load Balancer to read from the SQS queue and process orders into the database
B
Explanation:
Amazon SQS is a fully managed message queuing service that can decouple and scale microservices, distributed systems, and serverless applications. By writing orders to an SQS queue, the application
can handle spikes in traffic without losing any orders. The EC2 instances in an Auto Scaling group can read from the SQS queue and process orders into the database at a steady pace. The Application Load Balancer can distribute the load across the EC2 instances and provide health checks. This solution meets all the requirements of the question, while the other options do not.
Reference: https://docs.aws.amazon.com/wellarchitected/latest/reliability-pillar/welcome.html https://aws.amazon.com/architecture/serverless/ https://aws.amazon.com/sqs/
A company has an API that receives real-time data from a fleet of monitoring devices. The API stores this data in an Amazon RDS DB instance for later analysis. The amount of data that the monitoring devices send to the API fluctuates. During periods of heavy traffic, the API often returns timeout errors.
After an inspection of the logs, the company determines that the database is not capable of processing the volume of write traffic that comes from the API. A solutions architect must minimize the number of connections to the database and must ensure that data is not lost during periods of heavy traffic.
Which solution will meet these requirements?
- A . Increase the size of the DB instance to an instance type that has more available memory.
- B . Modify the DB instance to be a Multi-AZ DB instance. Configure the application to write to all active RDS DB instances.
- C . Modify the API to write incoming data to an Amazon Simple Queue Service (Amazon SQS) queue. Use an AWS Lambda function that Amazon SQS invokes to write data from the queue to the database.
- D . Modify the API to write incoming data to an Amazon Simple Notification Service (Amazon SNS) topic. Use an AWS Lambda function that Amazon SNS invokes to write data from the topic to the database.
C
Explanation:
Using Amazon SQS will help minimize the number of connections to the database, as the API will write data to a queue instead of directly to the database. Additionally, using an AWS Lambda function that Amazon SQS invokes to write data from the queue to the database will help ensure that data is not lost during periods of heavy traffic, as the queue will serve as a buffer between the API and the database.
A company runs an on-premises application that is powered by a MySQL database. The company is migrating the application to AWS to Increase the application’s elasticity and availability
The current architecture shows heavy read activity on the database during times of normal operation Every 4 hours the company’s development team pulls a full export of the production database to populate a database in the staging environment During this period, users experience unacceptable application latency. The development team is unable to use the staging environment until the procedure completes
A solutions architect must recommend replacement architecture that alleviates the application latency issue. The replacement architecture also must give the development team the ability to continue using the staging environment without delay
Which solution meets these requirements?
- A . Use Amazon Aurora MySQL with Multi-AZ Aurora Replicas for production. Populate the staging database by implementing a backup and restore process that uses the mysqldump utility.
- B . Use Amazon Aurora MySQL with Multi-AZ Aurora Replicas for production Use database cloning to create the staging database on-demand
- C . Use Amazon RDS for MySQL with a Mufti AZ deployment and read replicas for production Use the standby instance tor the staging database.
- D . Use Amazon RDS for MySQL with a Multi-AZ deployment and read replicas for production. Populate the staging database by implementing a backup and restore process that uses the mysqldump utility.
B
Explanation:
https://aws.amazon.com/blogs/aws/amazon-aurora-fast-database-cloning/
A company uses a set of Amazon EC2 instances to host a website. The website uses an Amazon S3 bucket to store images and media files.
The company wants to automate website infrastructure creation to deploy the website to multiple AWS Regions. The company also wants to provide the EC2 instances access to the S3 bucket so the instances can store and access data by using AWS Identity and Access Management (1AM).
Which solution will meet these requirements MOST securely?
- A . Create an AWS Cloud Format ion template for the web server EC2 instances. Save an 1AM access key in the UserData section of the AWS;:EC2::lnstance entity in the CloudFormation template.
- B . Create a file that contains an 1AM secret access key and access key ID. Store the file in a new S3 bucket. Create an AWS CloudFormation template. In the template, create a parameter to specify the location of the S3 object that contains the access key and access key ID.
- C . Create an 1AM role and an 1AM access policy that allows the web server EC2 instances to access the S3 bucket. Create an AWS CloudFormation template for the web server EC2 instances that contains an 1AM instance profile entity that references the 1AM role and the 1AM access policy.
- D . Create a script that retrieves an 1AM secret access key and access key ID from 1AM and stores them on the web server EC2 instances. Include the script in the UserData section of the AWS::EC2::lnstance entity in an AWS CloudFormation template.
C
Explanation:
The most secure solution for allowing EC2 instances to access an S3 bucket is by using IAM roles. An IAM role can be created with an access policy that grants the required permissions (e.g., to read and write to the S3 bucket). The IAM role is then associated with the EC2 instances through an IAM instance profile.
By associating the role with the instances, the EC2 instances can securely assume the role and receive temporary credentials via the instance metadata service. This avoids the need to store credentials (such as access keys) on the instances or within the application, enhancing security and reducing the risk of credentials being exposed.
AWS CloudFormation can be used to automate the creation of the entire infrastructure, including EC2 instances, IAM roles, and associated policies.
AWS
Reference: IAM Roles for EC2 Instances outlines the use of IAM roles for secure access to AWS services.
AWS CloudFormation User Guide details how to create and manage resources using CloudFormation templates.
Why the other options are incorrect:
A gaming company is designing a highly available architecture. The application runs on a modified Linux kernel and supports only UDP-based traffic. The company needs the front-end tier to provide the best possible user experience. That tier must have low latency, route traffic to the nearest edge location, and provide static IP addresses for entry into the application endpoints.
What should a solutions architect do to meet these requirements?
- A . Configure Amazon Route 53 to forward requests to an Application Load Balancer. Use AWS Lambda for the application in AWS Application Auto Scaling.
- B . Configure Amazon CloudFront to forward requests to a Network Load Balancer. Use AWS Lambda for the application in an AWS Application Auto Scaling group.
- C . Configure AWS Global Accelerator to forward requests to a Network Load Balancer. Use Amazon EC2 instances for the application in an EC2 Auto Scaling group.
- D . Configure Amazon API Gateway to forward requests to an Application Load Balancer. Use Amazon EC2 instances for the application in an EC2 Auto Scaling group.
C
Explanation:
AWS Global Accelerator and Amazon CloudFront are separate services that use the AWS global network and its edge locations around the world. CloudFront improves performance for both cacheable content (such as images and videos) and dynamic content (such as API acceleration and dynamic site delivery). Global Accelerator improves performance for a wide range of applications over TCP or UDP by proxying packets at the edge to applications running in one or more AWS Regions. Global Accelerator is a good fit for non-HTTP use cases, such as gaming (UDP), IoT (MQTT), or Voice over IP, as well as for HTTP use cases that specifically require static IP addresses or deterministic, fast regional failover. Both services integrate with AWS Shield for DDoS protection.
A company has thousands of edge devices that collectively generate 1 TB of status alerts each day. Each alert is approximately 2 KB in size. A solutions architect needs to implement a solution to ingest and store the alerts for future analysis.
The company wants a highly available solution. However, the company needs to minimize costs and
does not want to manage additional infrastructure. Ad ditionally, the company wants to keep 14 days of data available for immediate analysis and archive any data older than 14 days.
What is the MOST operationally efficient solution that meets these requirements?
- A . Create an Amazon Kinesis Data Firehose delivery stream to ingest the alerts Configure the Kinesis Data Firehose stream to deliver the alerts to an Amazon S3 bucket Set up an S3 Lifecycle configuration to transition data to Amazon S3 Glacier after 14 days
- B . Launch Amazon EC2 instances across two Availability Zones and place them behind an Elastic Load Balancer to ingest the alerts Create a script on the EC2 instances that will store tne alerts m an Amazon S3 bucket Set up an S3 Lifecycle configuration to transition data to Amazon S3 Glacier after 14 days
- C . Create an Amazon Kinesis Data Firehose delivery stream to ingest the alerts Configure the Kinesis Data Firehose stream to deliver the alerts to an Amazon Elasticsearch Service (Amazon ES) duster Set up the Amazon ES cluster to take manual snapshots every day and delete data from the duster that is older than 14 days
- D . Create an Amazon Simple Queue Service (Amazon SQS i standard queue to ingest the alerts and set the message retention period to 14 days Configure consumers to poll the SQS queue check the age of the message and analyze the message data as needed If the message is 14 days old the consumer should copy the message to an Amazon S3 bucket and delete the message from the SQS queue
A
Explanation:
https://aws.amazon.com/kinesis/data-firehose/features/?nc=sn&loc=2#:~:text=into%20Amazon%20S3%2C%20Amazon%20Redshift%2C%20Amazon%20OpenSearch%20Service%2C%20Kinesis,Delivery%20streams
A company is developing an application that will run on a production Amazon Elastic Kubernetes Service (Amazon EKS) cluster. The EKS cluster has managed node groups that are provisioned with On-Demand Instances.
The company needs a dedicated EKS cluster for development work. The company will use the development cluster infrequently to test the resiliency of the application. The EKS cluster must manage all the nodes.
Which solution will meet these requirements MOST cost-effectively?
- A . Create a managed node group that contains only Spot Instances.
- B . Create two managed node groups. Provision one node group with On-Demand Instances.
Provision the second node group with Spot Instances. - C . Create an Auto Scaling group that has a launch configuration that uses Spot Instances. Configure the user data to add the nodes to the EKS cluster.
- D . Create a managed node group that contains only On-Demand Instances.
A
Explanation:
Spot Instances are EC2 instances that are available at up to a 90%discount compared to On-Demand prices. Spot Instances are suitable for stateless, fault-tolerant, and flexible workloads that can tolerate interruptions. Spot Instances can be reclaimed by EC2 when the demand for On-Demand capacity increases, but they provide a two-minute warning before termination. EKS managed node groups automate the provisioning and lifecycle management of nodes for EKS clusters. Managed node groups can use Spot Instances to reduce costs and scale the cluster based on demand. Managed node groups also support features such as Capacity Rebalancing and Capacity Optimized allocation strategy to improve the availability and resilience of Spot Instances. This solution will meet the requirements most cost-effectively, as it leverages the lowest-priced EC2 capacity and does not require any manual intervention.
Reference: 1 explains how to create and use managed node groups with EKS.
2 describes how to use Spot Instances with managed node groups.
3 provides an overview of Spot Instances and their benefits.
A company runs an application on Amazon EC2 Linux instances across multiple Availability Zones. The application needs a storage layer that is highly available and Portable Operating System Interface (POSIX) compliant. The storage layer must provide maximum data durability and must be shareable across the EC2 instances. The data in the storage layer will be accessed frequency for the first 30 days and will be accessed infrequently alter that time.
Which solution will meet these requirements MOST cost-effectively?
- A . Use the Amazon S3 Standard storage class Create an S3 Lifecycle policy to move infrequently accessed data to S3 Glacier
- B . Use the Amazon S3 Standard storage class. Create an S3 Lifecycle policy to move infrequently accessed data to S3 Standard-Infrequent Access (EF3 Standard-IA).
- C . Use the Amazon Elastic File System (Amazon EFS) Standard storage class. Create a Lifecycle management policy to move infrequently accessed data to EFS Standard-Infrequent Access (EFS Standard-IA)
- D . Use the Amazon Elastic File System (Amazon EFS) One Zone storage class. Create a Lifecycle management policy to move infrequently accessed data to EFS One Zone-Infrequent Access (EFS One Zone-IA).
C
Explanation:
https://aws.amazon.com/efs/features/infrequent-access/