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| Section | Weight | Objectives |
|---|
| Design Secure Architectures | 30% | - Design secure access to AWS resources
- 1. Identity federation
- 2. Multi-factor authentication (MFA)
- 3. IAM policies and roles
- 4. AWS Organizations and SCPs
- Determine appropriate data security controls
- 1. Data backup and recovery
- 2. Data classification
- 3. Amazon Macie and GuardDuty
- 4. Data encryption strategies
- Design secure workloads and applications
- 1. Security groups and NACLs
- 2. AWS WAF and Shield
- 3. Encryption at rest and in transit
- 4. AWS KMS and CloudHSM
|
| Design High-Performing Architectures | 24% | - Determine high-performing and/or scalable storage solutions
- 1. Amazon EBS volume types
- 2. Amazon FSx
- 3. Amazon S3 storage classes and lifecycle policies
- 4. Amazon EFS
- 5. Instance Store
- Design high-performing and elastic compute solutions
- 1. Amazon ECS and EKS
- 2. AWS Lambda
- 3. Amazon EC2 instance types and families
- 4. AWS Elastic Beanstalk
- Determine high-performing and/or scalable network architectures
- 1. VPC endpoints
- 2. Amazon CloudFront
- 3. AWS Global Accelerator
- 4. AWS Direct Connect
- 5. Amazon Route 53
- Determine high-performing data ingestion and transformation solutions
- 1. AWS Data Pipeline
- 2. AWS Glue
- 3. Amazon MSK
- 4. Amazon Kinesis
- Determine high-performing database solutions
- 1. Amazon Redshift
- 2. Amazon DynamoDB
- 3. Amazon RDS and Aurora
- 4. Amazon ElastiCache (Redis/Memcached)
|
| Design Resilient Architectures | 26% | - Design scalable and loosely coupled architectures
- 1. Auto Scaling groups
- 2. Amazon SQS and SNS
- 3. Amazon API Gateway
- 4. Amazon EventBridge
- 5. Elastic Load Balancing
- Design highly available and/or fault-tolerant architectures
- 1. AWS Global Accelerator
- 2. Amazon Route 53 routing policies
- 3. Multi-AZ deployments
- 4. Disaster recovery strategies (backup/restore, pilot light, warm standby, multi-site)
- 5. Multi-Region architectures
|
| Design Cost-Optimized Architectures | 20% | - Design cost-optimized network architectures
- 1. CloudFront to reduce origin load
- 2. AWS Direct Connect for cost optimization
- 3. VPC endpoints to reduce NAT costs
- 4. Data transfer costs
- Design cost-optimized compute solutions
- 1. Auto Scaling for cost optimization
- 2. EC2 purchasing options (On-Demand, Reserved, Spot, Savings Plans)
- 3. AWS Lambda pricing model
- 4. Right-sizing instances
- Design cost-optimized storage solutions
- 1. EFS cost optimization
- 2. EBS volume type selection
- 3. S3 Intelligent-Tiering
- 4. S3 storage classes and lifecycle policies
- Design cost-optimized database solutions
- 1. Aurora Serverless
- 2. DynamoDB capacity modes (On-demand vs Provisioned)
- 3. ElastiCache for caching
- 4. RDS Reserved Instances
|
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2026 Amazon SAA-C03: AWS Certified Solutions Architect - Associate –High-quality Training For Exam
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Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q197-Q202):
NEW QUESTION # 197
[Design High-Performing Architectures]
A company uses an Amazon Aurora PostgreSQL provisioned cluster with its application. The application's peak traffic occurs several times a day for periods of 30 minutes to several hours.
The database capacity is provisioned to handle peak traffic from the application, but the database has wasted capacity during non-peak hours. The company wants to reduce the database costs.
Which solution will meet these requirements with the LEAST operational effort?
- A. Schedule an AWS Lambda function to provision the required database capacity at the start of each day. Schedule another Lambda function to reduce the capacity at the end of each day.
- B. Migrate the database to Amazon EC2 instances in on Auto Scaling group. Increase or decrease the number of instances based on the amount of traffic.
- C. Set up an Amazon CloudWatch alarm to monitor database utilization. Scale up or scale down the database capacity based on the amount of traffic.
- D. Migrate the database to an Amazon Aurora Serverless DB cluster to scale up or scale down the capacity based on the amount of traffic.
Answer: D
Explanation:
Requirement Analysis: The database experiences peak traffic multiple times a day but has wasted capacity during non-peak hours. The goal is to reduce costs with minimal operational effort.
Aurora Serverless Overview: Aurora Serverless automatically adjusts database capacity based on current demand, scaling up during peak times and scaling down during non-peak times.
Cost Efficiency: Aurora Serverless charges only for the capacity used, which is more cost-effective than provisioning for peak traffic.
Operational Efficiency: Aurora Serverless eliminates the need for manual scaling or scheduling Lambda functions for capacity management.
Implementation: Migrate the database from the provisioned Aurora PostgreSQL cluster to an Aurora Serverless cluster.
Reference
Amazon Aurora Serverless:Aurora Serverless Documentation
NEW QUESTION # 198
A media company runs an application on multiple Amazon EC2 instances that requires high storage input/output operations per second (IOPS). To achieve the necessary performance, a solutions architect wants to stripe multiple Amazon EBS volumes together and attach the volumes to EC2 instances. The solutions architect wants to receive a notification when IOPS are over-provisioned. Which solution will meet these requirements?
- A. Create a custom AWS Config rule to monitor the provisioned IOPS for the EBS volumes that are attached to the EC2 instances and to send notifications.
- B. Adjust the IOPS of each EBS volume daily based on Amazon CloudWatch metrics for IOPS utilization.
- C. Configure auto scaling for the EBS volumes to automatically increase or decrease IOPS based on the EC2 instance CPU utilization metric.
- D. Deploy the application on an EC2 instance type that supports the highest possible IOPS.
Answer: A
Explanation:
AWS Config allows for creation of custom rules to monitor EBS configurations. Combined with CloudWatch metrics and Amazon SNS, custom rules can track over-provisioned IOPS and send alerts when thresholds are breached, allowing proactive cost and performance management.
NEW QUESTION # 199
A company uses an organization in AWS Organizations to manage AWS accounts that contain applications. The company sets up a dedicated monitoring member account in the organization. The company wants to query and visualize observability data across the accounts by using Amazon CloudWatch.
Which solution will meet these requirements?
- A. Configure a new 1AM user in the monitoring account. In each AWS account, configure an 1AM policy to have access to query and visualize the CloudWatch data in the account. Attach the new 1AM policy to the new I AM user.
- B. Enable CloudWatch cross-account observability for the monitoring account. Deploy an AWS CloudFormation template provided by the monitoring account in each AWS account to share the data with the monitoring account.
- C. Set up service control policies (SCPs) to provide access to CloudWatch in the monitoring account under the Organizations root organizational unit (OU).
- D. Create a new 1AM user in the monitoring account. Create cross-account 1AM policies in each AWS account. Attach the 1AM policies to the new 1AM user.
Answer: B
Explanation:
CloudWatch cross-account observability is a feature that allows you to monitor and troubleshoot applications that span multiple accounts within a Region. You can seamlessly search, visualize, and analyze your metrics, logs, traces, and Application Insights applications in any of the linked accounts without account boundaries1. To enable CloudWatch cross-account observability, you need to set up one or more AWS accounts as monitoring accounts and link them with multiple source accounts. A monitoring account is a central AWS account that can view and interact with observability data shared by other accounts. A source account is an individual AWS account that shares observability data and resources with one or more monitoring accounts1. To create links between monitoring accounts and source accounts, you can use the CloudWatch console, the AWS CLI, or the AWS API. You can also use AWS Organizations to link accounts in an organization or organizational unit to the monitoring account1. CloudWatch provides a CloudFormation template that you can deploy in each source account to share observability data with the monitoring account. The template creates a sink resource in the monitoring account and an observability link resource in the source account. The template also creates the necessary IAM roles and policies to allow cross-account access to the observability data2. Therefore, the solution that meets the requirements of the question is to enable CloudWatch cross-account observability for the monitoring account and deploy the CloudFormation template provided by the monitoring account in each AWS account to share the data with the monitoring account.
The other options are not valid because:
Service control policies (SCPs) are a type of organization policy that you can use to manage permissions in your organization. SCPs offer central control over the maximum available permissions for all accounts in your organization, allowing you to ensure your accounts stay within your organization's access control guidelines3. SCPs do not provide access to CloudWatch in the monitoring account, but rather restrict the actions that users and roles can perform in the source accounts. SCPs are not required to enable CloudWatch cross-account observability, as the CloudFormation template creates the necessary IAM roles and policies for cross-account access2.
IAM users are entities that you create in AWS to represent the people or applications that use them to interact with AWS. IAM users can have permissions to access the resources in your AWS account4. Configuring a new IAM user in the monitoring account and an IAM policy in each AWS account to have access to query and visualize the CloudWatch data in the account is not a valid solution, as it does not enable CloudWatch cross-account observability. This solution would require the IAM user to switch between different accounts to view the observability data, which is not seamless and efficient. Moreover, this solution would not allow the IAM user to search, visualize, and analyze metrics, logs, traces, and Application Insights applications across multiple accounts in a single place1.
Cross-account IAM policies are policies that allow you to delegate access to resources that are in different AWS accounts that you own. You attach a cross-account policy to a user or group in one account, and then specify which accounts the user or group can access5. Creating a new IAM user in the monitoring account and cross-account IAM policies in each AWS account is not a valid solution, as it does not enable CloudWatch cross-account observability. This solution would also require the IAM user to switch between different accounts to view the observability data, which is not seamless and efficient. Moreover, this solution would not allow the IAM user to search, visualize, and analyze metrics, logs, traces, and Application Insights applications across multiple accounts in a single place1.
NEW QUESTION # 200
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. 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.
- B. 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.
- C. 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.
- D. 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.
Answer: A
NEW QUESTION # 201
[Design High-Performing Architectures]
A company wants to create an application to store employee data in a hierarchical structured relationship. The company needs a minimum-latency response to high-traffic queries for the employee data and must protect any sensitive dat a. The company also need to receive monthly email messages if any financial information is present in the employee data.
Which combination of steps should a solutin architect take to meet these requirement? ( Select TWO.)
- A. Use Amazon Athena to analyze the employee data in Amazon S3 integrate Athena with Amazon QuickSight to publish analysis dashboards and share the dashboards with users.
- B. Use Amazon DynamoDB to store the employee data in hierarchies Export the data to Amazon S3 every month.
- C. Configure Amazon Macie for the AWS account Integrate Macie with Amazon EventBridge to send monthly events to AWS Lambda.
- D. Configure Amazon Macie for the AWS account. integrate Macie with Amazon EventBridge to send monthly notifications through an Amazon Simple Notification Service (Amazon SNS) subscription.
- E. Use Amazon Redshift to store the employee data in hierarchies. Unload the data to Amazon S3 every month.
Answer: B,D
Explanation:
https://docs.aws.amazon.com/prescriptive-guidance/latest/dynamodb-hierarchical-data-model/introduction.html
NEW QUESTION # 202
......
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