2026 SAA-C03: Trustable AWS Certified Solutions Architect - Associate Exam Cram Questions

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Amazon SAA-C03 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Design Resilient Architectures	26%	- Design scalable and loosely coupled architectures 1. Auto Scaling groups 2. Amazon API Gateway 3. Amazon EventBridge 4. Amazon SQS and SNS 5. Elastic Load Balancing - Design highly available and/or fault-tolerant architectures 1. AWS Global Accelerator 2. Disaster recovery strategies (backup/restore, pilot light, warm standby, multi-site) 3. Multi-AZ deployments 4. Multi-Region architectures 5. Amazon Route 53 routing policies
Topic 2: Design High-Performing Architectures	24%	- Determine high-performing and/or scalable network architectures 1. AWS Global Accelerator 2. Amazon CloudFront 3. Amazon Route 53 4. AWS Direct Connect 5. VPC endpoints - Design high-performing and elastic compute solutions 1. AWS Lambda 2. AWS Elastic Beanstalk 3. Amazon EC2 instance types and families 4. Amazon ECS and EKS - Determine high-performing and/or scalable storage solutions 1. Amazon FSx 2. Amazon S3 storage classes and lifecycle policies 3. Amazon EBS volume types 4. Amazon EFS 5. Instance Store - Determine high-performing database solutions 1. Amazon DynamoDB 2. Amazon RDS and Aurora 3. Amazon Redshift 4. Amazon ElastiCache (Redis/Memcached) - Determine high-performing data ingestion and transformation solutions 1. AWS Glue 2. Amazon MSK 3. Amazon Kinesis 4. AWS Data Pipeline
Topic 3: Design Secure Architectures	30%	- Determine appropriate data security controls 1. Amazon Macie and GuardDuty 2. Data backup and recovery 3. Data encryption strategies 4. Data classification - Design secure workloads and applications 1. Security groups and NACLs 2. Encryption at rest and in transit 3. AWS KMS and CloudHSM 4. AWS WAF and Shield - Design secure access to AWS resources 1. Multi-factor authentication (MFA) 2. IAM policies and roles 3. Identity federation 4. AWS Organizations and SCPs
Topic 4: Design Cost-Optimized Architectures	20%	- Design cost-optimized compute solutions 1. EC2 purchasing options (On-Demand, Reserved, Spot, Savings Plans) 2. AWS Lambda pricing model 3. Auto Scaling for cost optimization 4. Right-sizing instances - Design cost-optimized network architectures 1. VPC endpoints to reduce NAT costs 2. Data transfer costs 3. AWS Direct Connect for cost optimization 4. CloudFront to reduce origin load - Design cost-optimized storage solutions 1. S3 Intelligent-Tiering 2. EFS cost optimization 3. S3 storage classes and lifecycle policies 4. EBS volume type selection - Design cost-optimized database solutions 1. ElastiCache for caching 2. DynamoDB capacity modes (On-demand vs Provisioned) 3. RDS Reserved Instances 4. Aurora Serverless

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Amazon AWS Certified Solutions Architect - Associate Sample Questions (Q806-Q811):

NEW QUESTION # 806
An application running on an Amazon EC2 instance in VPC-A needs to access files in another EC2 instance in VPC-B. Both VPCs are in separate AWS accounts. The network administrator needs to design a solution to configure secure access to EC2 instance in VPC-B from VPC-A. The connectivity should not have a single point of failure or bandwidth concerns.
Which solution will meet these requirements?

A. Set up VPC gateway endpoints for the EC2 instance running in VPC-B.
B. Set up a VPC peering connection between VPC-A and VPC-B.
C. Attach a virtual private gateway to VPC-B and set up routing from VPC-A.
D. Create a private virtual interface (VIF) for the EC2 instance running in VPC-B and add appropriate routes from VPC-A.

Answer: B

Explanation:
AWS uses the existing infrastructure of a VPC to create a VPC peering connection; it is neither a gateway nor a VPN connection, and does not rely on a separate piece of physical hardware. There is no single point of failure for communication or a bandwidth bottleneck.
https://docs.aws.amazon.com/vpc/latest/peering/what-is-vpc-peering.html

NEW QUESTION # 807
A company has an application that is backed ny an Amazon DynamoDB table. The company's compliance requirements specify that database backups must be taken every month, must be available for 6 months, and must be retained for 7 years.
Which solution will meet these requirements?

A. Create an AWS Backup plan to back up the DynamoDB table on the first day of each month. Specify a lifecycle policy that transitions the backup to cold storage after 6 months. Set the retention period for each backup to 7 years.
B. Use the AWS SDK to develop a script that creates an on-demand backup of the DynamoDB table. Set up an Amzon EvenlBridge rule that runs the script on the first day of each month. Create a second script that will run on the second day of each month to transition DynamoDB backups that are older than 6 months to cold storage and to delete backups that are older than 7 years.
C. Create a DynamoDB on-damand backup of the DynamoDB table on the first day of each month Transition the backup to Amazon S3 Glacier Flexible Retrieval after 6 months. Create an S3 Lifecycle policy to delete backups that are older than 7 years.
D. Use the AWS CLI to create an on-demand backup of the DynamoDB table Set up an Amazon EventBridge rule that runs the command on the first day of each month with a cron expression Specify in the command to transition the backups to cold storage after 6 months and to delete the backups after 7 years.

Answer: A

Explanation:
Explanation
This solution satisfies the requirements in the following ways:
* AWS Backup will automatically take full backups of the DynamoDB table on the schedule defined in the backup plan (the first of each month).
* The lifecycle policy can transition backups to cold storage after 6 months, meeting that requirement.
* Setting a 7-year retention period in the backup plan will ensure each backup is retained for 7 years as required.
* AWS Backup manages the backup jobs and lifecycle policies, requiring no custom scripting or management.

NEW QUESTION # 808
[Design Cost-Optimized Architectures]
A company uses Amazon Elastic Container Service (Amazon ECS) to run workloads that belong to service teams. Each service team uses an owner tag to specify the ECS containers that the team owns. The company wants to generate an AWS Cost Explorer report that shows how much each service team spends on ECS containers on a monthly basis.
Which combination of steps will meet these requirements in the MOST operationally efficient way? (Select TWO.)

A. Activate the owner tag as a cost allocation tag. Group the Cost Explorer report by the owner cost allocation tag.
B. Activate the owner tag as a cost allocation tag. Group the Cost Explorer report by linked account.
C. Set up AWS Compute Optimizer. Review the rightsizing recommendations.
D. Create a custom report in Cost Explorer. Apply a filter for Amazon ECS.
E. Create a custom report in Cost Explorer. Apply a filter for the owner resource tag.

Answer: A,D

Explanation:
To allocate costs based on team ownership, AWS recommends tagging resources using cost allocation tags. Activating the "owner" tag as a cost allocation tag allows AWS Cost Explorer to categorize and group spending. Additionally, filtering for Amazon ECS services enables the visibility into service-specific usage. This approach is both scalable and operationally efficient.
Reference:

NEW QUESTION # 809
A company runs game applications on AWS. The company needs to collect, visualize, and analyze telemetry data from the company's game servers. The company wants to gain insights into the behavior, performance, and health of game servers in near real time. Which solution will meet these requirements?

A. Use Amazon DynamoDB Streams to collect and store telemetry data. Configure DynamoDB Streams to invoke AWS Lambda functions to process the data in near real time. Use Amazon Managed Grafana to visualize and analyze the data.
B. Use Amazon Kinesis Data Streams to collect telemetry data. Use Amazon Managed Service for Apache Flink to process the data in near real time and publish custom metrics to Amazon CloudWatch. Use Amazon CloudWatch to create dashboards and alarms from the custom metrics.
C. Use Amazon Kinesis Data Streams to collect, process, and store telemetry data. Use Amazon EMR to process the data in near real time into required formats for analysis. Use Amazon Athena to analyze and visualize the data.
D. Use Amazon Data Firehose to collect, process, and store telemetry data in near real time. Use AWS Glue to extract, transform, and load (ETL) data from Firehose into required formats for analysis. Use Amazon QuickSight to visualize and analyze the data.

Answer: B

Explanation:
Amazon Kinesis Data Streams is designed for low-latency ingestion of streaming data. Combined with Amazon Managed Service for Apache Flink, telemetry can be processed and aggregated in near real time. Processed metrics can be sent to Amazon CloudWatch, which natively supports creating dashboards, metrics visualization, and alarms. Firehose (B) is primarily for batch ingestion and delivery, not real-time analytics. EMR with Athena (C) introduces more complexity and is better for large-scale offline analytics. DynamoDB Streams (D) is not a fit because telemetry data is not stored in DynamoDB. Therefore, option A provides the most suitable and real-time analytics pipeline for telemetry data.
Reference:
* Amazon Kinesis Data Streams Developer Guide - Real-time data ingestion
* Amazon Managed Service for Apache Flink Developer Guide - Real-time stream processing

NEW QUESTION # 810
A company runs a serverless architecture that supports multiple projects and resources in the company's AWS account. The company wants to use resource tags to monitor and analyze costs contributed by individual projects to the company's AWS bill. Which solution will meet these requirements?

A. Use AWS Billing Conductor to configure reports for each project based on the tags assigned to resources.
B. Use AWS Budgets to set budgets for each project based on the tags assigned to resources.
C. Use AWS Pricing Calculator to model cost reports for each project based on the tags assigned to resources.
D. Use AWS Cost Explorer to create custom cost allocation reports based on the tags assigned to resources.

Answer: D

Explanation:
AWS Cost Explorer allows you to analyze, visualize, and report AWS costs based on resource tags. By activating and applying cost allocation tags, you can create custom cost reports grouped by project or department, showing each project's contribution to the AWS bill. This provides cost visibility and analysis with minimal operational overhead.

NEW QUESTION # 811
......

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