SAA-C03 Amazon Web Services AWS Certified Solutions Architect - Associate (SAA-C03) Free Practice Exam Questions (2026 Updated)

For high availability, Amazon ElastiCache for Redis supports Multi-AZ with automatic failover, which provides primary and replica nodes in different Availability Zones. If the primary node fails, Redis automatically promotes a replica to primary.

From AWS Documentation:

“When you enable Multi-AZ with automatic failover, Amazon ElastiCache automatically detects failures and promotes a read replica to primary with minimal downtime.”

(Source: Amazon ElastiCache for Redis User Guide)

Why B is correct:

Multi-AZ provides automatic failover and data replication.

Ensures continuous availability and protects against node or AZ failures.

Fully managed with no manual intervention needed.

Why others are incorrect:

A: Manual promotion is not automatic.

C & D: Restoring from backup is slow and meant for disaster recovery, not failover.

AWS Elastic Disaster Recovery (AWS DRS) enables fast, reliable, and cost-effective disaster recovery. It replicates on-premises machines to AWS using continuous block-level replication. It supports automated testing and failover, meeting aggressive RTO targets such as 15 minutes.

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.

AWS Config is a service that enables you to assess, audit, and evaluate the configurations of your AWS resources. By creating a Config rule, you can automatically check whether your Amazon EBS volumes are encrypted and flag those that are not, with minimal cost and configuration effort.

AWS Config Rule: AWS Config provides managed rules that you can use to automatically check the compliance of your resources against predefined or custom criteria. In this case, you wouldcreate a rule to evaluate EBS volumes and determine if they are encrypted. If a volume is not encrypted, the rule will flag it, allowing you to take corrective action.

Operational Overhead: This approach significantly reduces operational overhead because once the rule is in place, it continuously monitors your EBS volumes for compliance, and there’s no need for manual checks or custom scripting.

Why Not Other Options?:

Option A (Lambda with API calls and EventBridge): While this can work, it involves writing and maintaining custom code, which increases operational overhead compared to using a managed AWS Config rule.

Option B (API calls on Fargate): Running API calls on Fargate is more complex and costly compared to using AWS Config, which provides a simpler, managed solution.

Option C (IAM policy with Cost Explorer): This option does not directly enforce encryption compliance and involves manual intervention, making it less efficient and more prone to errors.

AWS References:

AWS Config Rules- Overview of AWS Config rules and how they can be used to evaluate resource configurations.

Amazon EBS Encryption- Information on how to manage and enforce encryption for EBS volumes.

Key Requirements:

Protect public endpoints (CloudFront distributions and ALBs) frommalicious attacks.

Centralizedmanagementacross multiple accounts in an organization.

Ability tomonitor security configurationseffectively.

Minimizeoperational overhead.

Analysis of Options

Option A:

AWS WAF:Protects web applications by filtering and blocking malicious requests. Rules can be applied to both ALBs and CloudFront distributions.

AWS Firewall Manager:Enables centralized management of WAF rules across multiple accounts in an AWS Organizations organization. It simplifies rule deployment, avoiding the need to configure rules individually in each account.

AWS Config:Monitors compliance by using rules that check Regional and global WAF configurations. Ensures that security configurations align with organizational policies.

Operational Overhead:Centralized management and automated monitoring reduce the operational burden.

Correct Approach:Meets all requirements with the least overhead.

Option B:

This approach involves applying WAF rules in each account manually.

While AWS Config and AWS Security Hub provide monitoring capabilities, managing individual WAF configurations in multiple accounts introduces significant operational overhead.

Incorrect Approach:Higher overhead compared to centralized management with AWS Firewall Manager.

Option C:

Similar to Option A but includesAmazon Inspector, which is not designed for monitoring WAF configurations.

AWS Security Hubis appropriate for monitoring but is redundant when Firewall Manager and Config are already in use.

Incorrect Approach:Adds unnecessary complexity and does not focus on monitoring WAF specifically.

Option D:

AWS Shield Advanced:Focuses on mitigating large-scale DDoS attacks but does not provide the fine-grained web application protection offered by WAF.

AWS Config:Can monitor Shield Advanced configurations but does not fulfill the WAF monitoring requirements.

Incorrect Approach:Does not address the need for WAF or centralized rule management.

Why Option A is Correct

Protection:

AWS WAF provides fine-grained filtering and protection against SQL injection, cross-site scripting, and other web vulnerabilities.

Rules can be applied at both ALBs and CloudFront distributions, covering all public endpoints.

Centralized Management:

AWS Firewall Manager enables security teams to centrally define and manage WAF rules across all accounts in the organization.

Monitoring:

AWS Config ensures compliance with WAF configurations by checking rules and generating alerts for misconfigurations.

Operational Overhead:

Centralized management via Firewall Manager and automated compliance monitoring via AWS Config greatly reduce manual effort.

AWS Solution Architect References

AWS WAF Documentation

AWS Firewall Manager Documentation

AWS Config Best Practices

AWS Organizations Documentation

AWS recommends using cost allocation tags to associate costs with owners (e.g., department, project) and AWS Budgets to create cost or usage budgets with alerts at defined thresholds (e.g., 60%). Budgets can send notifications via email or Amazon SNS when “Actual or forecasted” spend exceeds the threshold. Cost Explorer forecasts help visualize trends but do not provide budget alerting or ownership attribution by themselves. Trusted Advisor does not generate budget threshold alerts. Therefore, tagging resources for accountability and setting a budget with a 60% alert provides governance and proactive notifications aligned with cost control best practices for experimentation.

Why Option C is Correct:

NAT Gateway: Allows private subnets to access the internet for outbound requests while preventing inbound connections.

High Availability: Deploying NAT gateways in both AZs ensures fault tolerance.

Shared Route Table: Simplifies routing configuration for private subnets.

Why Other Options Are Not Ideal:

Option A: Creating separate route tables for each subnet adds unnecessary complexity.

Option B: Internet gateways allow inbound access, violating the requirement to block public IPv4 access.

Option D: Egress-only internet gateways are designed for IPv6, not IPv4.

AWS References:

Amazon VPC NAT Gateway:AWS Documentation - NAT Gateway

A. EC2 with EBS:Does not support SQL Server Always On availability groups effectively.

B. RDS Multi-AZ:Provides high availability but does not support SQL Server Always On availability groups.

C. EC2 with FSx for Windows:Best solution for SQL Server Always On as FSx provides shared storage compatible with SQL Server clustering.

D. EC2 with S3:S3 is not suitable for SQL Server storage.

Amazon S3 is suitable for storing data that needs to be accessed weekly and integrates with AWS Key Management Service (KMS) to provide encryption at rest with server-side encryption using KMS-managed keys (SSE-KMS).

SSE-KMS uses envelope encryption and allows automatic key rotation and logging through AWS CloudTrail, satisfying the requirements for audit trails and compliance.

S3 Glacier Deep Archive is unsuitable due to its high retrieval latency. SSE-C requires customer-side management of encryption keys, with no support for automatic rotation or audit. SSE-S3 does not use customer-managed keys and lacks fine-grained control and auditing.

Amazon FSx for ONTAP supports both NFS and SMB protocols and includes automated tiering between SSD and capacity pool storage, optimizing cost and performance. It is ideal for mixed operating systems and varied access patterns with minimal administrative overhead.

The ALB must be in a public subnet to receive internet traffic. The EC2 instances and the RDS database should be in private subnets to prevent direct internet access, minimizing the attack surface. This aligns with AWS security best practices for web application architectures.

Reference Extract:

"Internet-facing ALBs should be placed in public subnets; EC2 instances and RDS databases should be in private subnets to restrict direct internet access."

Source: AWS Certified Solutions Architect – Official Study Guide, Network Security and Design section.

Amazon OpenSearch Service is the AWS-native service for real-time search, analytics, and visualization. Ingesting streaming data with Amazon Kinesis Data Streams ensures scalable and reliable data ingestion. OpenSearch supports indexing and querying the data in near real time. QuickSight can then be integrated for visualization and reporting. Options A and B involve batch processing and are not optimized for real-time search. Option C (EKS + DynamoDB) is not a fit for search workloads, as DynamoDB does not support advanced text search. Option D provides the closest AWS-native equivalent to the company’s existing search-and-visualization architecture.

Why Option B is Correct:

Amazon SQS: Ensures no requests are lost, even during traffic spikes.

API Gateway: Handles dynamic traffic patterns efficiently, integrating with SQS for asynchronous processing.

Lambda: Polls the queue and processes requests in a serverless and scalable manner.

Dead-Letter Queue (DLQ): Ensures failed messages are retried or logged for debugging.

Why Other Options Are Not Ideal:

Option A: Elastic Beanstalk cannot handle queue-based decoupling, making it unsuitable for spiky traffic.

Option C: ALB to Lambda does not provide buffering for traffic spikes, risking request loss.

Option D: SNS is better suited for notifications, not reliable for ensuring message durability.

AWS References:

Amazon SQS:AWS Documentation - SQS

Amazon Data Lifecycle Manager (DLM) automates the creation, retention, and deletion of EBSsnapshots. This allows organizations to define policies that ensure snapshots are only kept as long as needed, reducing costs automatically and minimizing manual effort. AWS recommends using DLM for optimizing storage and managing backup lifecycle with minimal overhead.

Application Load Balancer (ALB): ALB is suitable for routing HTTP/HTTPS traffic to the application servers. It provides advanced routing features and integrates well with Auto Scaling groups.

Target Group Configuration:

Create a target group for the application servers and register the Auto Scaling group with this target group.

Configure the ALB to forward requests from the web servers to the application servers.

Security Group Setup:

Configure the security group of the application servers to only allow traffic from the web servers' security group.

This ensures that only the web servers can access the application servers, meeting the requirement to limit access.

Benefits:

Security: Using security groups to restrict access ensures a secure environment where only intended traffic is allowed.

Scalability: ALB works seamlessly with Auto Scaling groups, ensuring the application can handle varying loads efficiently.

To ensure ALB access only via CloudFront, AWS prescribes restricting the origin to traffic from CloudFront. For ALB origins, the standard pattern is to allow inbound to the ALB only from CloudFront edge IP ranges using security groups or ALB listener rules. Network ACLs are coarse and stateless and add operational burden. CloudFront does not have a “VPC origin” object; instead, CloudFront references the ALB DNS name. By limiting the ALB’s security group to CloudFront IP ranges, direct client access to the ALB is blocked while CloudFront remains permitted. This aligns with security best practices to “restrict origin access to only CloudFront” and use SGs for instance/ALB layer controls.

Amazon Kinesis Data Streams provides a highly scalable and durable service for ingesting real-time streaming data. By decoupling ingestion and processing, Kinesis can handle large spikes in traffic without service disruption. Lambda functions (or other consumers) can then process the data as it arrives, scaling automatically. This pattern avoids 503 errors due to compute saturation and delivers a resilient, serverless, and highly scalable architecture.

Reference Extract from AWS Documentation / Study Guide:

"Kinesis Data Streams provides a scalable and durable real-time data streaming service. Coupling Kinesis with AWS Lambda enables event-driven processing, elasticity, and decoupling between ingestion and processing layers."

Source: AWS Certified Solutions Architect – Official Study Guide, Streaming and Serverless section.

To securely integrate Amazon S3 with an application that uses Amazon Cognito for user authentication, the following two steps are essential:

Step 1: Create an Amazon Cognito Identity Pool (Option A)

Amazon Cognito Identity Poolsallow users to obtain temporary AWS credentials to access AWS resources, such as Amazon S3, after successfully authenticating with the Cognito user pool. The identity pool bridges the gap between user authentication and AWS service access by generating temporary credentials using AWS Identity and Access Management (IAM).

Once a user logs in using theCognito User Pool, the identity pool providesIAM roles with specific permissionsthat the application can use to access S3 securely. This ensures that each user has appropriate access controls while accessing the S3 bucket.

This is a secure way to ensure that users only have temporary and least-privilege access to the S3 bucket for their documents.

Step 2: Create an Amazon S3 VPC Endpoint (Option C)

By creating anAmazon S3 VPC endpoint, the company ensures that communication between the application (which is hosted in a private subnet) and the S3 bucket occurs over theAWS private network, without the need to traverse the internet. This enhances security and prevents exposure of data to public networks.

TheVPC endpointallows the application to access the S3 bucket privately and securely within the VPC. It also ensures that traffic stays within the AWS network, reducing attack surface and improving overall security.

Why the Other Options Are Incorrect:

Option B: This is incorrect becauseAmazon Cognito User Poolsare used for user authentication, not for generating S3 access tokens. To provide S3 access, you need to useAmazon Cognito Identity Pools, which offer AWS credentials.

Option D: ANAT gatewayis unnecessary in this scenario. Using aVPC endpointfor S3 access provides a more secure and cost-effective solution by keeping traffic within AWS.

Option E: Attaching a policy to restrict access based on IP addresses is not scalable or efficient. It would require managing users’ dynamic IP addresses, which is not an effective security measure for this use case.

AWS References:

Amazon Cognito Identity Pools

Amazon VPC Endpoints for S3

A. Mutual TLS:Provides secure communication but does not integrate with AWS credential exchange.

B. AWS Signature v4:Requires direct integration with AWS and is less secure for external systems.

C. Kerberos:Not natively supported for AWS API authentication.

D. IAM Roles Anywhere:Enables AWS API access using X.509 certificates without long-term credentials.

The most secure and manageable way to provide developers with temporary, least-privilege access is by using AWS IAM Identity Center (formerly AWS SSO). IAM Identity Center allows assigning IAM roles with scoped permissions based on the developer’s team role. This ensures no permanent credentials are required and minimizes risk.

Option B enables role-based access with centralized identity and access management, making it the most secure and scalable solution for managing developer permissions.

Amazon Macieis purpose-built for detecting PII in S3.

Option Auses EventBridge to filter SensitiveData findings and notify via SNS, meeting the requirements.

Options B and Dinvolve GuardDuty, which is not designed for PII detection.

Option Cuses SQS, which is less suitable for immediate notifications.

Amazon Neptune is a fully managed graph database service optimized for storing and navigating complex many-to-many relationships like social graphs or network topologies.

It supports Gremlin and openCypher queries that allow efficient traversal of connections even multiple levels deep. SQL JOINs (Athena or RDS) are inefficient for deep relationship queries due to exponential complexity.

QuickSight is used for data visualization, not graph traversal.

For globally distributed consumers of REST APIs, API Gateway edge-optimized endpoints “route requests to the nearest CloudFront edge location, which then forwards them to your API in the [home] Region,” reducing latency for users worldwide and scaling automatically for unknown or spiky traffic. By contrast, Regional endpoints are intended for clients within the same or nearby Region and do not provide global edge acceleration. AWS Lambda provides automatic scaling for serverless backends; latency can be further reduced by right-sizing memory (which also increases CPU) and, when needed, enabling provisioned concurrency to keep functions initialized and eliminate cold starts for critical paths. Using NLBs across Regions is not serverless and adds operational complexity without CloudFront edge acceleration. Therefore, combining API Gateway edge-optimized REST APIs with Lambda meets the requirements of minimal global latency and unknown initial traffic.

To improve scalability and availability, EC2 Auto Scaling across multiple Availability Zones with an Application Load Balancer ensures resilient infrastructure. Migrating to Amazon Aurora MySQL with reader endpoints reduces read latency by offloading read traffic to replicas in otherAZs, while also increasing high availability.

Amazon S3 Intelligent-Tiering: This storage class is designed to optimize costs by automatically moving data between two access tiers (frequent and infrequent) when access patterns change. It provides cost savings without performance impact or operational overhead.

S3 Lifecycle Rules: By creating an S3 Lifecycle rule, the company can automatically transition objects to the Intelligent-Tiering storage class. This eliminates the need for manual intervention and ensures that objects are moved to the most cost-effective storage tier based on their access patterns.

Operational Efficiency: Intelligent-Tiering requires no additional management and delivers immediate availability for frequently accessed objects. This makes it the most operationally efficient solution for the given requirements.

DynamoDB Streams: Captures real-time changes in DynamoDB tables and allows integration with Lambda for processing the changes.

Minimal Operational Overhead: Using a Lambda function directly to write data to S3 ensures simplicity and reduces the complexity of the pipeline.

Amazon DynamoDB Streams Documentation

AWS CloudTrail Lakeis a fully managed service that allows the collection, storage, and querying ofCloudTrail eventsfor both AWS and non-AWS services. CloudTrail Lake can be customized to collect logs from various sources, ensuring a centralized audit solution. It also supports long-term storage, so logs can be retained for 7 years, meeting the compliance requirement.

Option A (Data Lake): Setting up a data lake in S3 introduces unnecessary operational complexity compared to CloudTrail Lake.

Option C (Ingest non-AWS services into CloudTrail): CloudTrail Lake is better suited for this task with less operational overhead.

Option D (CloudWatch Logs): While CloudWatch can store logs, CloudTrail Lake is specifically designed for API auditing and storage.

AWS References:

AWS CloudTrail Lake

Amazon API Gatewayprovides a scalable and reusable solution for interacting with DynamoDB without requiring direct access by developers. By setting up a REST API with a POST methodthat integrates with DynamoDB'sPutItemaction, developers can submit data (such as user ratings) to the DynamoDB table through API Gateway, without having to directly interact with the database. This solution is serverless and minimizes operational overhead.

Option A: Using ALB with Lambda adds complexity and is less efficient for this use case.

Option B: While using Lambda is possible, API Gateway provides a more scalable, reusable interface.

Option C: SQS with Lambda introduces unnecessary components for a simple put operation.

AWS References:

Amazon API Gateway with DynamoDB

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'sVolume Gateway with cached volumesis the most appropriate solution for this scenario.

AWS Storage Gateway - Volume Gateway (Cached Volumes):

Volume Gateway with cached volumesallows 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 References:

AWS Storage Gateway - Volume Gateway