SAA-C03 Amazon Web Services AWS Certified Solutions Architect - Associate (SAA-C03) Free Practice Exam Questions (2025 Updated)

For processing thousands of images and generating large files while minimizing manual tasks and operational overhead, usingAWS Batchis the best solution. AWS Batch allows you to run large-scale, parallel, and managed batch computing jobs without needing to manage the underlying infrastructure.

AWS Batch: Automates the image processing jobs, dynamically allocating the necessary resources based on the job requirements, which reduces operational overhead.

AWS Step Functions: Orchestrates the entire image processing workflow, ensuring that tasks are executed in the correct sequence, improving manageability.

Amazon S3: Stores the processed files, providing scalable and cost-effective storage.

Option A (ECS with EC2 Spot Instances): While cost-effective, managing ECS and Spot Instances involves more operational effort.

Option C (Lambda with EC2 Spot): Lambda functions have size and duration limitations, making them less suited for large image processing tasks.

Option D (EC2 with Step Functions): Managing EC2 instances involves more overhead than using AWS Batch.

AWS References:

AWS Batch

AWS Step Functions

This solution meets the requirements of providing encryption at both the network and session layers while also allowing for controlled access between on-premises systems and AWS resources.

AWS Site-to-Site VPN: This service allows you to establish a secure and encrypted connection between your on-premises network and AWS VPC over the internet or via AWS Direct Connect. The VPN encrypts data at the network layer (IPsec) as it travels between the corporate network and AWS.

Routing and Security Controls: By configuring route table entries, you can ensure that only the traffic intended for AWS resources is directed to the VPC. Additionally, by setting up security groups and network ACLs, you can further restrict and control which traffic is allowed to communicate with the instances within your VPC. This approach provides the necessary security to prevent unrestricted access, aligning with the company’s security policies.

Why Not Other Options?:

Option A (AWS Direct Connect): While Direct Connect provides a private connection, it does not inherently provide encryption. Additional steps would be required to encrypt traffic, and it doesn’t address the session layer encryption.

Option B (IAM policies for Console access): This option does not meet the requirement for network-level encryption and security between the corporate network and the VPC.

Option D (AWS Transit Gateway): Although Transit Gateway can help in managing multiple connections, it doesn’t directly provide encryption at the network layer. You would still need to configure a VPN or use other methods for encryption.

AWS References:

AWS Site-to-Site VPN- Overview of AWS Site-to-Site VPN capabilities, including encryption.

Security Groups and Network ACLs- Information on configuring security groups and network ACLs to control traffic.

The requirement to “have access to the operating system” means the compute layer must be Amazon EC2 (or containers on EC2). Managed runtimes such as Lambda and Fargate do not provide OS-level access.

The requirement for a “low-latency NoSQL database” maps directly to Amazon DynamoDB, which is a fully managed NoSQL key-value and document database that provides single-digit millisecond latency at any scale.

Because the application runs in a private subnet, AWS best practice is to access DynamoDB privately via a VPC endpoint (gateway endpoint for DynamoDB). This avoids traversing the public internet and simplifies security.

An instance profile (EC2 role) is the recommended method to grant EC2 instances permission to access DynamoDB without hardcoding credentials.

Why the other options are not correct:

B: Lambda does not provide OS access, which violates the security requirement.

C: Fargate does not provide OS access, and Aurora PostgreSQL is a relational database, not NoSQL.

D: S3 + Athena is an analytics pattern, not a low-latency NoSQL database solution; query latency is much higher and not suitable for OLTP-style app storage.

Service control policies (SCPs) in AWS Organizations apply to the accounts or OUs to which they are attached:

To restrict only nonproduction accounts, you can:

Attach the SCP directly to those specific member accounts (Option B), or

Create a dedicated OU for the nonproduction accounts and attach the SCP to that OU (Option E).

Both methods ensure that the deny policy affects only the nonproduction accounts and does not impact the production account.

Why the others are incorrect:

A: Attaching the SCP to the root OU would apply the deny to all accounts, including production, which does not meet the requirement.

C: SCPs attached to the management account only affect that account, not all member accounts.

D: Creating an OU for the production account and attaching the deny SCP there would block the prohibited instance types in production, which is the opposite of what is required.

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

AWS Lake Formationis designed for managing fine-grained access control to data in an efficient manner:

Granular Permissions: Lake Formation allows column-level, row-level, and table-level access controls, which can precisely define access to PII data.

Integration with AWS Glue Catalog: Lake Formation natively integrates with AWS Glue for seamless data cataloging and access control.

Operational Efficiency: Centralized access control policies minimize the need for separate IAM roles or policies.

Why Other Options Are Not Ideal:

Option A:

Creating multiple IAM policies introduces complexity and lacks column-level access control.Not efficient.

Option B:

Managing multiple IAM roles for granular access is operationally complex.Not efficient.

Option D:

Creating views in Glue adds unnecessary complexity and may not provide the level of granularity that Lake Formation offers.Not the best choice.

AWS References:

AWS Lake Formation:AWS Documentation - Lake Formation

Fine-Grained Permissions with Lake Formation:AWS Documentation - Fine-Grained Permissions

AWS Glue jobs are designed for extract, transform, and load (ETL) operations, which are perfect for transforming clinical trial data. AWS Glue integrates with AWS Key Management Service (KMS), allowing for customer-specific encryption keys, fulfilling the encryption requirement with minimal operational effort. Client-side encryption with AWS KMS ensures that the data is encrypted before it is sent to S3, aligning with the security needs specified in the scenario.

Key aspects:

AWS Glue: This managed ETL service simplifies data transformation, reduces operational overhead, and integrates seamlessly with KMS.

CSE-KMS: Client-side encryption with KMS ensures that the data is encrypted with customer-specific keys before it is processed or stored in S3, offering robust security​​.

Minimal Operational Overhead: Compared to managing an EMR cluster, AWS Glue automates much of the process, making it a lower-effort solution.

AWS Documentation: According to the AWS Well-Architected Framework, encryption with AWS KMS offers strong security controls that meet the needs of industries requiring high levels of confidentiality​​.

Why Option A is Correct:

ElastiCache for Redis: Provides persistent, scalable caching for in-progress transactions and SQL queries. Redis supports data durability and advanced features, making it suitable for transactional workloads.

Integration with Aurora: Easily integrates with the Aurora cluster to improve query performance.

Why Other Options Are Not Ideal:

Option B: CloudFront and S3 are unsuitable for transactional caching. EC2 instance store volumes are ephemeral and lack persistence.

Option C: Memcached does not offer persistence or advanced transactional support, unlike Redis.

Option D: Combining Redis with EC2 instance store is unnecessary; Redis alone meets all caching requirements.

AWS References:

Amazon ElastiCache:AWS Documentation - ElastiCache

Pre-Signed URLs: Allow temporary access to S3 buckets, making it easy to manage time-limited upload permissions without complex operational overhead.

Lambda for Automation: Automatically generates and provides pre-signed URLs when users authenticate, minimizing manual steps and code complexity.

Least Operational Overhead: Requires no custom authentication service or deep integration with STS or Cognito.

Amazon S3 Pre-Signed URLs Documentation

For an application requiring TCP communication and high availability:

Network Load Balancer (NLB)is the best choice for load balancing TCP traffic because it is designed for handling high-throughput, low-latency connections.

Auto Scaling groupensures that the application can automatically scale based on demand, adding or removing EC2 instances as needed, which is crucial for handling user growth.

Option C (Application Load Balancer): ALB is primarily for HTTP/HTTPS traffic, not ideal for TCP.

Option D (Manual scaling): Manually adding instances does not provide the automation or scalability required.

Option E (Gateway Load Balancer): GLB is used for third-party virtual appliances, not for direct application load balancing.

AWS References:

Network Load Balancer

Auto Scaling Group

For secure communication between Lambda and an RDS DB instance, AWS documentation recommends placing the Lambda functions inside the same VPC and controlling traffic using security groups.

Lambda should have a dedicated security group with outbound access to the VPC CIDR range, and the DB instance’s security group should explicitly allow inbound connections from the Lambda security group. This follows the "least privilege" principle while avoiding public exposure.

Options A and B expose the DB to unnecessary risk. Option D is insecure because it bypasses security groups.

Amazon S3 Intelligent-Tiering is designed for data with unknown or changing access patterns. It automatically moves data between frequent and infrequent access tiers based on usage. This tier offers immediate access to all objects, regardless of which tier they are stored in, while optimizing storage costs. S3 Intelligent-Tiering also provides the same high durability, availability, and security as other S3 storage classes and supports access from external resources using standard S3 APIs. Lifecycle policies and Glacier classes are more suitable for archival when infrequent access is predictable, but retrieval from Glacier classes is not immediate and incurs extra charges and delays.

Reference Extract from AWS Documentation / Study Guide:

"S3 Intelligent-Tiering is designed to optimize costs by automatically moving data between two access tiers when access patterns change. Data is always available and immediately accessible, making it ideal for unknown or unpredictable access patterns."

Source: AWS Certified Solutions Architect – Official Study Guide, S3 Storage Classes section.

AWS Key Management Service (AWS KMS) supports multi-Region keys, which are managed customer master keys that can be replicated to multiple Regions and treated as a single logical key. This allows applications in different Regions to encrypt and decrypt data using equivalent keys while AWS handles key replication, durability, and availability.

KMS is a fully managed key service, so the company does not need to operate hardware or manage low-level key storage. Tags combined with attribute-based access control (ABAC) let you enforce fine-grained access to keys by using IAM policies and condition keys, giving centralized and flexible access control with low operational overhead.

CloudHSM (Options C and D) requires managing HSM clusters, scaling, backups, and manual key operations, which significantly increases operational burden. Importing key material in KMS (Option B) adds lifecycle complexity and is unnecessary when native multi-Region keys exist.

Amazon ECS with AWS Fargate provides serverless container compute that can scale tasks dynamically in response to demand. This matches the unpredictable scaling requirements of a gaming workload. Aurora Serverless v2 provides on-demand, autoscaling relational database capacity while supporting complex SQL queries. EC2 with Auto Scaling (A) works but requires significant management overhead. Lambda with DynamoDB (B) is not suitable because the workload requires a relational database and long-running processes. ParallelCluster with HPC (D) is designed for batch scientific workloads, not dynamic, interactive gaming. Option C provides the correct balance of elasticity, performance, and managed services for both compute and relational database needs.

Edge-optimized API Gateway endpoints utilize the Amazon CloudFront global network to decrease latency for clients globally. This setup ensures that the request is routed to the closest edge location, significantly reducing response time and improving performance for worldwide users.

AWS Firewall Manager integrates with AWS Organizations to centrally manage and apply security group policies, AWS WAF rules, and AWS Shield Advanced protections. It automates the propagation of rules across accounts and Regions and can also audit and remediate noncompliant configurations.

To send data privately from on-premises to S3 buckets across multiple AWS accounts:

A: Using AWS Direct Connect with a private virtual interface (VIF) enables private connectivity from on-premises into the VPC.

E: After establishing the central VPC in a networking account, use VPC peering to allow access to S3 buckets across multiple AWS accounts.

“Direct Connect private virtual interface (VIF) allows private IP connectivity to VPC resources.”

“VPC Peering enables routing of traffic between VPCs using private IP addresses.”

— AWS Direct Connect Documentation

— VPC Peering Guide

Why not others:

B: Public VIF sends traffic over public AWS services—not fully private.

C: Interface endpoint is useful within a single account/VPC context.

D: Gateway endpoint doesn't solve inter-account routing.

Amazon S3 Intelligent-Tiering is designed for unknown or unpredictable access patterns, automatically moving objects to the most cost-effective tier without performance impact.

It is ideal when you do not know object size or access frequency.

S3 Standard (Option B) works but costs more.

S3 One Zone-IA and Glacier Deep Archive (Options D and A) are not appropriate because data is frequently accessed for processing and persists only 24 hours.

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Amazon Route 53 Resolver endpoints allow you to integrate DNS between AWS and on-premises environments easily. By creating inbound and outbound resolver endpoints, you can configure conditional forwarding rules so that DNS queries for your on-premises AD domain are forwarded to the on-premises DNS servers. This approach is fully managed, scales automatically, and requires the least administrative overhead.

AWS Documentation Extract:

"Route 53 Resolver provides DNS resolution between AWS and on-premises environments, using endpoints and forwarding rules to manage DNS query routing seamlessly."

(Source: Route 53 Resolver documentation)

A, D: Require provisioning, managing, and patching EC2 servers or domain controllers.

B: NS records in a private hosted zone do not provide true DNS forwarding.

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

Incremental Exports: Exporting DynamoDB data directly to Amazon S3 provides an automated, serverless way to make data available for analytics without operational overhead.

Analytics-Friendly Storage: Amazon S3 supports long-term analytics workloads and can integrate with tools like Athena or QuickSight.

DynamoDB Export to S3 Documentation

Amazon RDS does not support enabling encryption at rest on an existing unencrypted DB instance. To encrypt an existing RDS instance’s data at rest, the recommended method is to:

Take a snapshot of the unencrypted DB instance.

Create an encrypted copy of the snapshot using AWS KMS. This encrypted snapshot contains the existing data encrypted at rest.

Restore a new DB instance from the encrypted snapshot. This new instance will have encryption at rest enabled.

Additionally, to manage encryption keys securely, companies can use customer managed keys (CMKs) in AWS Key Management Service (KMS). CMKs provide greater control over key management policies, rotation, and usage permissions compared to default AWS managed keys. Using a CMK allows customization of access control and auditability.

Option A is incorrect because you cannot enable encryption directly on a snapshot; you must create an encrypted copy. Option C is invalid because encryption cannot be enabled by modifying an existing instance’s configuration. Option D refers to the default AWS managed key, which is less flexible than customer managed keys.

Background Jobs with Event Invocation Type:

The Event invocation type is asynchronous, meaning the Lambda function does not send an immediate result to the API Gateway and processes the request in the background. This is ideal for video encoding tasks that take time.

REST API vs. HTTP API:

REST APIs support advanced features like API keys, request validation, and throttling that HTTP APIs do not support fully.

Since the developer needs API keys and request validations, a REST API is the correct choice.

Integration with Lambda:

AWS Lambda integration is seamless with REST APIs, and using the Event invocation ensures asynchronous processing.

Incorrect Options Analysis:

Option A: HTTP API lacks full support for API keys and validation.

Option CandD: RequestResponse invocation type requires immediate responses, unsuitable for background jobs.

This solution directly addresses the scalability and high availability requirements with minimal downtime.

Additional Reader Instances: Adding more reader instances to the Aurora cluster will distribute the read load, improving the performance of the application under heavy read traffic. Aurora reader instances automatically replicate the data from the writer instance, enabling you to scale out read operations.

Amazon RDS Proxy: RDS Proxy improves database availability by managing database connections more efficiently and providing a connection pool. This reduces the overhead on the Aurora cluster during peak loads, further enhancing performance and availability without requiring changes to the application code.

Why Not Other Options?:

Option A (EventBridge and Lambda): This doesn’t directly address the performance and availability issues. Logging state changes and adding reader nodes on failure events doesn’t provide proactive scalability.

Option B (Zero-Downtime Restart and Activity Streams): Zero-Downtime Restart (ZDR) is useful for minimizing downtime during maintenance but doesn’t directly improve scalability. Database Activity Streams are more for security monitoring than for performance enhancement.

Option D (ElastiCache for Redis): While adding a caching layer can help with read performance, it introduces complexity and may not be necessary if additional reader instances can handle the load.

AWS References:

Amazon Aurora Scaling- Information on scaling Aurora clusters with reader instances.

Amazon RDS Proxy- Details on how RDS Proxy can improve database performance and availability.

AWS Global Accelerator is a service that improves global application availability and performance using the AWS global network. It supports both TCP and UDP protocols and provides optimized routing and lower latency for real-time applications such as VoIP, regardless of where the user is located globally.

AWS Documentation Extract:

"AWS Global Accelerator uses the AWS global network to optimize the path to your application endpoints, improving performance for TCP and UDP traffic, such as VoIP."

(Source: AWS Global Accelerator documentation)

B: CloudFront accelerates HTTP/S content, not TCP/UDP.

C: Route 53 geoproximity routing is for DNS-based routing, not for traffic acceleration.

D: Network Load Balancers support TCP/UDP, but do not address global latency or provide acceleration.

SAML 2.0-based federation allows organizations to integrate their on-premises Active Directory with AWS, enabling Single Sign-On (SSO) for AWS Management Console and AWS CLI/API access. This lets users continue using their existing AD credentials, removing the need to manage separate identities for AWS and on-premises systems. Mapping roles to AD groups provides granular access control and seamless management.

Reference Extract from AWS Documentation / Study Guide:

"AWS supports SAML 2.0 for federated access, enabling integration with Active Directory or other identity providers to provide single sign-on to AWS resources without creating separate IAM users."

Source: AWS Certified Solutions Architect – Official Study Guide, Identity and Access Management section.

Comprehensive and Detailed Step-by-Step Explanation:

The requirement is toprevent data deletion by any user, including administrators, for 7 years while allowing automatic deletion afterward.

S3 Object Lock in Compliance Mode (Correct Choice - C)

Compliance mode ensures that even the root user cannot delete or modify the objects during the retention period.

After 7 years, the S3 Lifecycle policy automatically deletes the objects.

This meets bothimmutability and automatic deletionrequirements.

Governance Mode (Option B - Incorrect)

Governance mode prevents deletion,but administrators can override it.

The requirement explicitly states thateven administrators must not be able to delete the data.

S3 Bucket Policy (Option A - Incorrect)

An S3 bucket policy candeny deletes, but policies can be modified at any time by administrators.

It does not enforce strict retention like Object Lock.

S3 Batch Operations Job (Option D - Incorrect)

A legal hold does not have an automatic expiration.

Legal holds must be manually removed, which is not efficient.

Why Option C is Correct:

S3 Object Lock in Compliance Mode prevents deletion by all users, including administrators.

The S3 Lifecycle policy deletes the data automatically after 7 years, reducing operational overhead.

AWS IAM Identity Center:

IAM Identity Centerprovides centralized access management for multiple AWS accounts within an organization and integrates seamlessly with existing identity providers (IdPs) throughSAML 2.0 federation.

It allows users to authenticate using their existing IdP credentials and gain access to AWS resources without the need to create and manage separate IAM users in each account.

IAM Identity Centeralso simplifies provisioning and de-provisioning users, as it can automatically synchronize users and groups from the external IdP to AWS, ensuring secure and managed access.

Integration with Existing IdP:

The solution involves configuringIAM Identity Centerto connect to the company's IdP using SAML. This setup allows employees to log in with their existing credentials, reducing the complexity of managing separate AWS credentials.

Once connected,IAM Identity Centerhandles authentication and authorization, granting users access to the AWS accounts based on their assigned roles and permissions.

Why the Other Options Are Incorrect:

Option A: Creating separateIAM usersfor each employee is not scalable or efficient. Managing thousands of IAM users across multiple AWS accounts introduces unnecessary complexity and operational overhead.

Option B: Using AWSroot userswith synchronized passwords is a security risk and goes against AWS best practices. Root accounts should never be used for day-to-day operations.

Option D:AWS Resource Access Manager (RAM)is used for sharing AWS resources between accounts, not for federating access for users across accounts. It doesn’t provide a solution for authentication via an external IdP.

AWS References:

AWS IAM Identity Center

SAML 2.0 Integration with AWS IAM Identity Center

By setting upIAM Identity Centerand connecting it to the existing IdP, the company can efficiently manage access for thousands of employees across multiple AWS accounts with a high degree of operational efficiency and security. Therefore,Option Cis the best solution.