SAA-C03 Exam Dumps - Amazon Web Services AWS Certified Associate Questions and Answers

Amazon API Gateway with CloudFront: API Gateway allows you to create, deploy, and manage APIs, while CloudFront provides a CDN to deliver content with low latency and high transfer speeds.

AWS WAF (Web Application Firewall):

AWS WAF can be configured in CloudFront to protect against common web exploits, including SQL injection and cross-site scripting (XSS).

WAF allows you to create custom rules to block specific attack patterns and can be managed centrally.

Configuration:

Deploy your APIs using Amazon API Gateway.

Set up an Amazon CloudFront distribution in front of the API Gateway.

Configure AWS WAF on the CloudFront distribution to apply security rules.

Operational Efficiency: This solution provides robust protection with minimal operational overhead by leveraging managed AWS services, ensuring that your APIs are secure without extensive custom implementation.

The requirement calls for three capabilities at fleet scale: (1) regular security/vulnerability scanning of EC2 instances, (2) scheduled patching, and (3) reporting on patch compliance/status. The AWS-managed services designed for this are Amazon Inspector for vulnerability scanning and AWS Systems Manager Patch Manager for patch orchestration and compliance reporting.

Amazon Inspector provides automated vulnerability management that can assess EC2 instances for software vulnerabilities and exposure, producing findings that identify missing patches and vulnerable packages. This addresses the security scanning portion without requiring custom tooling on each instance beyond standard agent/configuration requirements.

Systems Manager Patch Manager allows you to define patch baselines, schedule patching operations via maintenance windows, and apply patches across large fleets in a controlled manner. Patch Manager also provides compliance views and reporting so you can see which instances are compliant, which are missing patches, and the results of patch operations. This directly meets the need to patch “on a regular schedule” and to “provide a report of each instance’s patch status.”

The other options are mismatched services: Macie focuses on discovering and protecting sensitive data (especially in S3), not scanning EC2 for software vulnerabilities. GuardDuty is for threat detection based on logs and events; it is not an EC2 vulnerability scanner and does not function as a patching orchestrator. Detective helps investigate security events and relationships; it is not a vulnerability scanning or patch deployment tool. Additionally, cron jobs on each instance create high operational overhead and inconsistent reporting—exactly what the company wants to avoid.

Therefore, D is the correct, operationally excellent approach: use Inspector for vulnerability scanning and Systems Manager Patch Manager for automated, scheduled patching with centralized compliance reporting.

AWS Backup supports cross-Region backup for Amazon EFS, allowing automated, scheduled backups and replication to another Region. This managed service simplifies backup management and ensures data resilience without the need for custom scripts or manual processes

The Application Load Balancer (ALB) supports sticky sessions (session affinity) using application cookies. AWS WAF integrates natively with ALB to provide Layer 7 protection at the same endpoint.

From AWS Documentation:

“You can enable sticky sessions for your Application Load Balancer target groups to ensure that a user’s requests are consistently routed to the same target. AWS WAF integrates with Application Load Balancer to protect your web applications from common exploits.”

(Source: Elastic Load Balancing User Guide & AWS WAF Developer Guide)

Why C and E are correct:

C: ALB operates at Layer 7 (HTTP/HTTPS), supports sticky sessions, and can serve as a public endpoint.

E: AWS WAF can be directly associated with the ALB to inspect traffic and enforce rules.Together, they fulfill both the security and session affinity requirements.

Why others are incorrect:

A: Network Load Balancer doesn’t support session affinity.

B: Gateway Load Balancer is used for virtual appliances, not web applications.

D: Using EIPs bypasses load balancing and WAF integration.

Hardcoded database credentials create security risks and operational challenges, especially when compliance requires regular credential rotation. AWS Secrets Manager is the AWS-recommended service for securely storing, managing, and rotating secrets such as database credentials.

Option B is the correct solution because Secrets Manager natively supports automated credential rotation using AWS-managed or custom Lambda functions. By enabling rotation on a 90-day schedule, Secrets Manager automatically updates the credentials in the RDS database and stores the new values securely. The application retrieves credentials dynamically at runtime, eliminating the need for storing passwords on EC2 instances.

Options A, C, and D all rely on custom scripts, SSH access, and manual distribution of secrets, which significantly increases operational overhead, security risk, and failure potential. These approaches also violate AWS best practices by spreading sensitive credentials across multiple hosts.

Secrets Manager integrates with IAM for fine-grained access control, supports auditing through AWS CloudTrail, and improves overall security posture while reducing operational complexity. Therefore, B best meets the requirements in a secure, scalable, and compliant manner.

EC2 Account Attributes: Amazon EC2 allows you to set account attributes to automatically encrypt new EBS volumes. This ensures that all new volumes created in your account are encrypted by default.

Configuration Steps:

Go to the EC2 Dashboard.

Select " Account Attributes " and then " EBS encryption " .

Enable default EBS encryption and select the default AWS KMS key or a customer-managed key.

Prevention of Unencrypted Volumes: By setting this account attribute, you ensure that it is not possible to create unencrypted EBS volumes, thereby enforcing compliance with security requirements.

Operational Efficiency: This solution requires minimal configuration changes and provides automatic enforcement of encryption policies, reducing operational overhead.

The lowest-overhead centralized access model is to connect the existingon-premises Active Directoryby usingAD Connectorand then manage AWS account access throughIAM Identity Center permission sets. AWS documentation explains that IAM Identity Center providesone place to assign permissions to multiple AWS accounts, and AD Connector is specifically designed to let AWS services use an existing directory without storing directory information in AWS. This approach preserves the company’s current authentication source and adds centralized authorization across the organization. Creating IAM users or scripting cross-account role assignments would add significant administrative work and weaken the identity model.

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Durable storage of incoming orders with buffering and ability to handle surges is exactly what Amazon SQS is designed for. SQS provides highly durable, scalable queues that decouple producers from consumers.

Centrally tracking workflow steps is a core use case of AWS Step Functions, which gives a visual workflow and state machine, tracks the state of each order, and can orchestrate calls to multiple microservices (in this case, Lambda functions).

Combining SQS + Step Functions + Lambda gives:

Durable queueing for orders (SQS).

Loose coupling and surge handling (SQS decoupling + auto-scaling Lambda).

Central orchestration and tracking of order-processing steps (Step Functions).

Why the other options are not correct:

A: SNS is a pub/sub service, not a durable work queue, and is not designed for “store-and-retry until processed” workloads in the same way SQS is.

C: SQS + EventBridge provides decoupling but no central, stateful workflow tracking; EventBridge is event routing, not workflow orchestration.

D: SNS + EventBridge still lacks durable order storage and explicit centralized workflow/state tracking.

AWS Glue Crawler: AWS Glue is a fully managed ETL (Extract, Transform, Load) service that makes it easy to prepare and load data for analytics. A Glue crawler can automatically discover new data and schema in Amazon S3, making it easy to keep the data catalog up-to-date.

Crawling the Data:

Set up an AWS Glue crawler to scan the S3 bucket containing the clickstream data.

The crawler will automatically detect the schema and create/update the tables in the AWS Glue Data Catalog.

Amazon Athena:

Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL.

Once the data catalog is updated by the Glue crawler, use Athena to query the clickstream data directly in S3.

Operational Efficiency: This solution leverages fully managed services, reducing operational overhead. Glue crawlers automate data cataloging, and Athena provides a serverless, pay-per-query model for quick data analysis without the need to set up or manage infrastructure.

AWS Spot best practices recommend diversifying capacity across multiple instance types and Availability Zones and using the capacity-optimized (price-capacity-optimized) allocation strategy to choose pools with the deepest capacity for higher availability. Adding a small On-Demand base in the Auto Scaling group maintains steady, uninterrupted baseline processing while keeping costs low and absorbing Spot interruptions. Option C (lowest price) increases interruption risk. Capacity Reservations (B) target On-Demand capacity guarantees and add cost, not needed for Spot-based elasticity. Option E is redundant; diversification is already achieved with (D). This combination maximizes resiliency of Spot workloads while preserving strong cost efficiency and aligns with AWS guidance for fault-tolerant, stateless applications on Spot.

Amazon S3 Glacier Flexible Retrieval is designed for long-lived, infrequently accessed data where retrieval times of minutes to hours are acceptable. It offers very low storage cost per GB while still supporting faster retrieval than archival tiers that can take many hours or days.

The requirement states that data is rarely accessed and must be retrievable within 12 hours. Glacier Flexible Retrieval meets this retrieval-time requirement and is more cost-effective per GB than Standard and Infrequent Access storage classes for long-term, rarely accessed data.

S3 Standard, S3 Standard-IA, and S3 One Zone-IA are optimized for more frequent or lower-latency access and have higher storage cost per GB compared to Glacier Flexible Retrieval.

Amazon Route 53 is a highly available and scalable authoritative DNS service. To move a public domain, you create a public hosted zone, import or recreate the zone records, and then update the registrar to use the Route 53 name servers assigned to the zone. Route 53 is globally distributed and designed for rapid propagation and resilience, and supports features such as health checks and routing policies. A private hosted zone (Option B) is resolvable only by VPCs that are associated with it and is not for public internet DNS. Directory Service and zone transfers (Option C) are unrelated to Route 53 public DNS hosting. Route 53 Resolver inbound endpoints (Option D) provide hybrid DNS forwarding for VPC workloads, not authoritative public hosting. Therefore, the fastest AWS-native migration path to a resilient managed DNS is to create a Route 53 public hosted zone and import the existing zone file.

AWS recommends using AWS IAM Identity Center (formerly AWS SSO) for centralized authentication and access control across multiple accounts in an AWS Organization, especially when integrating with an external IdP.

From AWS Documentation:

“Use IAM Identity Center to provide centralized access to multiple AWS accounts or applications. You can integrate with an external IdP via SAML 2.0. Assign users permissions through permission sets that define the roles users can assume.”

(Source: AWS IAM Identity Center User Guide)

Why B and E are correct:

E enables centralized identity federation using IAM Identity Center with your external IdP.

B uses permission sets to apply least-privilege access roles to users and groups across accounts, in alignment with the principle of least privilege.

Why others are incorrect:

Option A: IAM users in each account break centralized access model and are hard to manage at scale.

Option C: Managing individual IAM roles and inline policies across accounts is not scalable.

Option D: Per-account SAML providers are redundant when using IAM Identity Center, which provides centralized federation.

A DynamoDB gateway VPC endpoint is the most secure and cost-effective option because it allows private access from the VPC to DynamoDB without requiring an internet gateway, NAT gateway, or public IP path. Gateway endpoints for DynamoDB use route table entries to direct traffic to the DynamoDB prefix list over the AWS network. Endpoint policies can further restrict access to only the required DynamoDB tables, which supports least privilege. Interface endpoints are available for DynamoDB, but they add hourly and data processing charges, so they are not the most cost-effective choice when a gateway endpoint satisfies the requirement. VPC peering is not valid because DynamoDB is an AWS managed service, not a customer VPC that can be peered.

AWS KMS automatic key rotationis the simplest and most operationally efficient solution. Enabling automatic key rotation ensures that KMS automatically generates new key material for the key every year without requiring manual intervention.

Option B:Configuring alerts to rotate keys introduces operational overhead as the actual rotation must still be managed manually.

Option C:Scheduling a Lambda function to rotate keys adds unnecessary complexity compared to enabling automatic key rotation.

Option D:Using a CloudFormation stack to run a Lambda function for key rotation increases operational overhead and complexity unnecessarily.

AWS Documentation References:

AWS KMS Key Rotation

Using Customer-Managed Keys with Amazon RDS

The requirement that the security team manage key lifecycle actions such as creation, deletion, and rotation points tocustomer managed AWS KMS keys, not SSE-S3. Customer managed KMS keys allow fine-grained IAM authorization for both the Lambda execution role and the security administrator group. That supports least privilege because the Lambda role can be restricted to decrypt usage, while the administrator group can be limited to the KMS management actions it actually needs. The other answers either do not provide the required KMS management control or grant permissions too broadly. Therefore, using customer managed KMS keys with separate, scoped IAM permissions for decryption and key administration is the correct design.

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Maintaining two NAT gateways for production ensures high availability. Reducing to one NAT gateway in non-production environments lowers cost while maintaining necessary connectivity. This approach is recommended by AWS for cost optimization in non-critical environments.

Reference Extract:

" For environments that do not require high availability, you can reduce costs by using a single NAT gateway and updating route tables accordingly. "

Source: AWS Certified Solutions Architect – Official Study Guide, Cost Optimization and NAT Gateway section.

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.

Analysis:

The solution must handle variable sales volumes, preserve transaction information, and store data in an Amazon Aurora database with minimal operational overhead. UsingAPI Gateway, AWS Lambda, and SQSis the best option because it provides scalability, reliability, and resilience.

Why Option A is Correct:

API Gateway: Serves as an entry point for transaction data in a serverless, scalable manner.

AWS Lambda: Processes the transactions and sends them to Amazon SQS for queuing.

Amazon SQS: Buffers the transaction data, ensuring durability and resilience against spikes in transaction volume.

Second Lambda Function: Processes messages from the SQS queue and updates the Aurora database, decoupling the workflow for better scalability.

Dead-Letter Queue (DLQ): Ensures failed transactions are logged for later debugging or reprocessing.

Why Other Options Are Not Ideal:

Option B:

Using an ALB with ECS on EC2 introduces operational overhead, such as managing EC2 instances and scaling ECS tasks.Not cost-effective.

Option C:

EKS is highly operationally intensive and requires Kubernetes cluster management, which is unnecessary for this use case.Too complex.

Option D:

Amazon Data Firehose and DMS are not designed for real-time transactional workflows. They are better suited for data analytics pipelines.Not suitable.

AWS References:

Amazon API Gateway:AWS Documentation - API Gateway

AWS Lambda:AWS Documentation - Lambda

Amazon SQS:AWS Documentation - SQS

Amazon Aurora:AWS Documentation - Aurora

AWS Lake Formation natively supports fine-grained access control, including:

Row-level security

Cell/column-level security

These are implemented through data filters and Lake Formation permissions on governed tables and views. This allows you to centrally define which users or groups can access which rows and which columns, including sensitive data fields, with minimal custom code or maintenance.

Why others are incorrect:

A: IAM alone does not provide row-level or cell-level data security inside Lake Formation tables.

C and D: Using Lambda to scrub or periodically remove sensitive data is complex, error-prone, and high overhead compared to built-in Lake Formation data filters.