Amazon AWS Certified Solutions Architect - Associate SAA-C03 Exam Dumps & Practice Test Questions
Question No 1:
An organization is operating a web application infrastructure within AWS and seeks a consistent tagging strategy across its resources. They aim to enforce a tagging policy that includes Amazon EC2 instances, Amazon RDS databases, and Amazon Redshift clusters. The goal is to ensure all these resources are properly tagged for reasons such as cost tracking, automation, and compliance. The company is also looking for a solution that minimizes manual management and maximizes automation using native AWS tools.
Which approach should a Solutions Architect recommend?
A. Use AWS Config rules to define and detect resources that are not properly tagged
B. Use AWS Cost Explorer to display resources that are not properly tagged. Tag those resources manually
C. Write custom scripts with API calls to detect untagged resources and run them periodically on an EC2 instance
D. Develop API-based scripts to detect untagged resources and run them on an AWS Lambda function triggered by Amazon CloudWatch Events
Correct Answer: A
Explanation:
To enforce a consistent resource tagging policy with minimal manual effort, AWS Config is the most suitable service. AWS Config provides the ability to continuously assess and audit the configuration of AWS resources. It enables organizations to define rules that automatically check whether certain conditions are met—for example, whether all EC2, RDS, and Redshift instances have specific tags. These rules can be used to evaluate resource compliance in real time and can trigger alerts or remediation workflows if any resources are found to be non-compliant.
Choosing AWS Config helps streamline operations by reducing the need for manual intervention. Unlike AWS Cost Explorer, which only provides visibility into cost and usage based on existing tags, AWS Config enforces compliance through automation. AWS Config supports managed rules like required-tags, which can be applied to a wide variety of AWS resources to validate the presence of mandatory tags.
By contrast, options B, C, and D require more hands-on effort. Using Cost Explorer for manual tagging (B) is inefficient and doesn't scale well. Writing custom scripts for EC2 or Lambda functions (C and D) increases complexity, requires ongoing maintenance, and lacks the native integration and management simplicity that AWS Config offers.
Additionally, AWS Config can be integrated with Systems Manager or Lambda for automated remediation, such as applying default tags or notifying administrators, further reducing operational overhead.
In summary, AWS Config offers a low-maintenance, scalable, and automated way to ensure resource tagging compliance across multiple AWS services. This makes it the optimal solution for organizations seeking a robust and efficient tagging enforcement strategy.
Question No 2:
A development team needs to host a static website that includes only HTML, CSS, JavaScript, and images. The website will be used internally by various teams in the company. They are looking for a highly affordable, simple, and scalable AWS-native hosting solution.
What should the team choose for hosting this website most cost-effectively?
A. Package the website into a Docker container and host it using AWS Fargate
B. Upload the static website content to an Amazon S3 bucket and enable static website hosting
C. Launch an Amazon EC2 instance and configure a web server (e.g., Apache or Nginx) to serve the website
D. Use AWS Lambda with the Express.js framework behind an Application Load Balancer to serve the website content
Correct Answer: B
Explanation:
Amazon S3 is designed to host static files efficiently and at a very low cost, making it the best option for hosting a simple internal website that consists of HTML, CSS, JavaScript, and images. When static website hosting is enabled on an S3 bucket, files can be served over HTTP directly from the bucket. This service offers high availability and durability by default, without any need to manage servers or other infrastructure.
Amazon S3 charges only for the amount of storage used and the number of HTTP requests, making it extremely cost-effective, particularly for internal sites with predictable or moderate traffic. There is no need to manage patching, scaling, or uptime, as AWS handles the underlying infrastructure.
In contrast, the other options introduce unnecessary complexity and cost. Option A, AWS Fargate, is designed for containerized applications but is excessive for simple file hosting. It requires defining container images and maintaining container tasks. Option C, using an EC2 instance with Apache or Nginx, adds overhead in the form of compute costs, instance monitoring, OS patching, and server maintenance—all for a task that S3 handles natively. Option D, which involves deploying a serverless application using Lambda and Express.js behind an Application Load Balancer, is better suited for dynamic web applications rather than static websites.
By choosing Amazon S3 for this use case, the development team benefits from minimal management, low operational costs, and easy scalability, all while staying within the AWS ecosystem. This makes it the most suitable solution for hosting an internal static website.
Question No 3:
A large-scale e-commerce company hosted on AWS is experiencing high user engagement and processes millions of sensitive financial transactions each day. These transactions must be distributed to various internal systems quickly and securely. Before storing the data, sensitive information must be removed or masked, and the cleaned data should be saved in a document database to support fast access and querying. The system must support high throughput, scalability, and near-real-time processing.
Which architecture should the Solutions Architect implement?
A. Store transactions in Amazon DynamoDB and use DynamoDB Streams to distribute data. Apply transformation during writes
B. Use Amazon Kinesis Data Firehose with AWS Lambda to sanitize data, then deliver it to Amazon S3 and DynamoDB
C. Stream transactions into Amazon Kinesis Data Streams. Process the data in real time with AWS Lambda to remove sensitive fields and then store the results in DynamoDB
D. Batch the transactions into S3 files. Use AWS Lambda to sanitize and store them in DynamoDB
Correct Answer: C
Explanation:
The optimal architecture for this high-throughput, low-latency transaction processing use case is using Amazon Kinesis Data Streams in combination with AWS Lambda and Amazon DynamoDB. Kinesis Data Streams is designed for real-time data streaming at massive scale. It can handle hundreds of thousands of records per second, and its multiple-shard architecture enables parallel processing by several consuming applications.
AWS Lambda can be invoked in response to new records in Kinesis Data Streams, allowing for real-time processing. Within the Lambda function, sensitive data fields can be identified and removed or encrypted before the sanitized data is stored in DynamoDB, a low-latency NoSQL document database suitable for fast queries.
This setup provides immediate processing and scalable ingestion, and it decouples data producers from consumers, enabling multiple internal applications to access and process the data independently. It also supports auditing, extensibility, and further downstream processing via additional Lambda functions or Kinesis consumers.
Option A incorrectly assumes that DynamoDB can modify data on write without custom logic, which it cannot do natively. Option B uses Kinesis Data Firehose, which is better for delivery to data lakes or S3 and lacks the flexible processing features needed here. Firehose also buffers records before delivery, which delays processing. Option D relies on a batch-based model that adds latency and doesn't support real-time streaming or immediate processing needs.
In conclusion, Option C provides a fully managed, serverless, scalable, and real-time solution that meets the company's needs for speed, security, and internal data distribution.
Question No 4:
A company is running its multi-tier applications on AWS and is subject to stringent industry regulations. To comply with these requirements, the company must maintain strong auditing, governance, and security practices. One of the key expectations is to monitor all configuration changes made to AWS resources—knowing exactly what changed and when. Additionally, it must keep a full record of API activity, detailing who performed each action, when it was performed, and from where.
As the solutions architect responsible for this environment, which combination of AWS services will provide complete visibility into both resource configuration changes and API activity?
A. Use AWS CloudTrail to track configuration changes and AWS Config to record API calls
B. Use AWS Config to track configuration changes and AWS CloudTrail to record API calls
C. Use AWS Config to track configuration changes and Amazon CloudWatch to record API calls
D. Use AWS CloudTrail to track configuration changes and Amazon CloudWatch to record API calls
Correct Answer: B
Explanation:
To achieve robust visibility into configuration changes and API activities in AWS, two key services—AWS Config and AWS CloudTrail—must be used together in a complementary fashion. Each one is specifically designed to cover a distinct aspect of governance, auditing, and compliance.
AWS Config is the service that enables organizations to continuously monitor and log the configuration of AWS resources. It keeps a detailed timeline of configuration states and changes across services like Amazon EC2, IAM roles, security groups, and many others. By recording exactly what was modified, when it happened, and the before-and-after state of the resource, Config provides an essential layer of traceability for compliance and operational insight. It also supports rule-based evaluation, so it can alert administrators when resources drift from compliance baselines.
AWS CloudTrail, by contrast, is focused on API-level activity logging. It captures who made each API call, the time of the request, the IP address it originated from, and the specific actions taken. This is crucial for forensic investigations, compliance audits, and understanding access patterns. CloudTrail logs every management and data event across AWS services and integrates with other services like Amazon CloudWatch and AWS Athena for deeper analysis.
The incorrect options highlight common misconceptions. Option A incorrectly assigns API logging to AWS Config, which it doesn't handle. Option C uses CloudWatch for API tracking, but CloudWatch is primarily for monitoring performance metrics and logs, not for API call recording. Option D also misattributes functionality to CloudWatch.
Combining AWS Config to capture what changed with AWS CloudTrail to identify who did what provides a complete audit trail, meeting the strictest compliance standards with minimal manual effort. This solution supports everything from real-time change detection to historical forensic analysis—making it the best choice for regulated industries.
Question No 5:
A tech company is deploying a public web application hosted on Amazon EC2 instances within a VPC. These instances are placed behind an Elastic Load Balancer (ELB) to ensure scalability and availability. The application’s domain is managed by a third-party DNS provider rather than Amazon Route 53. Due to the public exposure of the app, the company wants to guard against potential Distributed Denial of Service (DDoS) attacks. As a solutions architect,
Which AWS service should you recommend to best detect and mitigate such attacks and protect the infrastructure?
A. Enable Amazon GuardDuty in the AWS account
B. Enable Amazon Inspector on the EC2 instances
C. Enable AWS Shield and use Amazon Route 53
D. Enable AWS Shield Advanced and associate the ELB with it
Correct Answer: D
Explanation:
In scenarios where a public-facing web application is at risk of DDoS attacks, AWS provides native protections that range from basic to advanced. The optimal choice for advanced DDoS defense is AWS Shield Advanced, especially when the application is hosted behind an Elastic Load Balancer (ELB).
While AWS Shield Standard offers baseline DDoS protection at no extra cost, it covers only the most common, low-level attacks. Shield Advanced, on the other hand, is purpose-built for enterprises requiring robust mitigation against larger and more complex attack vectors.
By associating Shield Advanced with the ELB, organizations gain access to features such as:
Real-time attack detection and automated mitigation tailored to large-scale, sophisticated DDoS events.
24/7 access to the AWS DDoS Response Team (DRT), which provides hands-on support and expert guidance during attacks.
Cost protection for scale-out events triggered by DDoS, minimizing the financial impact of auto-scaling during high traffic.
Detailed diagnostics and visibility into attack vectors via integration with AWS CloudWatch, AWS WAF, and VPC Flow Logs.
The other options don’t fully address the problem:
Option A, Amazon GuardDuty, provides intelligent threat detection and anomaly-based monitoring but does not actively mitigate DDoS attacks.
Option B, Amazon Inspector, focuses on assessing security vulnerabilities and best practices for EC2 instances, but it doesn't provide network-layer protection.
Option C is invalid because it relies on Route 53, which is not in use—this company’s DNS is managed by a third party.
Given the need for real-time mitigation, attack diagnostics, and enhanced support during incidents, the best approach is to enable AWS Shield Advanced and associate it with the ELB. This ensures the infrastructure is well-protected from modern, high-impact DDoS threats.
Question No 6:
A company is building an AWS-based application that needs to store mission-critical data in Amazon S3 buckets located in two different AWS Regions. The company has strict requirements around security and resilience. Specifically, it mandates that all stored data must be encrypted using a customer managed key created in AWS KMS, and that this key must be usable in both Regions. Additionally, the encryption key and data must reside in both Regions. Lastly, the company prefers a low-maintenance solution.
Which setup will best satisfy these conditions?
A. Create an S3 bucket in each Region. Use server-side encryption with Amazon S3 managed keys (SSE-S3). Enable cross-Region replication between the buckets.
B. Create a multi-Region customer managed KMS key. Create an S3 bucket in each Region. Enable cross-Region replication. Use client-side encryption with the KMS key in the application.
C. Create a customer managed KMS key and S3 bucket in each Region. Use SSE-S3. Enable replication between buckets.
D. Create a customer managed KMS key and S3 bucket in each Region. Use SSE-KMS with that key. Enable replication.
Correct Answer: B
Explanation:
To meet the requirement of using a single encryption key across two AWS Regions, the use of multi-Region customer managed keys in AWS KMS is essential. These keys are designed to be cryptographically equivalent and can be used interchangeably across Regions—making them ideal for disaster recovery and redundancy.
In this solution, Option B stands out because it uses a multi-Region KMS key combined with client-side encryption. The application encrypts data using this key before uploading to the S3 buckets in each Region. Since the same key is replicated across Regions by AWS, the encrypted data can be decrypted in either Region, ensuring both data accessibility and regulatory compliance.
Let’s evaluate the shortcomings of other options:
Option A uses SSE-S3, which relies on Amazon’s managed keys, not customer managed ones. This violates the explicit requirement for customer-controlled encryption.
Option C also uses SSE-S3, again failing to meet the customer managed key mandate.
Option D uses SSE-KMS, which is closer to compliance, but standard customer managed KMS keys are Region-specific. This would require separate keys in each Region, meaning the same key cannot be used across both Regions, breaching the requirement.
By leveraging multi-Region KMS keys, the company benefits from automatic key replication with minimal operational effort. Additionally, client-side encryption ensures that the data remains secure in transit and at rest, with encryption handled within the application. This method satisfies all the security, redundancy, and operational efficiency needs—making Option B the best choice.
Question No 7:
A company is launching a new set of Amazon EC2 workloads and wants to manage remote access to these instances in a way that aligns with the AWS Well-Architected Framework. The team wants a scalable solution that minimizes manual operations, uses AWS-native services, and can be replicated easily across future deployments.
Which solution best meets these goals while keeping complexity and maintenance as low as possible?
A. Use EC2 Serial Console to directly access the instance terminal.
B. Assign IAM roles to EC2 instances and access them using AWS Systems Manager Session Manager.
C. Create SSH keys, install them on each EC2 instance, and deploy a bastion host for remote access.
D. Set up a Site-to-Site VPN and connect administrators via SSH through this network.
Correct Answer: B
Explanation:
The best solution for remote administration in this case is using AWS Systems Manager Session Manager, as described in option B. This service offers secure, scalable, and efficient access to EC2 instances without relying on traditional SSH or bastion host setups. It aligns well with the AWS Well-Architected Framework's operational excellence and security pillars.
Session Manager allows users to open interactive shell sessions to EC2 instances from the AWS Management Console or CLI. To use it, each EC2 instance must be configured with the SSM Agent and associated with an IAM role that includes the AmazonSSMManagedInstanceCore policy. Once configured, Session Manager removes the need to expose port 22 (SSH), use SSH key pairs, or set up and manage bastion hosts. This significantly reduces the attack surface and operational overhead.
Security-wise, all session activity can be logged to Amazon CloudTrail or Amazon S3, making it easy to audit and monitor user actions. For scalability, Session Manager supports automation via launch templates, Auto Scaling, and AWS CloudFormation, allowing consistent implementation across large fleets.
In contrast:
Option A (EC2 Serial Console) is limited in functionality and typically used for troubleshooting when an instance is otherwise unreachable. It doesn’t scale well and lacks built-in session management features.
Option C adds unnecessary complexity through manual key management and introduces additional risk with an exposed bastion host. Key rotation and instance configuration must be handled manually.
Option D involves setting up a VPN, which introduces network configuration complexity and ongoing maintenance. While secure, it’s a heavier lift than what’s necessary for this use case.
By contrast, option B delivers strong security, minimal configuration overhead, auditability, and full scalability—all through a native AWS service. It requires fewer moving parts and reduces the administrative burden, making it the most suitable and efficient approach.
Question No 8:
A company has hosted its static website using Amazon S3 and routes traffic through Amazon Route 53. Recently, as the site gains popularity with users worldwide, visitors have reported slow load times. The company wants to improve performance globally while continuing to host on S3 and use Route 53.
Which solution offers the best combination of cost-efficiency and improved performance?
A. Replicate the S3 bucket across all regions and implement geolocation routing with Route 53.
B. Use AWS Global Accelerator to improve routing for the static site.
C. Deploy an Amazon CloudFront distribution in front of the S3 bucket and update Route 53 to point to it.
D. Enable S3 Transfer Acceleration to enhance file transfer performance.
Correct Answer: C
Explanation:
For static websites hosted on Amazon S3, performance issues for global users are often caused by latency due to geographic distance from the hosting region. The most cost-effective and performance-enhancing solution in this context is to implement Amazon CloudFront, as outlined in option C.
CloudFront is AWS’s content delivery network (CDN), designed to cache and distribute static and dynamic content from edge locations around the world. When integrated with an S3 bucket, CloudFront reduces latency by serving content from the nearest edge location to the user. This results in faster load times and an overall better experience, especially for users outside the S3 bucket’s hosting region.
In addition to performance gains, CloudFront offers built-in features such as DDoS protection, HTTPS support, and detailed access logs. It works seamlessly with Route 53; updating DNS records to point to the CloudFront distribution ensures that requests are directed to the CDN rather than the origin S3 bucket.
Let’s look at the alternatives:
Option A involves replicating S3 buckets across regions and configuring geolocation routing. While technically feasible, this introduces significant operational complexity and storage costs. Managing updates across multiple buckets and keeping data synchronized is inefficient for static content.
Option B uses AWS Global Accelerator, which is optimized for TCP and UDP-based applications, such as APIs or real-time services—not static websites. It’s also more expensive and not ideal for S3-based web hosting.
Option D, S3 Transfer Acceleration, is designed to speed up large file uploads and downloads over long distances but lacks the caching benefits that are essential for high-read, low-write static websites.
Therefore, CloudFront provides the optimal blend of cost-efficiency, low latency, and global scalability, making option C the most appropriate solution.
Question No 9:
A tech company runs a high-traffic application with a MySQL database hosted on Amazon RDS. This database has over 10 million rows and uses 2 TB of General Purpose SSD (gp2) storage. Recently, the development team noticed significant delays in insert operations, sometimes exceeding 10 seconds. A review indicates that the bottleneck is tied to storage throughput and IOPS.
What is the best way to resolve this issue effectively?
A. Upgrade the storage type to Provisioned IOPS SSD for the RDS instance.
B. Migrate to a memory-optimized instance class.
C. Switch the instance class to a burstable performance tier like the T series.
D. Enable Multi-AZ and read replicas for high availability.
Correct Answer: A
Explanation:
The root cause of the performance issue in this scenario is tied to storage input/output operations per second (IOPS), which are a critical factor for high-volume insert and update workloads. The database is currently using General Purpose SSD (gp2), which provides baseline performance proportional to the volume size—approximately 3 IOPS per GB. For a 2 TB volume, that equates to 6,000 IOPS. However, once the system exhausts its burst credits or consistently exceeds this baseline, performance drops.
Provisioned IOPS (io1 or io2) storage, described in option A, is specifically engineered for I/O-intensive applications that demand sustained and predictable performance. By upgrading to this storage type, the company can explicitly define the IOPS rate, ensuring consistent throughput even under heavy write conditions. Provisioned IOPS storage can support up to 256,000 IOPS with io2 Block Express, which is far superior to the burst-based gp2 model.
Now, consider the other options:
Option B, migrating to a memory-optimized instance, might help if the problem were due to insufficient RAM or slow query caching. However, it doesn't address the core issue of disk I/O, which is crucial for frequent inserts and updates.
Option C, switching to a burstable instance type like T-series, is not ideal for a workload with sustained demand. These instances rely on CPU credits, which are quickly depleted under heavy use, leading to throttled performance.
Option D, implementing Multi-AZ and read replicas, improves high availability and read scalability, but it doesn’t mitigate slow insert or update performance, which is tied to disk throughput.
In summary, option A provides a direct and reliable fix by enhancing the I/O capacity of the RDS instance. It ensures that the storage subsystem can handle high volumes of write operations without performance degradation, making it the most effective choice for this use case.
Question No 10:
A company plans to deploy a web application that serves users globally. The application architecture consists of web servers that serve static content and an application layer that processes dynamic requests. The company requires the solution to provide low-latency responses to users, be highly available, and automatically scale during demand spikes. Additionally, the company wants to minimize administrative overhead.
Which architecture will best meet these requirements using AWS services?
A. Launch web and application servers in a single Availability Zone within an Auto Scaling group behind an Application Load Balancer. Use Amazon EBS for shared storage.
B. Use Amazon CloudFront to distribute static content stored in Amazon S3. Deploy the application layer on AWS Lambda behind Amazon API Gateway.
C. Deploy web and application servers across multiple regions. Use Route 53 for routing. Store static content in Amazon EFS shared across regions.
D. Use Amazon EC2 Spot Instances to run all workloads. Store static content on instance volumes and deploy Auto Scaling for high availability.
Correct Answer: B
Explanation:
This question tests your understanding of designing highly available, low-latency, and scalable solutions using serverless and managed AWS services. Let’s break down why B is the best option and analyze the others.
Option B (Correct):
Amazon CloudFront is a global Content Delivery Network (CDN) service that caches and serves static content (like HTML, CSS, JS, images) closer to users across the world, reducing latency.
Amazon S3 is an ideal and highly durable storage solution for static content and works seamlessly with CloudFront.
AWS Lambda allows for serverless computing, meaning there are no servers to provision or manage. It automatically scales and handles traffic fluctuations well.
Amazon API Gateway provides a fully managed front door for the Lambda functions, managing HTTP requests and enabling RESTful interfaces.
This combination results in minimal operational overhead, global low-latency delivery, automatic scaling, and high availability.
Option A:
Launching in a single Availability Zone presents a single point of failure, which doesn't meet the high availability requirement.
Amazon EBS volumes cannot be shared across instances unless using a special file system like FSx for Lustre or clustering, adding complexity.
Option C:
Using Amazon EFS across regions is not natively supported without replication tools and complex setup.
Deploying across multiple regions adds operational complexity and cost and is not necessary unless required for compliance or ultra-low latency.
Not ideal for minimizing administrative overhead.
Option D:
EC2 Spot Instances are cost-effective but not ideal for critical workloads unless combined with On-Demand or Reserved Instances.
Storing static content on instance volumes is not persistent or durable and doesn't scale or distribute globally like CloudFront/S3.
Lacks the global scalability and availability required.
In conclusion, Option B provides a fully managed, cost-effective, scalable, and low-latency architecture by leveraging CloudFront, S3, Lambda, and API Gateway—making it ideal for the needs described and aligned with best practices for the SAA-C03 exam.
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