Amazon AWS Certified Solutions Architect – Associate SAA-C03 Exam Dumps and Practice Test Questions Set 5 Q81-100

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Question 81:

A company wants to migrate a large on-premises Oracle database to AWS with minimal downtime while ensuring high availability and automated maintenance. Which AWS service combination is most suitable?

Answer:

A) AWS Database Migration Service (DMS) with Amazon RDS Multi-AZ Oracle
B) EC2 with self-managed Oracle
C) S3 Standard only
D) DynamoDB

Explanation:

Option A is correct. AWS Database Migration Service (DMS) enables near-zero downtime migration by continuously replicating changes from the source database. When paired with Amazon RDS Multi-AZ Oracle, the database automatically handles high availability, failover, backups, and software patching.

EC2 with self-managed Oracle requires extensive operational management, including patching, replication, backup, monitoring, and failover configuration, which increases administrative overhead and risk. S3 is object storage, unsuitable for transactional relational databases. DynamoDB is a NoSQL database, incompatible with Oracle workloads and relational queries.

DMS supports continuous replication and schema conversion when moving from heterogeneous databases. The AWS Schema Conversion Tool (SCT) can convert database schemas and stored procedures to Oracle-compatible formats. Multi-AZ RDS ensures synchronous replication to a standby instance in another Availability Zone. If the primary instance fails, RDS automatically promotes the standby to minimize downtime.

Security best practices include encrypting data at rest with AWS KMS, enforcing least-privilege IAM policies, and auditing all changes with AWS CloudTrail. Monitoring is performed using CloudWatch metrics and alarms, which track replication lag, throughput, and latency. Error handling and automated notifications ensure operational visibility during migration.

This architecture reduces operational complexity while providing a reliable, secure, and high-performance Oracle database in the cloud. DMS with RDS Multi-AZ is ideal for enterprises requiring minimal downtime, high availability, and operational simplicity during database migration, aligning with AWS Well-Architected principles for reliability, operational excellence, security, and performance efficiency.

Question 82:

A company wants to implement a highly available, low-latency caching layer for its web application that reduces load on the database and supports both read-heavy and write-heavy workloads. Which AWS service is recommended?

Answer:

A) Amazon ElastiCache (Redis)
B) S3 only
C) DynamoDB
D) RDS Multi-AZ

Explanation:

Option A is correct. Amazon ElastiCache Redis provides an in-memory caching layer, significantly reducing database load and improving application performance. Redis supports high-performance read and write operations, replication, persistence, and failover, making it suitable for highly dynamic, high-traffic applications.

S3 is object storage, unsuitable as a caching layer. DynamoDB is a NoSQL database; while fast, it is not a dedicated in-memory cache and may increase costs for read-heavy workloads. RDS Multi-AZ ensures high availability for relational databases but does not provide in-memory caching to reduce read latency.

ElastiCache supports clustering and replication across nodes, ensuring high availability. Integration with VPCs and security groups enforces access control. CloudWatch metrics provide visibility into cache performance, hit/miss ratios, and memory usage. DAX can be added for DynamoDB applications, but Redis is preferred when advanced caching functionality, persistence, and pub/sub capabilities are required.

Use cases include session storage, leaderboard management, gaming applications, real-time analytics, and frequently accessed content. This caching architecture reduces response times to microseconds, reduces database costs, and improves overall system scalability and user experience.

By leveraging ElastiCache Redis, organizations achieve high performance, fault tolerance, and operational simplicity. It aligns with AWS Well-Architected principles, including reliability, performance efficiency, and cost optimization, while providing a scalable solution for web applications that demand rapid data access and minimal latency.

Question 83:

A company wants to implement a serverless event-driven workflow to process incoming files in S3, apply transformations, and store results in a database. Which services should be used together?

Answer:

A) S3, Lambda, and DynamoDB
B) EC2, RDS, and S3
C) S3 only
D) Elastic Beanstalk with RDS

Explanation:

Option A is correct. S3 can trigger Lambda functions when files are uploaded, enabling automated processing and transformation. Lambda executes code without provisioning servers and scales automatically with incoming events. Processed data can then be stored in DynamoDB for highly available, low-latency access.

EC2 requires manual provisioning, scaling, and operational overhead. S3 alone cannot process files. Elastic Beanstalk provides application deployment but is not serverless and requires management of underlying resources.

Serverless architecture ensures fault tolerance, cost efficiency, and operational simplicity. Lambda integrates with IAM roles to enforce least-privilege access to S3 and DynamoDB. CloudWatch monitors Lambda execution, logs errors, and tracks metrics. Step Functions can orchestrate complex workflows, retries, and exception handling.

This architecture supports ETL workflows, document processing, analytics pipelines, or automated compliance checks. Security features include encryption at rest (S3 SSE-KMS), data in transit encryption, and role-based access control. The system scales dynamically with event volume, providing near-real-time processing.

By combining S3, Lambda, and DynamoDB, organizations achieve a fully managed, scalable, and fault-tolerant serverless architecture. Operational overhead is minimized, compliance requirements are met, and the solution is aligned with AWS Well-Architected Framework principles for security, reliability, performance, and operational excellence.

Option A is the most appropriate choice for implementing a serverless, event-driven workflow to process files in S3, apply transformations, and store results in a database. Using S3, Lambda, and DynamoDB together allows organizations to build highly scalable and fully managed solutions without managing servers. S3 serves as the initial storage point for incoming files, and it can be configured to trigger Lambda functions automatically whenever new objects are uploaded. This event-driven architecture ensures that files are processed in near real-time as they arrive, removing the need for manual intervention or scheduled batch processing.

Lambda is a serverless compute service that executes code in response to events. It provides automatic scaling, fault tolerance, and high availability, enabling organizations to run processing logic such as data transformation, validation, or enrichment without worrying about infrastructure provisioning or scaling. Lambda integrates seamlessly with IAM roles, ensuring that functions have precise permissions to access S3, DynamoDB, and other resources, which enhances the security of the workflow. CloudWatch can monitor the execution of Lambda functions, providing logging, metrics, and error tracking, which is critical for operational visibility and troubleshooting.

DynamoDB, as a fully managed NoSQL database, stores the processed data efficiently and provides low-latency, high-throughput access. Its serverless nature ensures that it scales automatically with the volume of processed events, supporting dynamic workloads without the need for manual capacity planning. This combination of S3, Lambda, and DynamoDB supports a variety of use cases, including ETL pipelines, analytics, document processing, and automated compliance checks, while maintaining cost efficiency by paying only for actual usage.

Other options are less suitable for this scenario. Option B, using EC2, RDS, and S3, involves server-based components that require provisioning, scaling, patching, and ongoing maintenance, which increases operational overhead. Option C, relying on S3 alone, cannot perform processing or transformation tasks. Option D, Elastic Beanstalk with RDS, provides managed deployment but is not fully serverless and still requires infrastructure management. By selecting S3, Lambda, and DynamoDB, organizations achieve a fully serverless, event-driven architecture that is secure, scalable, reliable, and aligned with best practices for operational excellence.

Question 84:

A company wants to enforce organizational security policies across multiple AWS accounts to ensure all S3 buckets are encrypted and no public access is allowed. Which combination of services should be used?

Answer:

A) AWS Config with AWS Organizations
B) S3 only
C) IAM policies alone
D) EC2 instances

Explanation:

Option A is correct. AWS Config continuously evaluates S3 bucket configurations against organizational rules, such as enforcing encryption and denying public access. Using AWS Organizations, these rules can be applied centrally across multiple accounts, ensuring consistent compliance.

S3 alone cannot enforce organizational policies. IAM policies control access but do not enforce bucket-level encryption or public access prevention. EC2 instances do not provide centralized governance.

Config rules can trigger automated remediation, such as applying bucket policies or encryption. Cross-account aggregation consolidates compliance data for monitoring and auditing. CloudWatch provides alerts when non-compliant resources are detected.

This approach improves security posture, ensures regulatory compliance (PCI DSS, HIPAA, GDPR), and reduces operational risk. Integration with CloudTrail provides auditing for policy violations. Automated remediation ensures that resources adhere to security standards without manual intervention, supporting operational efficiency and governance.

By leveraging Config and Organizations, organizations can enforce consistent security policies, automate compliance, and reduce the risk of misconfigurations, fully aligning with AWS Well-Architected Framework principles for security, reliability, and operational excellence.

Question 85:

A company wants to provide low-latency access to frequently accessed data stored in S3 for a global audience while minimizing cost. Which AWS service combination is recommended?

Answer:

A) Amazon CloudFront with S3 origin
B) S3 only
C) EC2 only
D) RDS only

Explanation:

Option A is correct. CloudFront caches S3 content at edge locations worldwide, reducing latency for end users. It also reduces data transfer costs from the origin and supports dynamic content acceleration. HTTPS ensures secure access, while integration with WAF provides protection against DDoS and application-level attacks.

S3 alone delivers content but cannot accelerate access globally. EC2 cannot provide a global CDN without manual configuration. RDS is relational and unrelated to content delivery.

CloudFront supports caching strategies, signed URLs, and Lambda@Edge for edge processing. Monitoring via CloudWatch provides insights into request patterns, cache efficiency, and origin health. Integration with AWS Shield Advanced enhances security against sophisticated attacks.

This architecture optimizes performance, reliability, and cost efficiency, ensuring consistent low-latency experiences for a global audience. It supports scalability, reduces operational overhead, and aligns with AWS Well-Architected Framework principles for performance, security, and operational excellence.

Option A is the recommended choice for providing low-latency access to frequently accessed data stored in S3 for a global audience while minimizing costs. Amazon CloudFront is a content delivery network (CDN) that caches content at edge locations around the world. When paired with an S3 origin, CloudFront ensures that end users can access content from the edge location closest to them, significantly reducing latency compared to fetching data directly from S3 in a single region. This caching mechanism not only improves user experience but also reduces the number of requests made to the S3 bucket, which can lower data transfer and retrieval costs.

CloudFront supports a wide range of caching strategies, including time-to-live (TTL) settings and cache invalidation, allowing organizations to control how long content remains at the edge. It also provides secure delivery of content over HTTPS, ensuring encryption of data in transit. Integration with AWS Web Application Firewall (WAF) and AWS Shield offers protection against distributed denial-of-service (DDoS) attacks and other application-layer threats, enhancing the overall security posture of the system. For dynamic content or custom logic at the edge, Lambda@Edge can be used to manipulate requests and responses closer to the user, further improving performance and flexibility.

Using S3 alone, while cost-effective for storage, does not provide global acceleration or caching, resulting in higher latency for users located far from the S3 bucket’s region. EC2 can serve content but requires manual configuration to achieve global reach, and it lacks the integrated caching and security features of CloudFront. RDS is a managed relational database service and is unrelated to content delivery, making it unsuitable for this scenario.

CloudFront also integrates with CloudWatch to provide detailed monitoring and metrics, such as request rates, cache hit ratios, and origin health, which help optimize performance and troubleshoot issues. This combination of CloudFront with S3 delivers a scalable, reliable, and cost-efficient solution, ensuring consistent low-latency experiences for a worldwide audience. It reduces operational overhead, supports high availability, and aligns with AWS Well-Architected Framework best practices for performance, security, and operational excellence.

Question 86:

A company wants to analyze real-time streaming data from IoT sensors and store processed data in a highly available database for analytics. Which combination of AWS services should be used?

Answer:

A) Amazon Kinesis Data Streams, Lambda, and DynamoDB
B) EC2 with cron jobs
C) S3 only
D) RDS Multi-AZ

Explanation:

Option A is correct. Kinesis Data Streams ingests streaming IoT data and partitions it for parallel processing. Lambda functions process the data in near real-time, applying transformations, validations, or enrichment. Processed data is stored in DynamoDB for highly available, low-latency access.

EC2 with cron jobs cannot process data in real-time and requires manual management. S3 only supports batch processing. RDS Multi-AZ can store data but is less efficient for high-velocity streaming workloads and may require complex sharding.

Kinesis ensures durability, retention, and scalability. Lambda scales automatically with incoming data and supports error handling, retries, and dead-letter queues. DynamoDB provides automatic scaling, encryption at rest, and single-digit millisecond latency. CloudWatch monitors all stages for performance, throughput, and failures.

This architecture supports fault tolerance, scalability, and operational simplicity, making it ideal for IoT analytics, monitoring, and alerting. Automation ensures minimal operational effort while maintaining high performance, availability, and security. Integration with Step Functions or SNS allows further workflow orchestration and notifications.

Question 87:

A company wants to deploy a web application that is highly available, fault-tolerant, and automatically scales with traffic. Which AWS services and architecture should be used?

Answer:

A) EC2 Auto Scaling group, Application Load Balancer (ALB), and RDS Multi-AZ
B) Single EC2 instance with EBS
C) S3 static hosting only
D) Lambda only

Explanation:

Option A is correct. Deploying a web application using an EC2 Auto Scaling group ensures that the application layer scales automatically based on incoming traffic, maintaining high availability during traffic spikes. The Application Load Balancer distributes traffic across multiple healthy instances, increasing fault tolerance and improving overall application reliability. Using RDS Multi-AZ ensures that the relational database layer is highly available, automatically replicating data to a standby instance in another Availability Zone. If the primary instance fails, failover occurs automatically, minimizing downtime.

A single EC2 instance creates a single point of failure and cannot handle increased traffic efficiently. S3 static hosting is suitable only for static websites and cannot run dynamic web applications that require application logic. Lambda is serverless but is not suitable for multi-tier applications that require persistent relational storage without complex orchestration.

In this architecture, EC2 Auto Scaling ensures elasticity, scaling instances up or down based on performance metrics such as CPU utilization, network traffic, or request count. ALB supports health checks to ensure traffic is only routed to healthy instances, preventing degraded performance. Multi-AZ RDS ensures that the database layer remains available in the event of hardware failure, network disruption, or zone outage.

Security best practices involve deploying EC2 instances in private subnets, using security groups to control inbound and outbound traffic, encrypting RDS data at rest using KMS, and enabling IAM roles for secure access to AWS resources. CloudWatch metrics monitor application performance, ALB health, and database performance, while CloudTrail audits all API activity.

This architecture also supports disaster recovery and operational excellence. Backups can be automated using RDS snapshots, and Auto Scaling ensures sufficient capacity for recovery after an incident. Integration with CloudFront can reduce latency for global users by caching static assets at edge locations.

Overall, combining EC2 Auto Scaling, ALB, and RDS Multi-AZ delivers a resilient, high-performance, and scalable architecture suitable for modern web applications. This setup adheres to AWS Well-Architected Framework principles, providing reliability, performance efficiency, security, and cost optimization.

Question 88:

A company wants to provide secure temporary access to S3 objects for external vendors without sharing AWS credentials. Which AWS feature is most appropriate?

Answer:

A) Pre-signed URLs
B) Public S3 bucket
C) IAM user credentials shared with vendors
D) S3 Standard only

Explanation:

Option A is correct. Pre-signed URLs allow temporary access to specific S3 objects without exposing AWS credentials. The URL contains an embedded signature and expiration time, ensuring that access is time-limited. Vendors can use the pre-signed URL to download or upload objects as authorized, without needing IAM credentials.

Public S3 buckets are insecure and expose data to anyone with the URL. Sharing IAM user credentials is a significant security risk, violating the principle of least privilege. S3 Standard is a storage class and does not provide access control functionality.

Pre-signed URLs integrate seamlessly into web applications, scripts, or automated workflows. Lambda functions or API Gateway endpoints can generate pre-signed URLs dynamically in response to application events or vendor requests. Access and usage are fully auditable through AWS CloudTrail, providing visibility into who accessed which objects and when.

Encryption at rest (SSE-S3 or SSE-KMS) ensures that objects are protected, while encryption in transit (HTTPS) ensures confidentiality during transfer. Expiration times enforce security policies by limiting the window of access, and fine-grained IAM policies control which users or services can generate pre-signed URLs.

This approach is particularly useful for scenarios like document exchange, media content delivery, or collaborative projects with third-party vendors. It reduces operational complexity, enhances security, and ensures compliance with regulatory requirements such as HIPAA, PCI DSS, or GDPR.

By using pre-signed URLs, organizations can achieve secure, temporary, and auditable access to S3 objects, while maintaining the principle of least privilege and minimizing operational overhead. This aligns with AWS Well-Architected Framework principles for security, operational excellence, and reliability.

Option A is the most appropriate solution for providing secure temporary access to S3 objects for external vendors without sharing AWS credentials. Pre-signed URLs allow organizations to grant time-limited access to specific S3 objects without requiring the recipients to have AWS credentials. The URL includes an embedded signature and an expiration timestamp, ensuring that access is automatically revoked once the time limit is reached. Vendors can use the pre-signed URL to perform permitted actions, such as downloading or uploading files, without needing direct access to the S3 bucket or IAM credentials. This method maintains strong security controls while supporting seamless collaboration.

Using a public S3 bucket, as suggested in option B, exposes data to anyone who has the link or can discover the bucket, which poses a significant security risk. Similarly, sharing IAM user credentials with vendors, as in option C, violates the principle of least privilege and introduces risks such as accidental deletion, unauthorized access, or misuse of permissions. Option D, S3 Standard, refers only to the storage class and does not provide access control or security mechanisms, making it irrelevant to controlling temporary access.

Pre-signed URLs integrate well with web applications, serverless functions, and automated workflows. For example, Lambda functions or API Gateway endpoints can dynamically generate pre-signed URLs in response to vendor requests, ensuring that access is granted only when necessary and according to business rules. Access can be monitored and audited using AWS CloudTrail, allowing organizations to track which users accessed which objects and when, providing a clear security trail for compliance purposes.

Additional security measures enhance the protection of objects accessed via pre-signed URLs. Server-side encryption using SSE-S3 or SSE-KMS ensures data is encrypted at rest, while HTTPS guarantees that data in transit is secure. Expiration times enforce strict security policies, and fine-grained IAM policies determine which users or services are authorized to generate pre-signed URLs. This approach is particularly useful for scenarios such as secure document exchange, media content sharing, collaborative projects with third parties, and temporary file transfers, allowing organizations to maintain operational efficiency, minimize security risks, and meet regulatory compliance requirements. Pre-signed URLs provide a secure, auditable, and temporary access mechanism while adhering to AWS best practices for security, operational excellence, and reliability.

Question 89:

A company wants to process IoT sensor data in real-time and store results in a scalable database for analytics. Which AWS services should be used?

Answer:

A) Amazon Kinesis Data Streams, Lambda, and DynamoDB
B) EC2 with cron jobs
C) S3 only
D) RDS Multi-AZ

Explanation:

Option A is correct. Amazon Kinesis Data Streams ingests streaming IoT data in real-time and partitions it across multiple shards for parallel processing. Lambda functions process incoming data immediately, applying transformations, filtering, and enrichment. DynamoDB stores the processed results with low-latency, high availability, and automatic scaling.

EC2 with cron jobs is unsuitable for real-time processing and requires significant operational effort to manage scaling, fault tolerance, and retries. S3 is batch-oriented and cannot provide low-latency processing. RDS Multi-AZ is a relational database, not optimized for streaming workloads, and may require complex sharding for large-scale ingestion.

Kinesis provides durability by retaining data for a configurable period, allowing replay and reprocessing in case of errors. Lambda functions scale automatically to handle varying data volumes, and dead-letter queues capture failed events for later inspection. DynamoDB offers single-digit millisecond response times, seamless scaling, and encryption at rest via KMS.

CloudWatch monitors throughput, latency, and error rates, while CloudTrail ensures auditing of all actions. Security is enforced via IAM roles granting Lambda access only to the necessary resources. Integration with Step Functions allows complex workflows and orchestration of downstream processes.

This architecture supports IoT analytics, anomaly detection, real-time dashboards, and automated alerting. It is cost-efficient due to pay-per-use Lambda execution and eliminates the need for server management. By combining Kinesis, Lambda, and DynamoDB, organizations achieve a highly scalable, reliable, and low-latency solution for processing IoT data streams, aligning with AWS Well-Architected Framework principles for performance, operational excellence, reliability, and security.

Question 90:

A company wants to provide a global low-latency content delivery solution for static and dynamic web content while protecting against DDoS attacks. Which architecture is best?

Answer:

A) CloudFront with S3/EC2 origin, WAF, and HTTPS
B) S3 only
C) EC2 in a single region
D) Direct Connect

Explanation:

Option A is correct. CloudFront distributes content globally through edge locations, reducing latency for end users and improving performance for both static and dynamic content. The integration with WAF protects against common web application attacks and DDoS events. HTTPS ensures encrypted data transfer.

S3 alone cannot accelerate dynamic content and has higher latency for global users. EC2 in a single region increases latency for distant users and is not fault-tolerant. Direct Connect provides private connectivity but does not accelerate content delivery or provide DDoS protection.

CloudFront caching reduces origin load, supports cache invalidation, and can integrate with Lambda@Edge to modify requests/responses at edge locations for personalization. CloudWatch metrics track request counts, cache hit ratios, latency, and error rates. AWS Shield Advanced provides additional protection against sophisticated attacks.

This architecture supports high availability, fault tolerance, and operational simplicity. Edge caching ensures cost optimization and improved user experience, while managed services reduce operational overhead. This solution aligns with AWS Well-Architected Framework principles for performance, reliability, security, and operational excellence.

Option A is the most suitable architecture for providing a global, low-latency content delivery solution for both static and dynamic web content while protecting against DDoS attacks. Amazon CloudFront, when paired with S3 or EC2 as the origin, distributes content to edge locations around the world. This ensures that users access content from the nearest edge location, significantly reducing latency and improving overall performance. By caching frequently requested content, CloudFront also reduces load on the origin servers, which enhances scalability and availability. Dynamic content can also be accelerated, ensuring that personalized responses, API calls, and interactive features perform well for a global audience.

Integration with AWS Web Application Firewall provides protection against common web application attacks, such as SQL injection and cross-site scripting, as well as volumetric and application-layer DDoS attacks. For additional protection against more sophisticated threats, AWS Shield Advanced can be deployed alongside CloudFront. Secure data transmission is ensured through HTTPS, encrypting traffic between users and edge locations, and optionally between edge locations and origin servers. CloudFront also allows cache invalidation to refresh content as needed and supports Lambda@Edge for advanced edge processing, such as request/response manipulation, authentication, or personalization, closer to the user.

Using S3 alone, as in option B, cannot accelerate dynamic content and may result in higher latency for users who are geographically distant from the bucket’s region. Similarly, deploying EC2 in a single region, as in option C, increases latency for distant users and introduces a single point of failure, reducing fault tolerance. Direct Connect, suggested in option D, provides a private network connection but does not offer global caching, performance acceleration, or DDoS protection, making it unsuitable for delivering content globally.

CloudWatch metrics provide detailed monitoring of request volumes, cache hit ratios, latency, and error rates, which supports performance optimization and troubleshooting. This architecture delivers high availability, fault tolerance, security, and operational simplicity. It is ideal for serving websites, APIs, video streaming, or interactive applications globally, while minimizing latency, ensuring secure access, and maintaining cost efficiency by reducing repeated origin requests. By combining CloudFront, S3 or EC2 origins, WAF, and HTTPS, organizations achieve a scalable, reliable, and secure content delivery solution that aligns with AWS best practices for performance, security, and operational excellence.

Question 91:

A company wants to enforce tagging compliance across multiple AWS accounts automatically. Which combination of services is recommended?

Answer:

A) AWS Config with AWS Organizations
B) CloudTrail only
C) EC2 instances only
D) S3 only

Explanation:

Option A is correct. AWS Config evaluates resources against tagging rules and ensures compliance with organizational standards. Using AWS Organizations, these rules can be enforced centrally across multiple accounts, ensuring consistency and reducing operational overhead.

CloudTrail logs activity but cannot enforce tagging compliance. EC2 and S3 alone do not provide centralized governance or compliance automation.

Config rules can trigger automated remediation through Lambda, correcting non-compliant resources. Aggregators consolidate compliance data from multiple accounts and regions. CloudWatch alarms provide visibility for policy violations.

This approach enforces governance, supports auditing and cost allocation, reduces manual effort, and ensures operational excellence. Organizations maintain consistent metadata for resources, enabling efficient reporting, automation, and billing analysis. Automated compliance aligns with AWS Well-Architected principles, ensuring security, reliability, and operational efficiency.

Question 92:

A company wants to build a highly available, multi-region web application using a relational database while minimizing downtime during regional failures. Which architecture is most suitable?

Answer:

A) RDS Multi-AZ with Read Replicas in another region and Route 53 latency-based routing
B) Single RDS instance in one region
C) DynamoDB only
D) S3 static hosting

Explanation:

Option A is correct. Using RDS Multi-AZ ensures that each database has a synchronous standby in the same region, automatically failing over in case of AZ failure. To provide multi-region high availability, Read Replicas are created in a different region, allowing read traffic to be served from the nearest region while promoting a replica to primary in case of regional failure.

A single RDS instance does not provide high availability or fault tolerance. DynamoDB is NoSQL, and while it offers multi-region replication, it does not support relational SQL queries. S3 only stores static data, unsuitable for dynamic database-driven applications.

Route 53 latency-based routing ensures user traffic is directed to the nearest region with low latency. Read replicas can handle read-heavy workloads, improving performance, while Multi-AZ ensures high availability for writes in the primary region. Failover mechanisms minimize downtime during AZ or regional failures.

Security best practices include encrypting data with KMS, restricting access using IAM roles and security groups, and enabling CloudTrail for auditing. CloudWatch monitors metrics such as replica lag, CPU utilization, and storage usage. Automated backups and snapshots support point-in-time recovery.

This architecture ensures scalability, reliability, and fault tolerance. Organizations can maintain business continuity during outages and improve application responsiveness globally, aligning with AWS Well-Architected Framework principles for reliability, operational excellence, security, and performance efficiency.

Question 93:

A company wants to process high-volume streaming data from multiple sources in near real-time and store the results in a scalable database for analytics. Which AWS service combination is most appropriate?

Answer:

A) Amazon Kinesis Data Streams, Lambda, and DynamoDB
B) S3 only
C) EC2 with batch processing
D) RDS Multi-AZ

Explanation:

Option A is correct. Kinesis Data Streams ingest high-volume streaming data and allow parallel processing by sharding streams. Lambda functions process the data immediately, applying transformations, validations, and enrichment. DynamoDB stores the results with low-latency, high availability, and automatic scaling.

S3 alone is batch-oriented and unsuitable for real-time processing. EC2 with batch processing cannot achieve near real-time analytics and requires manual scaling and monitoring. RDS Multi-AZ is relational, but high-velocity streaming workloads may require complex sharding and do not scale automatically without added overhead.

Kinesis ensures durability, configurable retention, and reprocessing capabilities in case of errors. Lambda automatically scales with incoming data, and dead-letter queues capture failed events for inspection. DynamoDB provides single-digit millisecond latency, automatic scaling, and encryption at rest via KMS.

CloudWatch monitors throughput, error rates, and processing latency. CloudTrail audits all API activity, and IAM roles enforce least-privilege access. Step Functions can orchestrate complex workflows, retries, and exception handling.

This architecture supports IoT analytics, fraud detection, monitoring, dashboards, and automated alerting. By using managed services, organizations minimize operational overhead while achieving real-time processing, fault tolerance, and scalability, aligning with AWS Well-Architected Framework principles for operational excellence, performance efficiency, security, and reliability.

Question 94:

A company wants to automate backup and recovery of EBS volumes across multiple regions while minimizing operational effort. Which solution is recommended?

Answer:

A) Amazon Data Lifecycle Manager (DLM) with cross-region snapshot copy
B) Manual snapshots on each volume
C) EC2 instance backup scripts
D) S3 Standard only

Explanation:

Option A is correct. Data Lifecycle Manager (DLM) automates the creation, retention, and deletion of EBS snapshots. Cross-region snapshot copy ensures backups are available in multiple regions, improving disaster recovery and compliance.

Manual snapshots require administrative effort, are error-prone, and do not provide automation for retention policies. EC2 scripts require maintenance and monitoring. S3 alone is object storage and cannot snapshot EBS volumes.

DLM supports policy-based backup automation, including scheduling, retention, and cross-region replication. Snapshots are incremental, reducing storage costs, and all snapshots are encrypted using KMS for security. CloudWatch monitors snapshot creation and failures, while CloudTrail logs activity for auditing purposes.

This architecture ensures high availability, fault tolerance, and operational simplicity. Organizations can restore EBS volumes quickly in another region in case of disaster. It aligns with AWS Well-Architected Framework principles for reliability, operational excellence, and security while reducing administrative overhead and minimizing downtime.

Question 95:

A company wants to provide secure, temporary access to objects in S3 for partners while tracking access and ensuring compliance. Which solution is best?

Answer:

A) Pre-signed URLs with CloudTrail logging
B) Public S3 bucket
C) IAM user credentials shared
D) S3 Standard only

Explanation:

Option A is correct. Pre-signed URLs provide temporary, secure access to specific S3 objects without sharing AWS credentials. CloudTrail tracks usage, providing auditing and compliance visibility.

Public buckets are insecure and allow unrestricted access. Sharing IAM credentials violates least-privilege principles. S3 Standard is only a storage class and does not provide access control or auditing.

Pre-signed URLs support expiration times and can be generated dynamically via Lambda or API Gateway. Encryption at rest (SSE-KMS) and in transit (HTTPS) ensures data confidentiality. CloudTrail logs provide full visibility into object access events for audit and compliance purposes.

This solution is cost-efficient, scalable, and reduces operational complexity. It is suitable for scenarios such as vendor document sharing, media delivery, and collaborative projects. By combining pre-signed URLs with CloudTrail, organizations enforce security, ensure compliance, and maintain operational efficiency in accordance with AWS Well-Architected Framework principles.

Question 96:

A company wants to deploy a web application using serverless architecture that automatically scales and only charges for execution time. Which services should be used?

Answer:

A) AWS Lambda, API Gateway, and DynamoDB
B) EC2 instances
C) Elastic Beanstalk with RDS
D) S3 only

Explanation:

Option A is correct. AWS Lambda provides compute in a serverless model, automatically scaling based on requests. API Gateway handles incoming HTTP requests and routes them to Lambda functions, while DynamoDB provides low-latency, scalable storage.

EC2 requires server management, scaling, and capacity planning. Elastic Beanstalk is partially managed but still requires infrastructure management. S3 only provides static storage and cannot execute dynamic application logic.

Lambda scales seamlessly with incoming traffic, eliminating the need to manage servers. DynamoDB supports automatic scaling, single-digit millisecond latency, and high availability. IAM roles enforce secure access between Lambda, API Gateway, and DynamoDB. CloudWatch monitors execution metrics, errors, and performance.

This architecture is cost-efficient because you pay only for actual compute time and storage used. It supports fault tolerance, operational simplicity, and rapid deployment. Automation reduces human error, and serverless principles align with AWS Well-Architected Framework goals of operational excellence, cost optimization, and performance efficiency.

Question 97:

A company wants to implement a multi-region, highly available DynamoDB table to serve global users with low latency. Which feature should be used?

Answer:

A) DynamoDB Global Tables
B) Single DynamoDB table in one region
C) RDS Multi-AZ
D) S3 Standard

Explanation:

Option A is correct. DynamoDB Global Tables replicate data across multiple AWS regions automatically. It allows applications to read and write data from the nearest region, minimizing latency and improving fault tolerance.

A single DynamoDB table cannot provide multi-region availability. RDS is relational and requires manual cross-region replication. S3 is object storage and does not provide database functionality.

Global Tables handle replication, conflict resolution, and automatic scaling. CloudWatch monitors read/write capacity, latency, and errors. IAM policies enforce secure access, and KMS ensures data encryption. Applications can scale globally without managing cross-region replication manually.

This solution is suitable for e-commerce, gaming, IoT, and global analytics platforms. By leveraging Global Tables, organizations achieve low-latency, highly available, and resilient multi-region data access, aligning with AWS Well-Architected principles for reliability, performance efficiency, and operational excellence.

Question 98:

A company wants to analyze large amounts of historical data stored in S3 without loading it into a data warehouse. Which service is most appropriate?

Answer:

A) Amazon Athena
B) RDS
C) EC2 with custom scripts
D) DynamoDB

Explanation:

Option A is correct. Athena enables SQL queries directly against S3 objects using standard SQL without provisioning servers or loading data into a data warehouse. It is serverless, scales automatically, and charges based on the amount of data scanned.

RDS requires data loading and management. EC2 with scripts requires manual maintenance and does not scale automatically. DynamoDB is NoSQL and cannot query large unstructured datasets efficiently.

Athena integrates with Glue Data Catalog for schema management and supports partitioning to improve query performance. Queries can be scheduled or triggered automatically, and CloudWatch monitors usage and performance. Security is enforced via IAM, encryption at rest (SSE-KMS), and fine-grained access control.

This architecture reduces operational overhead, provides cost-effective analytics, and allows organizations to gain insights from historical data quickly. It aligns with AWS Well-Architected Framework principles of cost optimization, performance efficiency, operational excellence, and security.

Question 99:

A company wants to provide secure access to an S3 bucket from multiple AWS accounts while enforcing logging and compliance. Which approach is recommended?

Answer:

A) S3 bucket policies, AWS CloudTrail, and AWS Config
B) Public S3 bucket
C) IAM users in each account
D) EC2 instances only

Explanation:

Option A is correct. S3 bucket policies allow cross-account access with fine-grained control. CloudTrail logs all API calls, providing visibility into object access. AWS Config monitors bucket configuration for compliance with encryption, access restrictions, and organizational policies.

Public buckets are insecure. IAM users per account create administrative overhead. EC2 instances do not enforce access or logging.

Bucket policies combined with CloudTrail provide secure, auditable access. Config rules can detect misconfigurations and trigger automated remediation. SSE-KMS ensures encryption at rest, while HTTPS ensures secure data transfer.

This approach ensures compliance, reduces operational complexity, and enforces security across multiple accounts. Organizations gain operational visibility, maintain regulatory compliance, and improve governance, aligning with AWS Well-Architected principles for security, reliability, and operational excellence.

Question 100:

A company wants to implement a real-time dashboard that visualizes IoT sensor data globally, ensuring low-latency updates and scalability. Which AWS architecture is suitable?

Answer:

A) Kinesis Data Streams, Lambda, DynamoDB, and Amazon QuickSight
B) EC2 with batch scripts
C) S3 only
D) RDS Multi-AZ

Explanation:

Option A is correct. Kinesis ingests real-time IoT data streams. Lambda processes the data immediately, performing transformations or aggregations. DynamoDB stores results for low-latency access. Amazon QuickSight visualizes the processed data in real-time dashboards.

EC2 with batch scripts is not real-time. S3 cannot provide low-latency analytics. RDS Multi-AZ provides relational storage but may not scale efficiently for high-velocity streams.

Kinesis ensures durability, partitioning, and reprocessing. Lambda scales automatically and handles errors with dead-letter queues. DynamoDB provides highly available, single-digit millisecond latency storage. QuickSight integrates directly for real-time analytics and dashboards.

CloudWatch monitors throughput, latency, and errors. CloudTrail tracks all API actions. IAM roles and KMS encryption enforce security and access control. This architecture provides scalable, fault-tolerant, and low-latency dashboards suitable for global IoT applications.