Amazon AWS Certified Solutions Architect – Professional SAP-C02 Exam Dumps and Practice Test Questions Set 3 Q41-60

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Question 41:

A company is designing a serverless application that requires orchestration of multiple AWS Lambda functions with conditional branching, retries, and error handling. Which service is most appropriate?

Answer:

A) AWS Step Functions
B) Amazon SWF
C) AWS Batch
D) Amazon SQS

Explanation:

The correct answer is A) AWS Step Functions.

AWS Step Functions provides serverless orchestration with state machines, allowing developers to define workflows with sequential, parallel, and conditional execution. It supports retries, error handling, and timeouts, providing visibility into execution state and integrating seamlessly with Lambda, ECS, and other AWS services.

Option B, SWF, is an older workflow service requiring manual worker management. Option C, Batch, is for batch processing, not orchestration. Option D, SQS, provides message queuing but cannot orchestrate complex workflows with error handling and branching.

Step Functions supports both standard and express workflows. Standard workflows are durable and track execution history, suitable for long-running tasks. Express workflows support high throughput for short-duration tasks. Integration with CloudWatch, X-Ray, and IAM provides observability, tracing, and secure execution.

This architecture simplifies serverless workflow management, reduces operational overhead, and ensures reliable execution of complex tasks with minimal code.

Question 42:

A company needs a database that supports global read scalability with minimal latency for users worldwide. Which AWS solution is most appropriate?

Answer:

A) Amazon Aurora Global Database
B) Amazon RDS Multi-AZ
C) Amazon DynamoDB with global tables
D) Amazon Redshift

Explanation:

The correct answer is A) Amazon Aurora Global Database.

Aurora Global Database replicates data across multiple regions asynchronously with replication lag under one second. Secondary regions support read queries locally, reducing latency for users worldwide. This architecture provides both high availability and disaster recovery.

Option B, Multi-AZ RDS, is limited to a single region and does not provide global read scaling. Option C, DynamoDB global tables, is NoSQL and does not support relational workloads requiring ACID compliance. Option D, Redshift, is for analytics and not transactional workloads.

Aurora integrates with CloudWatch for monitoring, KMS for encryption, and supports automated backups and point-in-time recovery. Read scaling in multiple regions reduces latency, improves user experience, and supports mission-critical applications with minimal operational overhead.

Question 43:

A company wants to ensure exactly-once processing of messages in an event-driven architecture. Which AWS service combination provides durability, ordering, and exactly-once processing?

Answer:

A) Amazon Kinesis Data Streams with Lambda
B) Amazon SQS standard queues with Lambda
C) Amazon SNS with S3 triggers
D) DynamoDB Streams

Explanation:

The correct answer is A) Amazon Kinesis Data Streams with Lambda.

Kinesis guarantees ordered delivery at the shard level and supports exactly-once processing when Lambda checkpoints are used. Messages are durably stored across multiple Availability Zones.

Option B, SQS standard queues, provides at-least-once delivery and may result in duplicates. FIFO queues help with ordering but have throughput limits. Option C, SNS with S3 triggers, does not guarantee ordering or exactly-once processing. Option D, DynamoDB Streams, only captures changes to DynamoDB tables and cannot process arbitrary messages.

This architecture ensures durability, high throughput, and ordered processing for event-driven applications. It supports reprocessing, analytics, and integration with other AWS services while minimizing operational complexity.

Question 44:

A company wants a scalable caching solution to reduce read latency for DynamoDB queries. Which service is most suitable?

Answer:

A) Amazon DynamoDB Accelerator (DAX)
B) Amazon ElastiCache Redis
C) Amazon S3
D) RDS Read Replicas

Explanation:

The correct answer is A) Amazon DynamoDB Accelerator (DAX).

DAX is a fully managed, in-memory cache for DynamoDB that reduces read latency from milliseconds to microseconds. It supports write-through caching and seamless integration with DynamoDB, minimizing operational overhead.

Option B, ElastiCache Redis, requires additional application logic for integration. Option C, S3, is not suitable for caching database queries. Option D, RDS Read Replicas, cannot cache DynamoDB queries and is not a caching solution.

DAX improves performance, supports high throughput, and reduces DynamoDB read costs. Security is managed with IAM, encryption, and VPC endpoints. It also supports scaling and fault tolerance across multiple nodes.

Question 45:

A company wants to implement global low-latency access for a web application with automatic failover. Which architecture meets this requirement?

Answer:

A) Multi-region Route 53 latency-based routing, CloudFront, and ALBs
B) Single-region ALB with CloudFront
C) S3 static hosting with Transfer Acceleration
D) Global Accelerator with single-region EC2

Explanation:

The correct answer is A) Multi-region Route 53 latency-based routing, CloudFront, and ALBs.

Route 53 directs users to the region with lowest latency. CloudFront caches content globally, reducing response times. Multi-region ALBs provide traffic distribution and automatic failover across regions.

Option B, single-region ALB, cannot failover. Option C, S3 Transfer Acceleration, only speeds up object transfer. Option D, Global Accelerator, improves network performance but does not manage application failover.

This architecture ensures global availability, low latency, and resiliency while supporting scaling, security, and observability through CloudWatch, WAF, and CloudTrail.

Question 46:

A company runs a web application in multiple AWS regions and wants to ensure near real-time synchronization of session state across regions. Which solution should the solutions architect implement?

Answer:

A) Amazon DynamoDB global tables
B) Amazon RDS Multi-AZ
C) Amazon ElastiCache with cross-region replication
D) S3 replication

Explanation:

The correct answer is A) Amazon DynamoDB global tables.

DynamoDB global tables provide a fully managed, multi-region, multi-master database solution. Each region contains a full replica of the table, allowing applications to perform read and write operations locally while automatically synchronizing data across all regions. This ensures near real-time consistency of session state globally, reducing latency for users and improving application responsiveness.

Option B, Amazon RDS Multi-AZ, ensures high availability within a single region but does not replicate across regions. Attempting cross-region replication manually adds operational complexity and latency. Option C, ElastiCache, can store session state but does not provide fully managed cross-region replication natively. Managing replication between Redis clusters manually introduces operational risk and latency issues. Option D, S3 replication, is suitable for objects rather than ephemeral session state, and the replication is eventually consistent rather than near real-time.

DynamoDB global tables automatically handle conflict resolution, ensuring data consistency when multiple users update the same session simultaneously. The service provides seamless scaling to handle millions of concurrent users, and integration with IAM and KMS ensures secure access and encryption at rest. Using DynamoDB Streams, applications can also trigger serverless workflows with AWS Lambda for additional processing of session updates.

The architecture enables highly responsive global applications by ensuring session data is available locally to users in every region. It also reduces dependency on a single region, improving fault tolerance and resilience. DynamoDB’s serverless nature reduces operational overhead while maintaining high performance, making it the ideal solution for distributed session state management.

Question 47:

A company needs to process large amounts of streaming data from IoT devices in real-time, performing analytics and alerting on anomalous behavior. Which AWS services combination provides durability, low latency, and scalability?

Answer:

A) Amazon Kinesis Data Streams with Lambda consumers
B) Amazon SQS with Lambda
C) Amazon SNS with S3 triggers
D) Amazon RDS with scheduled queries

Explanation:

The correct answer is A) Amazon Kinesis Data Streams with Lambda consumers.

Kinesis Data Streams allows real-time ingestion of high-volume IoT data. Data is divided into shards, providing parallelism for processing millions of events per second. Each shard ensures ordering of records and durability by replicating data across multiple Availability Zones. Lambda consumers can process each shard in parallel, applying analytics, anomaly detection, and triggering alerts.

Option B, SQS with Lambda, is suitable for decoupling components but does not provide shard-level ordering, and standard queues may result in duplicate message processing. FIFO queues enforce order but have throughput limits, making them unsuitable for millions of IoT devices. Option C, SNS with S3 triggers, is primarily a notification system; it lacks durability and ordering guarantees. Option D, RDS with scheduled queries, introduces significant latency and cannot handle real-time streaming data efficiently.

Kinesis integrates with CloudWatch for detailed monitoring of stream health, shard iterator age, and Lambda processing performance. Data retention can be extended up to seven days for replayability. Security is enforced with IAM policies, KMS encryption for data at rest, and TLS for in-transit data. The architecture allows real-time analytics, alerting, and downstream storage in S3, Redshift, or DynamoDB for further processing or historical analysis.

This approach ensures high throughput, durability, low latency, and scalability for processing IoT streams, providing operational simplicity and minimizing the risk of data loss. It also supports automatic scaling as the number of IoT devices increases, enabling enterprises to handle millions of simultaneous events efficiently.

Question 48:

A company wants to implement a disaster recovery strategy for a critical relational database with minimal downtime. The RPO must be under 1 minute, and the RTO under 10 minutes. Which AWS solution is best?

Answer:

A) Amazon Aurora Global Database
B) RDS snapshots with cross-region copy
C) Manual database replication using EC2 instances
D) Standby EC2 database servers in another region

Explanation:

The correct answer is A) Amazon Aurora Global Database.

Aurora Global Database replicates data asynchronously to secondary regions with replication lag typically under one second. This provides near-zero RPO and rapid failover to meet RTO requirements. Secondary regions can serve read requests, improving performance and availability globally.

Option B, cross-region RDS snapshots, introduces delays because snapshots are point-in-time backups. Recovery from snapshots exceeds the RTO of 10 minutes. Option C, manual replication, is error-prone, operationally complex, and cannot guarantee transactional consistency. Option D, standby EC2 servers, do not provide continuous replication, making failover unreliable and slow.

Aurora Global Database automatically replicates six copies of data across three Availability Zones per region. Failover between regions is automated and monitored via CloudWatch. Security and compliance are ensured through IAM, encryption with KMS, and auditing with CloudTrail. This architecture also allows scaling reads in secondary regions while maintaining high availability.

Question 49:

A company is deploying a high-traffic web application and wants to reduce database load while providing sub-millisecond read latency. Which caching solution is most appropriate?

Answer:

A) Amazon DynamoDB Accelerator (DAX)
B) Amazon ElastiCache Redis
C) Amazon S3
D) RDS Read Replicas

Explanation:

The correct answer is A) Amazon DynamoDB Accelerator (DAX).

DAX is a fully managed, in-memory caching layer for DynamoDB. It reduces read latency from milliseconds to microseconds without requiring application changes. DAX supports write-through caching, maintaining consistency between the cache and the database.

Option B, ElastiCache Redis, provides general-purpose caching but requires developers to implement cache logic, increasing operational complexity. Option C, S3, is not a caching solution and cannot provide sub-millisecond access to database queries. Option D, RDS Read Replicas, improve read throughput for RDS but cannot achieve the low latency DAX provides for DynamoDB.

DAX integrates seamlessly with DynamoDB, scales horizontally, and provides fault tolerance. Security features include IAM authorization, encryption at rest using KMS, and encryption in transit using TLS. This architecture reduces database load, improves performance for high-traffic applications, and simplifies operational management by offloading caching responsibilities to a fully managed service.

Question 50:

A company is building a serverless workflow that requires orchestration of multiple Lambda functions, error handling, retries, and conditional branching. Which AWS service is most suitable?

Answer:

A) AWS Step Functions
B) Amazon SWF
C) AWS Batch
D) Amazon SQS

Explanation:

The correct answer is A) AWS Step Functions.

AWS Step Functions allows developers to orchestrate serverless workflows with state machines. It supports sequential, parallel, and conditional execution of Lambda functions. It also provides built-in error handling, retry logic, and integration with other AWS services like ECS, Fargate, and SNS. Step Functions supports both standard and express workflows for durable long-running tasks or high-throughput, short-duration tasks.

Option B, SWF, is legacy and requires managing worker nodes. Option C, Batch, is intended for batch processing workloads, not orchestration. Option D, SQS, is for message queuing but cannot manage complex workflows.

Step Functions provide operational visibility with execution history, CloudWatch monitoring, and X-Ray tracing. IAM and KMS integration ensures secure workflow execution. This architecture simplifies development, reduces operational overhead, and ensures reliability for serverless workflows with complex branching and error handling.

Question 51:

A company needs to implement an automated, globally distributed backup solution for RDS databases with minimal operational effort. Which solution is recommended?

Answer:

A) Cross-region automated RDS snapshots
B) Manual database exports to S3
C) EC2 backup scripts
D) DynamoDB global tables

Explanation:

The correct answer is A) Cross-region automated RDS snapshots.

RDS supports automated snapshots that can be copied to secondary regions automatically. This provides disaster recovery, improves data durability, and minimizes operational effort. Snapshots are incremental and stored in S3, providing low-cost, reliable backup storage.

Option B, manual exports, are error-prone and require operational management. Option C, EC2 backup scripts, add complexity and do not guarantee transactional consistency. Option D, DynamoDB global tables, are not relational backups.

Cross-region snapshots integrate with CloudWatch for monitoring, KMS for encryption, and IAM for access control. This ensures backups are secure, durable, and recoverable across regions with minimal operational overhead.

When a company needs an automated, globally distributed backup solution for Amazon RDS databases, it is essential to choose a method that ensures data durability, supports disaster recovery, and requires minimal operational effort. Amazon RDS provides built-in capabilities to meet these requirements through cross-region automated snapshots.

Cross-region automated RDS snapshots allow the database to create backups that are automatically replicated to a secondary AWS region. These snapshots are incremental, which means that only the changes since the last snapshot are stored, reducing storage costs and improving efficiency. By replicating snapshots across regions, organizations can achieve disaster recovery readiness, ensuring that data remains available even if the primary region experiences an outage. These snapshots are stored in Amazon S3, which offers durability, security, and scalability, while also integrating with AWS Key Management Service (KMS) for encryption at rest and in transit. Access and permissions can be managed through AWS Identity and Access Management (IAM), ensuring that backups are secure and compliant with corporate policies.

Alternative solutions have limitations in this scenario. Manual database exports to Amazon S3, while possible, are error-prone and require ongoing operational management. Each export must be scheduled, monitored, and validated to ensure consistency, which increases administrative overhead. EC2 backup scripts also introduce complexity and are not ideal for relational databases. Scripts need to handle transactional consistency manually, and they require additional maintenance to scale across multiple instances or databases. DynamoDB global tables provide a mechanism for replicating NoSQL data across regions but are not suitable for relational database backups, as they do not maintain the structure or transactional integrity of RDS databases.

By leveraging cross-region automated RDS snapshots, companies can implement a fully managed backup solution that minimizes operational effort while ensuring security, durability, and recoverability. The integration with AWS services such as CloudWatch enables monitoring of snapshot status, providing visibility and alerting for any backup failures. This approach ensures that enterprise applications remain resilient, compliant, and highly available across geographic regions.

The correct answer is A) Cross-region automated RDS snapshots.

Question 52:

A company wants a highly available messaging system that can scale to millions of messages per second with exactly-once processing. Which AWS service should be used?

Answer:

A) Amazon Kinesis Data Streams
B) Amazon SQS standard queues
C) Amazon SNS
D) Amazon RDS

Explanation:

The correct answer is A) Amazon Kinesis Data Streams.

Kinesis Data Streams allows ordered, durable message streaming with shard-level scaling. Lambda consumers can provide exactly-once processing using checkpointing. The service is highly scalable and supports millions of records per second while maintaining durability across AZs.

Option B, SQS standard queues, provides at-least-once delivery and may duplicate messages. FIFO queues are limited in throughput. Option C, SNS, is pub/sub only and does not guarantee ordering or exactly-once processing. Option D, RDS, is not designed for real-time messaging.

Kinesis integrates with CloudWatch for monitoring, provides secure IAM access, supports KMS encryption, and allows replay of events. This architecture ensures real-time processing, durability, scalability, and operational simplicity.

Question 53:

A company is designing a multi-region web application that must remain available even if an entire AWS region fails. The architecture must also ensure low-latency access for global users. Which solution meets these requirements?

Answer:

A) Multi-region deployment with Route 53 latency-based routing, CloudFront, and multi-region ALBs
B) Single-region ALB with CloudFront
C) S3 static website hosting with Transfer Acceleration
D) Global Accelerator with single-region EC2

Explanation:

The correct answer is A) Multi-region deployment with Route 53 latency-based routing, CloudFront, and multi-region ALBs.

This solution is the most robust and best-practice design for a global, highly available application that must remain operational even if an entire AWS region fails. Each component addresses a specific requirement: Route 53 provides intelligent DNS routing, CloudFront caches content closer to users for low-latency access, and multi-region ALBs provide high availability and load balancing across multiple regions.

Route 53 latency-based routing ensures that end users are automatically directed to the region with the lowest network latency. This improves application responsiveness, especially for users located far from the primary region. Additionally, health checks in Route 53 can detect regional failures and automatically route traffic to healthy regions, ensuring that the application remains accessible during outages.

CloudFront acts as a global content delivery network (CDN). It caches static and dynamic content at edge locations around the world, reducing the round-trip time for users. This not only improves performance but also reduces load on origin servers. CloudFront can also serve dynamic content using regional edge caches, which further improves the responsiveness of applications that require real-time data or personalization.

Multi-region ALBs ensure that the application backend can handle traffic in multiple regions. Each ALB distributes traffic across multiple Availability Zones within a region, providing fault tolerance at the infrastructure level. If one Availability Zone fails, traffic is automatically routed to healthy instances in other AZs. By deploying ALBs in multiple regions, the architecture can survive even the failure of an entire AWS region.

Option B, single-region ALB with CloudFront, provides low latency only for users near that region and cannot survive a full regional failure. While CloudFront helps with content caching, it cannot provide real-time failover for dynamic application workloads.

Option C, S3 static website hosting with Transfer Acceleration, is limited to static content and does not provide dynamic application support. Transfer Acceleration optimizes object upload and download performance but does not provide regional failover or load balancing.

Option D, Global Accelerator with single-region EC2, improves network-level performance by routing users over AWS’s global network, but it cannot handle application-level failover or ensure high availability for dynamic workloads if the region hosting the EC2 instances goes down.

This architecture also integrates well with security, monitoring, and operational best practices. Traffic can be secured with AWS WAF and Shield for protection against web attacks and DDoS. IAM roles and policies control access to backend resources, while CloudTrail and CloudWatch provide visibility and auditing. CloudWatch metrics and alarms monitor ALB and EC2 performance, CloudFront cache hits, and Route 53 routing health checks.

In summary, a multi-region deployment with Route 53 latency-based routing, CloudFront, and multi-region ALBs ensures:

Global low-latency access to both static and dynamic content.

High availability during region-level failures.

Automatic failover with minimal operational overhead.

Integration with AWS security, logging, and monitoring services.

This approach follows AWS Well-Architected best practices, including the pillars of reliability, performance efficiency, operational excellence, and security. For SAP-C02 exam scenarios, this architecture demonstrates the proper use of multi-region design to achieve resiliency and optimal performance for global applications.

Question 54:

A company needs to implement a disaster recovery solution for an RDS database with an RPO of 5 minutes and an RTO of 15 minutes. Which AWS architecture should the solutions architect choose?

Answer:

A) Amazon Aurora Global Database
B) RDS automated backups with cross-region snapshot copy
C) Manual replication using EC2 instances
D) Standby EC2 database servers in another region

Explanation:

The correct answer is A) Amazon Aurora Global Database.

Aurora Global Database provides a fully managed, multi-region solution designed for disaster recovery, high availability, and minimal downtime. It replicates data asynchronously across multiple AWS regions with replication lag typically under one second. This ensures that the RPO—maximum allowable data loss—is effectively near zero, meeting the 5-minute RPO requirement.

Failover in Aurora Global Database is automated. In the event of a regional outage, applications can redirect traffic to the secondary region, achieving an RTO—time to recover operations—well within the required 15 minutes. Additionally, Aurora allows the secondary region to serve read queries while failover is pending, improving read availability and reducing latency for global users.

Option B, RDS automated backups with cross-region snapshot copy, introduces latency in both data replication and recovery. Restoring from snapshots is time-consuming and does not meet the 15-minute RTO requirement. Option C, manual replication using EC2 instances, is operationally complex, error-prone, and does not guarantee transactional consistency. Option D, standby EC2 database servers, cannot maintain real-time replication and failover requires manual intervention, making it unsuitable for strict RPO/RTO requirements.

Aurora Global Database supports six copies of data across three Availability Zones in each region. Data is automatically encrypted at rest using KMS and encrypted in transit using TLS. It also supports CloudWatch monitoring for replication lag, instance health, and query performance, which helps ensure operational visibility. CloudTrail auditing enables logging of all management actions, supporting compliance requirements.

This architecture ensures a cost-effective, highly available disaster recovery solution. Secondary regions can be used to scale read operations, reducing latency for global users and improving overall system performance. Additionally, automated failover and continuous replication simplify operational management and reduce human error, aligning with AWS Well-Architected principles of reliability, operational excellence, and performance efficiency.

For SAP-C02 exam scenarios, this demonstrates the correct use of Aurora Global Database for multi-region disaster recovery with strict RPO and RTO requirements. It illustrates the benefits of managed replication, high availability, and automation, which are critical for enterprise-level cloud architectures.

Question 55:

A company needs a serverless architecture for processing incoming IoT events, applying business logic, and storing results in a database. Which AWS services combination is most appropriate?

Answer:

A) AWS IoT Core, Lambda, DynamoDB
B) SQS with EC2 consumers
C) SNS with S3 triggers
D) RDS with manual ingestion

Explanation:

The correct answer is A) AWS IoT Core, Lambda, DynamoDB.

AWS IoT Core allows secure ingestion of IoT device data at massive scale. It supports authentication, device management, and reliable message delivery. Lambda functions can process these messages serverlessly, applying business logic without requiring provisioning or management of servers. DynamoDB provides a scalable, fully managed NoSQL database for storing results, supporting high throughput, low-latency access, and flexible data models for IoT telemetry.

Option B, SQS with EC2 consumers, requires manual provisioning and scaling of EC2 instances, adding operational overhead. Option C, SNS with S3 triggers, is suitable for notifications but does not support complex event processing or transactional storage. Option D, RDS with manual ingestion, introduces operational complexity and cannot scale efficiently to handle millions of events per second.

Serverless architectures with Lambda allow automatic scaling to handle spikes in incoming IoT events. Integration with CloudWatch provides monitoring and alerting for function invocations, error rates, and latency. DynamoDB integrates with Streams for event-driven updates or triggering downstream processes. Security is enforced through IAM policies, TLS connections, and KMS encryption for sensitive data.

This architecture follows AWS best practices for building highly available, cost-efficient, and scalable event-driven IoT solutions. It reduces operational complexity, eliminates server management, and supports near real-time analytics and processing. For SAP-C02 scenarios, it illustrates proper design for serverless, event-driven, and database-integrated architectures.

Question 56:

A company wants to implement a global caching solution to improve response times for a multi-region web application using DynamoDB. Which service should be used?

Answer:

A) DynamoDB Accelerator (DAX)
B) ElastiCache Redis
C) S3 Transfer Acceleration
D) RDS Read Replicas

Explanation:

The correct answer is A) DynamoDB Accelerator (DAX).

DAX provides a fully managed, in-memory cache for DynamoDB that reduces read latency from milliseconds to microseconds. It supports write-through caching, ensuring that updates in DynamoDB are automatically reflected in the cache. DAX clusters can scale horizontally and provide high availability with automatic failover across nodes.

Option B, ElastiCache Redis, is a general-purpose cache and requires application-level integration, increasing operational complexity. Option C, S3 Transfer Acceleration, is for object upload/download acceleration, not database caching. Option D, RDS Read Replicas, does not work with DynamoDB and cannot provide sub-millisecond read access.

DAX integrates with IAM for access control, KMS for encryption at rest, and TLS for encryption in transit. CloudWatch monitoring provides metrics for cache hits, latency, and node health. By offloading read operations from DynamoDB, DAX reduces cost, improves performance, and ensures consistent global application responsiveness.

For a multi-region web application using DynamoDB, implementing a global caching solution can significantly improve response times and overall application performance. AWS offers several caching and acceleration services, but choosing the right one depends on the database type and the required integration.

DynamoDB Accelerator (DAX) is a fully managed, in-memory caching service specifically designed for DynamoDB. It reduces read latency from milliseconds to microseconds by storing frequently accessed items in memory. DAX supports write-through caching, which means that updates to DynamoDB are automatically reflected in the cache, ensuring data consistency without requiring application-level logic. DAX clusters can scale horizontally to handle increasing traffic and provide high availability through automatic failover across nodes. This allows multi-region applications to maintain low-latency access to DynamoDB data, improving user experience and reducing operational complexity. DAX integrates with AWS Identity and Access Management (IAM) for access control, Key Management Service (KMS) for encryption at rest, and supports TLS for encryption in transit. CloudWatch monitoring provides detailed metrics such as cache hits, latency, and node health, enabling observability and proactive maintenance.

ElastiCache with Redis is a general-purpose, in-memory caching service. While it can accelerate data retrieval and support multiple data stores, it does not integrate directly with DynamoDB. Developers must implement caching logic in the application layer, which adds operational complexity and potential consistency challenges for multi-region applications.

S3 Transfer Acceleration is designed to speed up uploads and downloads to Amazon S3 using optimized network paths. Although it improves object transfer times, it does not provide database caching capabilities and cannot reduce DynamoDB read latency.

RDS Read Replicas are used to scale read operations for relational databases. They do not support DynamoDB, and therefore cannot provide the low-latency, in-memory access required for high-performance global applications.

Considering these factors, DynamoDB Accelerator (DAX) is the optimal solution for a global caching strategy for DynamoDB. It ensures consistent performance, reduces read load on the database, and simplifies application architecture while supporting high availability and security.

The correct answer is A) DynamoDB Accelerator (DAX).

Question 57:

A company is designing a high-throughput, event-driven system that requires ordered message processing and durability. Which AWS service is most appropriate?

Answer:

A) Amazon Kinesis Data Streams
B) Amazon SQS standard queues
C) Amazon SNS
D) DynamoDB Streams

Explanation:

The correct answer is A) Amazon Kinesis Data Streams.

Kinesis ensures durability and ordered delivery of records at the shard level. Lambda or EC2 consumers can process records in real time. Data is replicated across multiple Availability Zones, ensuring durability. Kinesis scales horizontally by adding shards to handle millions of messages per second.

Option B, SQS standard queues, provide at-least-once delivery and may result in duplicates. FIFO queues support ordering but have throughput limitations. Option C, SNS, is a pub/sub service that does not guarantee ordering. Option D, DynamoDB Streams, only captures table changes and is unsuitable for general message processing.

Kinesis integrates with CloudWatch for monitoring, supports extended data retention for replay, and provides encryption and access control via IAM and KMS. This architecture is ideal for high-throughput, low-latency, ordered event processing in real-time analytics and IoT workflows.

Question 58:

A company wants to implement a scalable global database with low-latency reads for users worldwide. Which AWS service is most suitable?

Answer:

A) Amazon Aurora Global Database
B) Amazon RDS Multi-AZ
C) DynamoDB global tables
D) Amazon Redshift

Explanation:

The correct answer is A) Amazon Aurora Global Database.

Aurora Global Database replicates data across regions with typical replication lag under one second. Secondary regions can handle read requests locally, providing low-latency access to global users. This solution also supports failover during regional outages, ensuring high availability.

Option B, Multi-AZ RDS, only replicates within a single region. Option C, DynamoDB global tables, is NoSQL and not ideal for relational workloads. Option D, Redshift, is designed for analytics and is unsuitable for transactional workloads.

Aurora integrates with CloudWatch for monitoring replication lag, query performance, and instance health. Security features include KMS encryption, IAM access control, and CloudTrail auditing. The architecture supports automatic storage scaling, read scaling, and high availability with minimal operational overhead, making it suitable for enterprise-grade global applications.

When designing a database solution for a global user base that requires low-latency reads and high availability, it is important to select a service capable of replicating data across multiple regions while supporting transactional workloads. AWS offers several database services, each suited for different use cases, and understanding the distinctions is key to making the right choice.

Amazon Aurora Global Database is a fully managed relational database solution that is specifically designed for globally distributed applications. Aurora Global Database replicates data across AWS regions with typical replication lag of under one second. This allows secondary regions to serve read requests locally, reducing latency for users worldwide. In the event of a regional outage, failover can be performed to another region, ensuring high availability and business continuity. Aurora also supports automatic storage scaling, read scaling with Aurora Replicas, and tight integration with monitoring and security services. CloudWatch provides metrics such as replication lag, query performance, and instance health, while security is maintained through AWS Key Management Service (KMS) encryption, Identity and Access Management (IAM) policies, and CloudTrail auditing. This combination of features makes Aurora Global Database suitable for enterprise-grade applications requiring relational data consistency and high-performance reads across multiple regions.

Amazon RDS Multi-AZ deployments, while providing high availability and automatic failover, only replicate data within a single region. This setup improves durability and uptime for applications in one region but does not address the low-latency read requirements for a global user base. Users located far from the primary region would still experience higher latency.

DynamoDB global tables offer multi-region replication for NoSQL workloads, providing low-latency reads worldwide. However, DynamoDB is a NoSQL database and may not be suitable for applications that require relational data structures, transactional consistency, or complex queries.

Amazon Redshift is a data warehousing solution designed for analytics rather than transactional workloads. While Redshift can handle large-scale queries efficiently, it is not optimized for low-latency transactional reads and is unsuitable for applications requiring frequent updates or global read access.

Considering the requirements for a relational, globally distributed, low-latency database, Amazon Aurora Global Database is the most suitable option. It provides seamless replication across regions, local read access, high availability, and enterprise-grade security with minimal operational overhead.

The correct answer is A) Amazon Aurora Global Database.

Question 59:

A company wants to implement exactly-once processing semantics in a serverless event-driven application that processes high-volume IoT messages. Which solution is best?

Answer:

A) Amazon Kinesis Data Streams with Lambda
B) Amazon SQS standard queues with Lambda
C) Amazon SNS with S3 triggers
D) DynamoDB Streams

Explanation:

The correct answer is A) Amazon Kinesis Data Streams with Lambda.

Kinesis provides ordered delivery at the shard level and durable storage across multiple AZs. Lambda can checkpoint processed records to ensure exactly-once processing. This ensures that each message is processed once and only once, even under high throughput.

Option B, SQS standard queues, provide at-least-once delivery and may result in duplicates. FIFO queues have throughput limitations. Option C, SNS, does not guarantee ordering or exactly-once semantics. Option D, DynamoDB Streams, only tracks table changes, limiting its use to specific scenarios.

This architecture is ideal for IoT, real-time analytics, and event-driven workflows. It provides high durability, low latency, and operational simplicity while supporting replay of events and integration with other AWS services for downstream processing.

Question 60:

A company needs to orchestrate a complex serverless workflow involving multiple Lambda functions, retries, and conditional branching. Which AWS service is most appropriate?

Answer:

A) AWS Step Functions
B) Amazon SWF
C) AWS Batch
D) Amazon SQS

Explanation:

The correct answer is A) AWS Step Functions.

AWS Step Functions provides serverless orchestration using state machines. Developers can define sequential, parallel, and conditional execution of Lambda functions. It supports retries, error handling, and timeouts. Step Functions also integrates with ECS, SNS, and other AWS services, providing operational visibility through execution history, CloudWatch metrics, and X-Ray tracing.

Option B, SWF, is legacy and requires managing worker nodes. Option C, Batch, is for batch processing, not orchestration. Option D, SQS is a messaging service, not a workflow orchestrator.

Step Functions standard workflows are durable and maintain a history of execution for auditability, while express workflows support high throughput for short-duration tasks. Integration with IAM ensures secure execution, and KMS encryption protects sensitive workflow data. This architecture simplifies complex serverless workflows, reduces operational overhead, and ensures reliability and observability, aligning with SAP-C02 best practices for serverless orchestration.

When a company needs to orchestrate a complex serverless workflow that involves multiple AWS Lambda functions, conditional logic, retries, and error handling, choosing the right service is critical to ensure reliability, scalability, and operational visibility. AWS provides several services for processing and workflow management, but each serves different use cases and operational models.

AWS Step Functions is the most appropriate solution for orchestrating complex serverless workflows. Step Functions allows developers to define workflows as state machines, which provide sequential, parallel, and conditional execution of Lambda functions and other AWS services. This makes it possible to implement complex business logic without building custom orchestration code. Step Functions also supports retries, catchers, and timeouts for individual states, ensuring that workflows can handle errors gracefully and continue processing without manual intervention. It integrates seamlessly with services such as Amazon ECS, SNS, SQS, DynamoDB, and more, enabling orchestration across a broad set of AWS resources. Operational visibility is enhanced through execution history, CloudWatch metrics, and AWS X-Ray tracing, allowing developers and operators to monitor, debug, and optimize workflows efficiently.

Alternative solutions are less suitable for this scenario. Amazon SWF (Simple Workflow Service) is a legacy workflow service that requires managing worker nodes and coordinating tasks manually, adding operational overhead. While it provides similar orchestration capabilities, it is not serverless and is less convenient for modern cloud-native applications. AWS Batch is designed for running large-scale batch processing jobs and is not intended for orchestrating conditional workflows with multiple small tasks like Lambda functions. Amazon SQS is a fully managed messaging queue that enables decoupling of microservices, but it does not provide workflow orchestration, retries, or conditional branching on its own.

Step Functions provides two workflow types: standard workflows, which are durable and maintain a complete execution history suitable for auditing and long-running tasks, and express workflows, which support high throughput and short-duration tasks. Security is integrated through IAM for access control and KMS for encrypting sensitive workflow data. This combination ensures that complex serverless workflows are reliable, observable, and maintainable, while significantly reducing operational complexity.

The correct answer is A) AWS Step Functions.