Amazon AWS Certified Solutions Architect — Associate SAA-C03 Exam Dumps and Practice Test Questions Set 14 Q196-210

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Question 196

Which AWS service provides fully managed, high-performance in-memory caching for applications?

A) Amazon ElastiCache
B) Amazon DynamoDB
C) Amazon RDS
D) Amazon Redshift

Answer: A) Amazon ElastiCache

Explanation:

Amazon ElastiCache is a fully managed in-memory caching service offered by AWS that is designed to enhance application performance by storing frequently accessed data in memory. By keeping data in memory rather than relying solely on disk-based databases, ElastiCache reduces latency and accelerates data retrieval, which significantly improves the responsiveness of applications. This capability is particularly valuable for workloads that require rapid access to data, such as real-time analytics, gaming leaderboards, session management, and high-traffic web applications. ElastiCache supports two widely used caching engines, Redis and Memcached, giving organizations the flexibility to choose the engine that best aligns with their application requirements. Redis provides advanced data structures, persistence options, and replication features, while Memcached offers a simpler, high-performance, and scalable caching solution.

One of the key advantages of Amazon ElastiCache is its ability to reduce the load on backend databases. By caching frequently queried data, applications can minimize the number of direct requests to databases such as Amazon RDS or DynamoDB, which helps optimize database performance and can lead to cost savings. This offloading of database traffic not only enhances performance but also improves scalability, allowing applications to handle higher volumes of requests without degradation in speed or reliability. Additionally, ElastiCache supports clustering and replication, which enables horizontal scaling and high availability. With clustering, data can be distributed across multiple nodes, allowing for larger datasets to be cached and providing better performance for read and write operations. Replication ensures that data is synchronized across multiple nodes, enhancing fault tolerance and ensuring continuous availability even if a node fails.

ElastiCache also offers automatic failover and seamless recovery mechanisms. In the event of a node failure, failover is automatically handled to maintain application availability without manual intervention. This makes ElastiCache a reliable choice for critical applications that cannot afford downtime. Monitoring and management are simplified through integration with Amazon CloudWatch, which provides metrics, logs, and alarms to help administrators track cache performance, identify potential issues, and take proactive action. Security is also an integral part of ElastiCache, with support for Virtual Private Cloud (VPC) deployment, encryption at rest and in transit, and fine-grained access control through AWS Identity and Access Management (IAM).

While other AWS services offer complementary capabilities, they do not provide the same fully managed in-memory caching functionality. Amazon DynamoDB is a fully managed NoSQL database and supports DAX (DynamoDB Accelerator) for caching, but it is not a general-purpose in-memory caching service. Amazon RDS provides managed relational databases, and Amazon Redshift is optimized for analytics, but neither is designed for low-latency, high-speed caching of frequently accessed data. For organizations seeking to improve application performance, reduce database load, and deliver low-latency experiences, Amazon ElastiCache is the appropriate solution. Its combination of high performance, scalability, reliability, and ease of management makes it a critical component for modern, high-performance applications deployed on AWS.

Question 197

Which AWS service allows orchestration of multi-step workflows with automated error handling?

A) AWS Step Functions
B) AWS Lambda
C) Amazon SQS
D) Amazon EventBridge

Answer: A) AWS Step Functions

Explanation:

AWS Step Functions is a fully managed serverless orchestration service that enables organizations to design and execute complex workflows in the cloud. It allows applications to be structured as a series of steps, where each step represents a task or an action that can interact with other AWS services. One of the primary advantages of Step Functions is its ability to coordinate multiple services in a reliable and fault-tolerant manner, providing a clear structure for executing multi-step processes that require error handling, retries, or conditional branching. This makes it particularly suitable for use cases such as ETL pipelines, microservices orchestration, and automating business processes that involve multiple interdependent operations.

Step Functions provides a highly visual interface for workflow design, allowing developers and administrators to easily map out the sequence of steps, understand the dependencies, and track the flow of data through each stage of the workflow. The visual nature of the service also makes monitoring and debugging simpler, as users can quickly identify where failures or delays occur and take corrective action. Workflows can include branching logic, enabling different execution paths based on conditions, as well as parallel execution to process multiple tasks simultaneously, improving efficiency and reducing the time required to complete complex operations. Additionally, Step Functions supports timeouts for individual tasks, ensuring that stalled or long-running operations do not block the entire workflow.

Another significant benefit of Step Functions is its built-in error handling and retry mechanisms. Tasks that fail due to transient errors can be automatically retried according to configurable policies, reducing the need for manual intervention and improving the overall reliability of workflows. In case of persistent failures, workflows can be designed to take alternative paths or trigger alerts, ensuring that critical processes continue to operate or that corrective measures are initiated promptly.

Step Functions integrates seamlessly with a wide range of AWS services, including Lambda, ECS, S3, DynamoDB, and more. This integration allows workflows to leverage serverless computing, containerized applications, storage, and database services within a single orchestrated process. For example, a Step Functions workflow can execute a Lambda function to process data, store intermediate results in S3, update a DynamoDB table, and trigger an ECS task for further processing, all while managing execution order, error handling, and retries automatically.

While other AWS services provide useful capabilities for building applications, they do not offer the same level of workflow orchestration that Step Functions provides. AWS Lambda is excellent for executing individual tasks but does not manage multi-step workflows or handle errors and retries automatically. Amazon SQS can decouple components through message queuing but cannot enforce sequential execution with conditional logic or retries. Amazon EventBridge can route events between services but lacks the ability to coordinate complex workflows with branching and error handling.

For organizations that require reliable, automated, and serverless workflow orchestration, AWS Step Functions is the optimal solution. It simplifies the management of multi-step processes, ensures fault tolerance, reduces operational overhead, and provides visibility into workflow execution. By combining orchestration, error handling, retries, and integration with other AWS services, Step Functions enables the creation of scalable, resilient, and maintainable cloud applications.

Question 198

Which AWS service enables encryption of data and key management across AWS services?

A) AWS KMS
B) AWS IAM
C) AWS Secrets Manager
D) Amazon S3

Answer: A) AWS KMS

Explanation:

AWS Key Management Service, commonly known as KMS, is a fully managed service provided by Amazon Web Services that allows organizations to create, control, and manage encryption keys used to protect data across a wide variety of AWS services. In modern cloud environments, securing sensitive data is critical, and KMS provides a centralized approach to key management, making it easier for organizations to enforce security policies, maintain compliance, and simplify encryption operations. KMS supports both symmetric and asymmetric encryption keys, enabling organizations to choose the appropriate cryptographic approach for different types of workloads and security requirements. Symmetric keys are used for scenarios where the same key is employed for both encryption and decryption, while asymmetric keys utilize a public-private key pair for additional security in cases such as digital signatures and secure key exchange.

One of the important features of AWS KMS is automatic key rotation. By enabling automatic rotation, organizations can ensure that cryptographic keys are periodically replaced without manual intervention, which reduces the risk of key compromise and aligns with security best practices and compliance mandates. This feature is particularly valuable for meeting regulatory requirements, where regular rotation of encryption keys is often mandated. KMS also allows for the creation of customer-managed keys, giving organizations full control over who can use them, what operations are permitted, and how long the keys remain active.

KMS integrates seamlessly with AWS Identity and Access Management (IAM) to provide fine-grained access control over encryption keys. Administrators can define policies that determine which users or services can perform specific cryptographic operations, such as encrypting, decrypting, or re-encrypting data. This level of control ensures that only authorized personnel or services can access sensitive data, reducing the risk of unauthorized disclosure. Additionally, KMS integrates with AWS CloudTrail to provide a complete audit trail of all key usage. Organizations can track every operation performed with their keys, enabling monitoring, compliance reporting, and forensic analysis in case of security incidents.

Many AWS services rely on KMS for encryption at rest, including Amazon Simple Storage Service (S3), Amazon Relational Database Service (RDS), Amazon Elastic Block Store (EBS), and Amazon DynamoDB. When data is stored in these services, KMS manages the encryption keys used to secure the information, ensuring that sensitive data remains protected while in storage. While other services provide complementary security functionality, they do not offer centralized key management in the same way. AWS IAM controls access to resources but does not perform encryption. AWS Secrets Manager securely stores sensitive information, such as database credentials or API keys, and can automatically rotate them, but it relies on KMS to handle encryption. Amazon S3 offers server-side encryption for objects, but KMS is responsible for managing the keys used in that encryption process, providing a higher level of security and compliance assurance.

Overall, AWS KMS is the appropriate service for centralized encryption and key management in AWS environments. It simplifies the creation, use, and monitoring of encryption keys, supports compliance with regulatory standards, and integrates with multiple AWS services to provide a secure foundation for protecting sensitive data. By combining centralized key management, access control, auditability, and automatic rotation, KMS enables organizations to implement strong encryption practices without the operational overhead of managing cryptographic keys manually. It is an essential tool for any organization seeking to secure data in the cloud while maintaining control, visibility, and compliance.

Question 199

Which AWS service provides centralized backup management across multiple AWS resources?

A) AWS Backup
B) Amazon S3
C) AWS DataSync
D) AWS Config

Answer: A) AWS Backup

Explanation:

AWS Backup is a fully managed service from Amazon Web Services that provides organizations with a centralized and automated approach to managing backups across multiple AWS services. In modern IT environments, protecting data is a critical aspect of operational strategy, and organizations often rely on multiple storage and database services to run their applications. AWS Backup addresses the challenges of coordinating backup operations across these services by offering a single point of management, thereby simplifying the process and improving reliability. It is designed to work with a wide range of AWS resources, including Elastic Block Store (EBS) volumes, Relational Database Service (RDS) databases, DynamoDB tables, Elastic File System (EFS) file systems, and FSx file systems. By providing centralized backup management, AWS Backup allows organizations to enforce consistent policies across different types of data and workloads without needing to configure separate backup mechanisms for each service.

One of the key features of AWS Backup is its support for automated backup scheduling. Administrators can define policies that specify when backups should occur, ensuring that data is consistently protected without requiring manual intervention. In addition to scheduling, AWS Backup allows organizations to define retention policies, which determine how long backups are retained and when they are deleted or archived. This capability ensures that backup data is maintained in compliance with organizational standards and regulatory requirements. Lifecycle management further enhances efficiency by enabling the automatic transition of backup data to lower-cost storage tiers over time, helping to optimize storage costs while maintaining access to critical information.

AWS Backup also supports advanced features such as cross-region and cross-account backups. Cross-region backups provide geographic redundancy by replicating data to a different AWS region, which is essential for disaster recovery planning and ensures that data remains available even in the event of a regional outage. Cross-account backups allow organizations to store backup data in separate AWS accounts, adding an additional layer of security and protection against accidental deletion or compromise. These capabilities make AWS Backup a versatile and reliable solution for organizations with complex or highly regulated environments.

Security and monitoring are integral aspects of AWS Backup. Integration with AWS Identity and Access Management (IAM) allows administrators to control access to backup resources and define fine-grained permissions, ensuring that only authorized users can perform backup or restore operations. Monitoring and reporting are facilitated through Amazon CloudWatch, which provides visibility into backup activities, operational status, and potential errors. This transparency helps organizations track compliance, identify issues proactively, and maintain confidence that their data protection strategies are being followed effectively.

While other AWS services offer related functionality, they do not provide the same centralized, automated backup management capabilities. Amazon S3 is primarily an object storage service and does not orchestrate backups. AWS DataSync is designed to transfer data between on-premises storage and AWS but does not manage backup scheduling or retention. AWS Config monitors configuration changes and compliance but does not handle the actual backup of data. In contrast, AWS Backup is specifically designed to address the full lifecycle of backup management, including automation, retention, cross-region replication, access control, and monitoring.

AWS Backup is the correct and most effective service for centralized backup management in AWS environments. It simplifies backup operations, enhances security, supports compliance requirements, and reduces operational complexity. By providing a fully managed solution with advanced automation, monitoring, and cross-service integration, AWS Backup enables organizations to protect their critical data reliably, efficiently, and consistently across multiple AWS services.

Question 200

Which AWS service allows querying data stored in S3 using standard SQL without ETL?

A) Amazon Athena
B) Amazon Redshift
C) AWS Glue
D) Amazon EMR

Answer: A) Amazon Athena

Explanation:

Amazon Athena is a fully managed, serverless interactive query service provided by Amazon Web Services that allows users to analyze data directly in Amazon S3 using standard SQL. One of the key advantages of Athena is that it eliminates the need to provision or manage any infrastructure, enabling organizations to focus on extracting insights from their data rather than maintaining servers or clusters. By supporting a wide range of data formats, including CSV, JSON, Parquet, ORC, and Avro, Athena provides flexibility for querying both structured and semi-structured data. Its integration with the AWS Glue Data Catalog allows users to manage schemas, create tables, and maintain metadata in a centralized manner, simplifying data organization and discovery.

Athena is particularly well-suited for ad-hoc analytics. Users can run queries on datasets stored in S3 without needing to perform complex Extract, Transform, Load (ETL) operations or move data into a separate analytics system. This serverless approach allows organizations to pay only for the queries they run, making it cost-effective for scenarios where large amounts of data need to be explored or analyzed intermittently. By enabling SQL queries directly on S3, Athena reduces the time and complexity associated with traditional data processing pipelines, making data immediately accessible to analysts, data scientists, and business users.

The service supports a variety of use cases, including log analysis, reporting, and interactive exploration of large datasets. For example, companies can use Athena to query web server logs stored in S3 to generate insights into user behavior, system performance, or security events. Similarly, financial or operational data stored in multiple formats can be queried and aggregated without needing to first transform or load the data into a data warehouse. This capability streamlines data analysis and accelerates decision-making by allowing users to gain insights from raw or lightly processed datasets.

While other AWS services provide related functionality, they do not offer the same combination of serverless operation and direct querying of S3 data. Amazon Redshift is a fully managed data warehouse designed for large-scale analytical workloads. It provides high performance for complex queries, but data must first be loaded into Redshift tables, which introduces additional ETL steps and infrastructure considerations. AWS Glue is a managed ETL service that allows users to extract, transform, and catalog data, but it does not provide an interactive query interface for running SQL queries directly against S3 data. Amazon EMR provides managed clusters for processing large-scale data using frameworks such as Hadoop or Spark, but it requires users to manage and configure clusters, and it is not serverless. Athena stands out because it allows immediate, on-demand querying of data in its native location without additional infrastructure or data movement.

Athena also integrates seamlessly with other AWS analytics and visualization services. Query results can be connected to Amazon QuickSight for dashboards and reporting, or combined with other AWS services such as Lambda for automated processing. Security features include encryption at rest using AWS KMS, fine-grained access control with IAM policies, and network isolation with Amazon VPC endpoints. These integrations and security capabilities make Athena a robust solution for organizations that need fast, flexible, and secure querying of data stored in S3.

Amazon Athena is the ideal service for querying data in Amazon S3 using SQL without requiring ETL pipelines or infrastructure management. Its serverless architecture, support for multiple data formats, integration with the AWS Glue Data Catalog, and pay-per-query pricing make it a cost-effective, flexible, and highly accessible solution for ad-hoc analytics and interactive exploration of large datasets. For organizations looking to analyze S3 data quickly and efficiently, Athena provides the necessary tools to gain insights directly from the source.

Question 201

Which AWS service provides scalable relational database hosting with automatic backups and multi-AZ deployments?

A) Amazon RDS
B) Amazon DynamoDB
C) Amazon Redshift
D) Amazon Aurora

Answer: A) Amazon RDS

Explanation:

Amazon RDS, or Relational Database Service, is a fully managed service provided by Amazon Web Services that allows organizations to deploy, operate, and scale relational databases in the cloud efficiently. One of the primary benefits of RDS is that it abstracts much of the operational complexity associated with running a relational database. This enables developers and database administrators to focus on building applications rather than managing infrastructure. RDS supports a wide variety of database engines, including MySQL, PostgreSQL, MariaDB, Oracle, and SQL Server, allowing organizations to choose the engine that best fits their specific application requirements or existing technology stack. This flexibility ensures that both new and existing applications can leverage cloud-managed relational databases without needing to modify underlying code significantly.

A critical feature of Amazon RDS is its automated backup and snapshot capabilities. Backups are performed automatically according to a defined schedule, enabling point-in-time recovery of databases. In addition to automated backups, RDS allows users to take manual snapshots of databases, which can be retained for as long as needed. These features provide robust protection against accidental deletion, data corruption, or other operational failures. Additionally, RDS supports multi-AZ deployments, which replicate data synchronously across multiple Availability Zones. This ensures high availability and automatic failover in the event of hardware or infrastructure failures, minimizing downtime and maintaining continuity for applications that require constant availability.

RDS also automates many routine maintenance tasks, including software patching, monitoring, and scaling. Administrators can monitor database performance and health using Amazon CloudWatch metrics, which provide insight into resource utilization, latency, and query performance. Scaling of database instances can be done vertically or horizontally with minimal manual intervention, allowing applications to handle increasing workloads without significant operational overhead. This combination of automated maintenance, monitoring, and scaling reduces administrative burden and ensures that databases remain reliable, performant, and secure.

While other AWS services offer complementary database or analytics capabilities, they do not provide the same features for relational database management. Amazon DynamoDB is a fully managed NoSQL database service optimized for key-value and document workloads. Although it offers fast performance and high availability, DynamoDB is not relational and does not support SQL queries or multi-AZ relational failover in the same manner as RDS. Amazon Redshift is designed as a data warehouse for large-scale analytical workloads. It provides petabyte-scale storage and the ability to perform complex analytical queries, but it is not intended for transactional workloads or high-availability relational database deployments. Amazon Aurora, on the other hand, is a high-performance, MySQL- and PostgreSQL-compatible database engine managed under the RDS umbrella. Aurora offers enhanced performance, multi-AZ replication, and automated backups, but RDS as a service encompasses a broader range of engines and provides the foundational framework for deploying scalable relational databases.

Amazon RDS is the ideal service for organizations seeking a scalable, fully managed relational database solution in the cloud. Its support for multiple database engines, automated backups, multi-AZ deployments, monitoring, and maintenance automation ensures high availability, reliability, and operational efficiency. For enterprises that require a relational database with robust backup capabilities, simplified management, and the ability to scale according to workload demands, Amazon RDS provides a comprehensive and dependable solution.

Question 202

Which AWS service allows serverless execution of code in response to events without provisioning servers?

A) AWS Lambda
B) Amazon EC2
C) Amazon ECS
D) AWS Fargate

Answer: A) AWS Lambda

Explanation:

AWS Lambda is a cloud-based, serverless compute service provided by Amazon Web Services that allows developers to run code in response to a wide variety of events without the need to manage servers or infrastructure. It is designed to automatically handle all aspects of computing resources, including provisioning, scaling, and execution. This means that developers do not need to worry about setting up or maintaining servers, patching operating systems, or scaling the infrastructure to handle changes in workload. Lambda is event-driven, which means it can be triggered by events generated by other AWS services, such as S3 when a new file is uploaded, DynamoDB when there is a change in the database, API Gateway for handling HTTP requests, or even custom triggers created by the user. One of the main advantages of AWS Lambda is its billing model. Users are only charged for the compute time that their code actually consumes, measured in milliseconds, rather than paying for idle resources. This can lead to significant cost savings, especially for workloads that have variable or unpredictable usage patterns. Lambda also supports multiple programming languages, including Python, Node.js, Java, Go, and C#, providing flexibility for developers to use the language that best suits their application needs.

In contrast, Amazon EC2, or Elastic Compute Cloud, provides virtual servers in the cloud that require manual provisioning and management. When using EC2, users are responsible for launching instances, choosing instance types, configuring security groups, managing storage, and scaling resources based on demand. Unlike Lambda, EC2 is not serverless; it requires continuous infrastructure management and maintenance. Users must monitor their instances, handle operating system updates, and scale their environment either manually or using automated scaling policies. EC2 is well suited for applications that need long-running processes, complex configurations, or direct control over the underlying operating system and server environment, but it does not provide the event-driven, serverless model that Lambda offers.

Amazon ECS, or Elastic Container Service, is another AWS service designed for container orchestration. ECS allows users to run and manage containerized applications, but it relies on either EC2 instances or AWS Fargate for the underlying compute resources. While ECS can operate in a serverless manner when paired with Fargate, it is primarily focused on managing containers rather than executing code in response to specific events. ECS provides powerful tools for deploying, scaling, and monitoring containers but does not natively offer the event-driven compute model that is central to Lambda’s design.

AWS Fargate is a serverless compute engine specifically for containers. It abstracts the underlying infrastructure, allowing developers to run containers without managing servers. However, Fargate is designed for containerized workloads rather than general-purpose functions triggered by events. It does not replace the event-driven execution model that Lambda provides, making it more suitable for running microservices or container-based applications rather than small, event-triggered functions.

For scenarios that require serverless, event-driven execution of code without the burden of infrastructure management, AWS Lambda is the most appropriate choice. It combines automatic scaling, precise billing, language flexibility, and integration with a wide range of AWS services, making it the ideal solution for building modern, responsive, and cost-efficient applications in the cloud.

Question 203

Which AWS service provides scalable object storage with lifecycle management and cross-region replication?

A) Amazon S3
B) Amazon EBS
C) Amazon FSx
D) Amazon Glacier

Answer: A) Amazon S3

Explanation:

Amazon S3, or Simple Storage Service, is a cloud-based storage solution designed to provide highly scalable, durable, and secure object storage for a wide variety of use cases. It allows organizations and developers to store virtually unlimited amounts of data in a reliable and accessible manner. One of the primary advantages of S3 is its scalability, which enables it to accommodate everything from small applications to enterprise-level workloads without the need for users to manage infrastructure or worry about capacity planning. Data stored in S3 is automatically distributed across multiple physical facilities within an AWS region, ensuring durability and availability. Amazon S3 is also built with security in mind, offering features such as encryption for data at rest and in transit, access control policies, and integration with AWS Identity and Access Management for fine-grained permission management.

S3 supports advanced features that make it highly versatile for different storage needs. One such feature is lifecycle policies, which allow users to automatically transition objects from one storage class to another over time. For example, frequently accessed data can remain in S3 Standard, while older or infrequently accessed data can automatically move to S3 Glacier or S3 Intelligent-Tiering to reduce storage costs. This automation helps organizations optimize their storage spending while still maintaining access to data as needed. S3 also supports cross-region replication, enabling data to be automatically copied to another AWS region for improved availability, compliance, or disaster recovery purposes. Versioning is another key capability, allowing users to preserve, retrieve, and restore every version of an object, which can be critical for data protection and recovery from accidental deletions or overwrites.

While Amazon S3 provides object storage with these advanced features, other AWS storage services serve different purposes and are not directly comparable for event-driven or lifecycle-managed storage. Amazon EBS, or Elastic Block Store, provides block-level storage intended for use with EC2 instances. EBS is optimized for low-latency access and high-performance workloads, making it ideal for applications such as databases or virtual machines. However, it does not include object-level management features such as lifecycle policies or cross-region replication, and it is not designed for long-term, scalable storage in the same way S3 is.

Amazon FSx offers fully managed file systems for workloads requiring shared file storage, such as Windows-based applications or high-performance computing with Lustre. FSx provides robust file-level access, but it does not function as object storage and lacks features like automated tiering, lifecycle policies, or cross-region replication that S3 provides. Similarly, Amazon Glacier is focused on archival storage, offering low-cost long-term storage for data that is rarely accessed. While Glacier integrates with S3 lifecycle policies for automated transitions, it is not meant to serve as an active storage solution for frequently used data.

For organizations looking for scalable, durable, and secure object storage that supports lifecycle management, cross-region replication, versioning, and encryption, Amazon S3 is the ideal choice. Its ability to handle a wide range of storage scenarios, from data lakes to backups and static content hosting, makes it the cornerstone of many cloud storage architectures, providing both flexibility and cost efficiency.

Question 204

Which AWS service provides temporary, secure credentials for programmatic access to AWS resources?

A) AWS STS
B) AWS IAM
C) Amazon Cognito
D) AWS KMS

Answer: A) AWS STS

Explanation:

AWS Security Token Service (STS) provides temporary credentials for users or applications to access AWS resources. STS enables role assumption, identity federation, and cross-account access without sharing long-term credentials. Temporary credentials include an access key ID, secret access key, and session token with configurable expiration times, enhancing security in dynamic environments.

AWS IAM is used to create users, groups, and roles with policies but does not provide temporary credentials by itself.

Amazon Cognito allows authentication and authorization for end users, including identity federation, but focuses on application-level users rather than programmatic AWS access.

AWS KMS manages encryption keys for securing data but does not provide temporary credentials.

The correct service for temporary, secure credentials is AWS STS.

Question 205

Which AWS service provides fully managed message queuing for decoupling application components?

A) Amazon SQS
B) Amazon SNS
C) Amazon EventBridge
D) AWS Lambda

Answer: A) Amazon SQS

Explanation:

Amazon Simple Queue Service (SQS) is a fully managed message queue that decouples components of distributed applications. It supports standard queues with at-least-once delivery and FIFO queues for exactly-once processing and message ordering. SQS scales automatically, ensuring applications can handle variable workloads without message loss. It integrates with Lambda, ECS, and other services for event-driven processing.

Amazon SNS is a pub/sub service for notifications and message broadcasting but does not provide queuing or guaranteed message retention.

Amazon EventBridge routes events between AWS services but does not function as a message queue for asynchronous processing.

AWS Lambda executes code in response to triggers but does not provide a queuing mechanism by itself.

The correct service for fully managed, decoupled message queuing is Amazon SQS.

Question 206

Which AWS service provides a fully managed, serverless workflow orchestration with visual workflow creation and error handling?

A) AWS Step Functions
B) AWS Lambda
C) Amazon EventBridge
D) Amazon SQS

Answer: A) AWS Step Functions

Explanation:

AWS Step Functions is a fully managed service for orchestrating distributed applications and microservices using visual workflows. It allows defining sequential or parallel tasks, branching logic, retries, and error handling in workflows. Step Functions integrates with Lambda, ECS, S3, DynamoDB, and other AWS services, making it ideal for ETL pipelines, business process automation, and complex event-driven workflows. Step Functions automatically scales and handles state management, reducing operational overhead.

AWS Lambda executes individual tasks in response to events, but it does not orchestrate multi-step workflows with built-in visual execution and error handling.

Amazon EventBridge is a serverless event bus that allows routing of events between AWS services and applications, but it does not coordinate sequential or parallel tasks in a workflow with retry logic.

Amazon SQS is a message queuing service that decouples application components, providing reliable message delivery. However, it does not provide orchestration or visual workflow management.

The correct service for fully managed, serverless workflow orchestration with visual monitoring and error handling is AWS Step Functions.

Question 207

Which AWS service allows querying structured data in Amazon S3 using standard SQL without requiring ETL?

A) Amazon Athena
B) Amazon Redshift
C) AWS Glue
D) Amazon EMR

Answer: A) Amazon Athena

Explanation:

Amazon Athena is a serverless interactive query service that allows users to run SQL queries directly on data stored in S3. It supports formats such as CSV, JSON, Parquet, ORC, and Avro. Athena integrates with the AWS Glue Data Catalog for schema management. It eliminates the need for complex ETL processes, enabling ad-hoc analytics on structured or semi-structured data. Billing is pay-per-query, and Athena automatically scales to handle query execution without provisioning servers.

Amazon Redshift is a fully managed data warehouse that requires loading data into its cluster and is optimized for analytics but does not natively query S3 without ETL.

AWS Glue is an ETL service designed to extract, transform, and load data but does not provide direct ad-hoc querying.

Amazon EMR provides managed Hadoop and Spark clusters for big data processing but requires cluster management and is not serverless.

The correct service for SQL queries on S3 without ETL is Amazon Athena.

Question 208

Which AWS service provides managed in-memory caching for low-latency application performance?

A) Amazon ElastiCache
B) Amazon DynamoDB
C) Amazon RDS
D) Amazon Redshift

Answer: A) Amazon ElastiCache

Explanation:

Amazon ElastiCache is a fully managed in-memory caching service supporting Redis and Memcached. It improves application performance by caching frequently accessed data, reducing database load, and decreasing latency. ElastiCache supports clustering, replication, automatic failover, and CloudWatch monitoring. Common use cases include session storage, leaderboard tracking, and caching database query results.

Amazon DynamoDB is a managed NoSQL database with optional DAX for caching, but it is not primarily an in-memory cache service.

Amazon RDS is a managed relational database service for transactional workloads, not designed for high-performance in-memory caching.

Amazon Redshift is a data warehouse optimized for analytical workloads and is not suitable for low-latency caching.

The correct service for fully managed, high-performance in-memory caching is Amazon ElastiCache.

 

Question 209

Which AWS service provides encryption key management and centralized control over cryptographic keys?

A) AWS KMS
B) AWS IAM
C) AWS Secrets Manager
D) Amazon S3

Answer: A) AWS KMS

Explanation:

AWS Key Management Service (KMS) provides centralized creation, management, and control of encryption keys used to protect data across AWS services. KMS supports symmetric and asymmetric keys, automatic rotation, fine-grained IAM-based access policies, and integration with CloudTrail for auditing key usage. Many AWS services, including S3, RDS, EBS, and DynamoDB, use KMS-managed keys for data encryption.

AWS IAM manages access and permissions to AWS resources but does not perform encryption itself.

AWS Secrets Manager stores and rotates credentials and secrets, using KMS for encrypting those secrets.

Amazon S3 provides storage and can encrypt objects, but the underlying key management is handled by KMS.

The correct service for encryption key management is AWS KMS.

Question 210

Which AWS service provides centralized backup management across multiple AWS resources and supports policy-based scheduling?

A) AWS Backup
B) Amazon S3
C) AWS DataSync
D) AWS Config

Answer: A) AWS Backup

Explanation:

AWS Backup is a fully managed service offered by Amazon Web Services that provides a centralized solution for automating and managing backups across a variety of AWS resources. Organizations often face the challenge of ensuring that critical data stored in multiple services is consistently backed up, securely retained, and recoverable in case of data loss or corruption. AWS Backup addresses these challenges by offering a unified platform to handle backup operations for services such as Amazon Elastic Block Store (EBS) volumes, Amazon Relational Database Service (RDS) databases, Amazon DynamoDB tables, Amazon Elastic File System (EFS) file systems, and Amazon FSx file systems. By consolidating backup management under a single service, AWS Backup eliminates the need to configure individual backup solutions for each service, streamlining operational efforts and reducing complexity.

One of the key features of AWS Backup is policy-based automation. Organizations can define backup policies that include scheduling, retention periods, and lifecycle rules. This allows backups to be performed automatically according to predefined schedules, reducing the risk of human error and ensuring that all critical resources are consistently protected. Retention management within AWS Backup ensures that data is stored for the appropriate duration according to organizational or regulatory requirements, and old backups can be automatically deleted or transitioned to lower-cost storage tiers when they are no longer needed. This feature helps organizations manage storage costs while maintaining compliance with data retention policies.

AWS Backup also supports cross-region and cross-account backups. Cross-region backup allows organizations to replicate backup data to different AWS regions, providing geographic redundancy and enhancing disaster recovery capabilities. Cross-account backup enables organizations to store backups in separate AWS accounts, which adds an additional layer of protection against accidental deletion, unauthorized access, or operational errors within a single account. These capabilities make AWS Backup a versatile solution for organizations with complex environments or strict regulatory and compliance requirements.

Integration with AWS Identity and Access Management (IAM) ensures secure access control over backup operations. Administrators can define who can create, restore, or delete backups and which resources they can access. This granular control is critical for enforcing security policies and meeting compliance requirements. Additionally, AWS Backup provides detailed monitoring and reporting features that allow organizations to track backup activity, identify failures, and generate audit reports. This visibility helps maintain compliance with internal policies and external regulations by demonstrating that data protection measures are in place and functioning as intended.

While other AWS services provide related capabilities, they do not offer the centralized backup management that AWS Backup delivers. Amazon S3 is primarily object storage and does not orchestrate backups across multiple services. AWS DataSync facilitates data transfer between on-premises environments and AWS but does not manage backup scheduling or retention. AWS Config monitors configuration changes and compliance but does not handle data backup operations. Therefore, for organizations seeking a fully managed, centralized, and automated backup solution across a variety of AWS services, AWS Backup is the appropriate choice. It simplifies backup management, enhances security, supports compliance, and provides the tools necessary for efficient disaster recovery planning.