Amazon AWS Certified Developer – Associate DVA-C02 Exam Dumps and Practice Test Questions Set 3 Q41-60

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Question 41 

Which AWS service allows you to implement fine-grained access control for your S3 objects?

A) AWS IAM
B) Amazon S3 Bucket Policies
C) AWS KMS
D) Amazon CloudFront

Answer: B) Amazon S3 Bucket Policies

Explanation: 

AWS IAM (Identity and Access Management) is a foundational service for managing access in AWS. It allows you to define users, groups, and roles and assign permissions to these identities. With IAM, you can control who can access AWS resources at a high level, including S3 buckets. However, IAM policies are generally broad and apply to resource-level access rather than specific object-level permissions. While IAM is essential for overarching security management, it does not provide the granularity needed to enforce fine-grained controls on individual S3 objects.

Amazon S3 Bucket Policies are JSON-based access policies attached directly to S3 buckets. These policies allow you to define highly specific access rules for the bucket itself and the objects within it. You can control read, write, and delete operations on individual objects or sets of objects, and you can apply conditional rules based on IP addresses, VPC endpoints, or multi-factor authentication. This capability allows developers and administrators to implement fine-grained, programmatic access control tailored to precise security requirements. Bucket policies are directly interpreted by S3, making them the most appropriate mechanism for controlling object-level access.

AWS Key Management Service (KMS) focuses on encryption and key management. KMS can enhance security by controlling who can use encryption keys to access data, including S3 objects encrypted with AWS-managed keys. While KMS provides an important layer of security, it is not an access management service in the same way as bucket policies. KMS controls the ability to decrypt or encrypt data but does not allow you to grant or restrict S3 API actions such as reading or writing an object independently of encryption.

Amazon CloudFront is a content delivery network (CDN) that accelerates content distribution. CloudFront can restrict access to content through signed URLs or signed cookies, but this functionality is geared toward delivery and caching rather than native object-level access management. It does not replace bucket policies for defining detailed permissions on specific objects in S3. Therefore, while CloudFront can complement access management, it is not sufficient for implementing fine-grained S3 access control.

The correct choice is Amazon S3 Bucket Policies because they directly support detailed access rules for both the bucket and its objects. They allow user-specific permissions, conditional rules, and the flexibility to enforce security policies at a granular level, which IAM, KMS, or CloudFront alone cannot fully achieve. Bucket policies provide native integration with S3, making them the ideal tool for fine-grained access control.

Question 42 

Which AWS service can be used to trigger workflows based on changes in data stored in S3?

A) AWS Lambda
B) AWS CloudTrail
C) AWS Step Functions
D) Amazon CloudWatch

Answer:  A) AWS Lambda

Explanation:

AWS Lambda is a serverless compute service that allows you to run code without provisioning or managing servers. Lambda functions can be triggered by a variety of events, including changes in S3 buckets. For example, you can configure a Lambda function to execute when a new object is created, deleted, or updated. This event-driven model allows automatic workflow execution, such as image resizing, data transformation, notifications, or integration with other AWS services, providing highly responsive automation.

AWS CloudTrail is a service designed for auditing and compliance. It records API calls made in your AWS account, allowing administrators to track changes and monitor access. While CloudTrail is excellent for auditing, it does not natively trigger workflows or process S3 events. It is primarily a logging tool rather than an automation or processing engine, so it is not suitable for reacting to S3 data changes in real time.

AWS Step Functions is a workflow orchestration service that allows you to coordinate multiple AWS services into serverless workflows. Step Functions is ideal for managing complex multi-step processes, handling retries, and error handling. However, it cannot directly respond to S3 events on its own. To integrate S3 with Step Functions, you would typically need an intermediary like Lambda to trigger the workflow, which adds an extra layer rather than providing native event-driven triggers.

Amazon CloudWatch primarily monitors AWS resources and applications. It collects logs, metrics, and generates alarms based on thresholds or events. While CloudWatch can track S3 metrics or invoke alarms, it does not automatically execute custom workflows in response to object changes in S3. Therefore, it cannot fully replace Lambda for event-driven processing of S3 data.

The correct answer is AWS Lambda because it directly integrates with S3 event notifications and enables serverless, automated processing. It is highly scalable, supports real-time data handling, and eliminates the need for server management, making it the ideal service for triggering workflows based on S3 changes.

Question 43 

Which AWS service provides a fully managed document database for JSON data?

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

Answer: C) Amazon DocumentDB

Explanation:

Amazon DynamoDB is a fully managed NoSQL database service optimized for key-value and document storage. While it supports storing JSON documents, it uses a proprietary data model and API rather than MongoDB’s interface. DynamoDB excels at low-latency, high-scale operations and flexible schema design, but it does not provide full MongoDB compatibility or document-centric querying features like indexing nested fields and using MongoDB drivers, which are critical for some JSON-based applications.

Amazon RDS is a relational database service that supports engines such as MySQL, PostgreSQL, SQL Server, and Oracle. RDS is ideal for structured relational data but does not natively handle JSON document queries or MongoDB-compatible operations. Although some engines like PostgreSQL have JSON column support, RDS is primarily designed for relational models, which limits its effectiveness for document-based applications that require schema flexibility and document-specific indexing.

Amazon DocumentDB is a fully managed document database service compatible with MongoDB. It is designed to store, query, and index JSON documents efficiently while handling operational tasks like backup, patching, scaling, and high availability. Developers can use familiar MongoDB drivers and tools with DocumentDB, making it seamless to migrate or build document-oriented applications. Its fully managed nature eliminates administrative overhead, allowing teams to focus on application development rather than database management.

Amazon Aurora is a relational database optimized for MySQL and PostgreSQL. It delivers high performance and availability but remains relational in design. Aurora is not intended for document-centric storage and querying, making it unsuitable for workloads that require MongoDB-style operations on JSON documents.

The correct option is Amazon DocumentDB because it provides a fully managed, MongoDB-compatible service specifically designed for JSON document storage and querying. It combines the operational simplicity of AWS-managed services with the document-oriented flexibility required for modern applications.

Question 44 

Which AWS service is used to centrally manage, rotate, and retrieve database credentials securely?

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

Answer:  A) AWS Secrets Manager

Explanation:

AWS Secrets Manager is designed for secure storage, retrieval, and automatic rotation of secrets such as database credentials, API keys, and tokens. Secrets Manager eliminates the need for hardcoding sensitive information in applications, reducing security risks. It integrates seamlessly with other AWS services and can automatically rotate credentials for supported databases, which simplifies operations and strengthens security posture.

AWS Key Management Service (KMS) is focused on encryption key management. While KMS ensures that your data can be encrypted and decrypted securely, it does not manage or rotate application credentials by itself. KMS enhances the security of secrets when combined with Secrets Manager but is not a standalone solution for credential management.

AWS Identity and Access Management (IAM) controls access to AWS resources at the user or role level. It defines who can perform which actions on specific AWS resources. While IAM policies can control access to Secrets Manager or databases, IAM is not intended for storing, retrieving, or rotating application credentials, so it cannot replace Secrets Manager for this purpose.

Amazon RDS is a relational database service that can integrate with Secrets Manager to automate credential rotation. However, RDS alone does not manage secrets; it relies on external tools like Secrets Manager for secure credential storage and rotation. RDS provides the database service but not the secure management layer for credentials.

The correct answer is AWS Secrets Manager because it offers centralized, secure storage, automatic rotation, and easy retrieval of credentials. It simplifies secret management across applications, minimizes operational overhead, and strengthens security by reducing the risk of exposure or misuse of sensitive data.

Question 45 

Which AWS service is ideal for processing high-throughput streaming data in real-time?

A) Amazon Kinesis Data Streams
B) Amazon SQS
C) Amazon SNS
D) AWS Lambda

Answer:  A) Amazon Kinesis Data Streams

Explanation:

Amazon Kinesis Data Streams is a service built specifically for ingesting and processing streaming data in real-time. It can handle large volumes of data, such as application logs, clickstreams, or IoT telemetry, with high throughput and low latency. Kinesis supports real-time analytics, enabling applications to process and respond to data as it arrives. It also integrates with other AWS services like Lambda, S3, and Redshift for downstream processing and storage.

Amazon SQS is a fully managed message queuing service used to decouple distributed systems. It ensures reliable message delivery between producers and consumers but is not optimized for continuous, high-throughput data streams. SQS is ideal for asynchronous communication but does not provide real-time streaming or analytics capabilities on large-scale data.

Amazon SNS is a pub/sub notification service that delivers messages to multiple subscribers. SNS is effective for broadcasting notifications, alerts, or updates but is not designed for handling high-throughput streams or processing each message with low latency. It lacks the continuous stream processing capabilities provided by Kinesis.

AWS Lambda is a serverless compute service capable of processing events, including streaming data from Kinesis. However, Lambda alone cannot ingest very high-throughput streams directly; it depends on services like Kinesis to provide the scalable ingestion pipeline. Lambda works best as an event handler for processing or transforming smaller workloads rather than raw large-scale streams.

The correct answer is Amazon Kinesis Data Streams because it is purpose-built for high-volume, real-time streaming data. It provides reliable, scalable ingestion, near real-time processing, and seamless integration with AWS analytics and storage services, making it the ideal choice for streaming workloads.

Question 46 

Which AWS service allows you to orchestrate multiple serverless functions into a workflow?

A) AWS Step Functions
B) AWS Lambda
C) Amazon EC2
D) AWS CodePipeline

Answer:  A) AWS Step Functions

Explanation:

AWS Step Functions is a serverless orchestration service that allows developers to coordinate multiple AWS services, particularly Lambda functions, into complex workflows. It provides a visual interface to design and execute workflows with sequential, parallel, branching, and error-handling capabilities. Step Functions is particularly useful for building applications that require multiple steps or stages, such as data processing pipelines, automated approvals, or microservice orchestration. By enabling a workflow model, developers can reduce the complexity of managing multiple interdependent functions manually and improve overall reliability.

AWS Lambda is a compute service that runs code in response to events and automatically manages compute resources. While Lambda functions can be triggered individually or chained through code, they do not inherently provide a structured way to manage a full workflow. Lambda is excellent for executing individual units of work but does not include orchestration features such as state management, retries, or branching, which are critical for complex multi-step workflows.

Amazon EC2 provides scalable virtual servers in the cloud, giving developers the flexibility to run applications on managed compute instances. However, EC2 is an infrastructure-level service and does not provide orchestration for serverless workflows. Developers would need to build their own orchestration logic when using EC2, which can introduce complexity and increase the potential for errors, particularly in highly distributed serverless architectures.

AWS CodePipeline is a continuous integration and continuous delivery (CI/CD) service that automates building, testing, and deploying code. While it orchestrates stages of software release pipelines, it is not designed to coordinate runtime serverless application workflows. CodePipeline focuses on deployment automation rather than runtime task orchestration.

Step Functions is the correct choice because it is purpose-built for orchestrating serverless workflows. It allows developers to coordinate multiple Lambda functions and AWS services in a visual and maintainable way. The service improves scalability, error handling, and maintainability by managing state transitions, retries, and branching, which would otherwise require significant custom code. For applications that involve multiple sequential or parallel processes, Step Functions provides a robust and reliable orchestration layer.

Question 47 

Which AWS service allows developers to track API calls and user activity for auditing?

A) AWS CloudTrail
B) AWS CloudWatch
C) AWS X-Ray
D) AWS Config

Answer:  A) AWS CloudTrail

Explanation:

AWS CloudTrail is a service that provides governance, compliance, and operational auditing of AWS accounts by recording API calls and user activity. Every API request made to AWS resources is logged, including the identity of the caller, the time of the call, parameters, and the response. CloudTrail logs can be used to monitor access, detect unauthorized activity, and meet regulatory compliance requirements. It provides a historical record of account activity, which is essential for auditing, forensic analysis, and security monitoring.

AWS CloudWatch focuses on monitoring metrics and operational data from AWS resources and applications. It can collect logs, create dashboards, and trigger alarms based on thresholds, but it does not specifically capture or audit API calls and user activity. CloudWatch is oriented toward operational visibility and performance management rather than compliance or auditing.

AWS X-Ray is a distributed tracing service that helps developers analyze and debug applications by visualizing request flows and latencies. While X-Ray provides deep insights into application behavior and bottlenecks, it does not provide account-level auditing of API calls or comprehensive tracking of user activity. It is focused on performance analysis rather than security or compliance logging.

AWS Config monitors resource configurations, tracks changes over time, and helps maintain compliance with policies. Although it can alert when configurations deviate from defined standards, Config does not provide a complete record of API calls or user actions across the account. It is valuable for configuration auditing but not for tracking individual API-level interactions.

CloudTrail is correct because it provides a centralized, auditable log of all API and user activity across AWS resources. It ensures visibility into actions taken in an account, which is critical for security investigations, compliance audits, and governance. By capturing who did what, when, and from where, CloudTrail gives organizations the tools to trace activity and maintain accountability across their AWS environment.

Question 48 

Which AWS service provides global content delivery and caching for applications?

A) Amazon CloudFront
B) AWS Lambda
C) Amazon S3
D) Amazon API Gateway

Answer:  A) Amazon CloudFront

Explanation:

Amazon CloudFront is a content delivery network (CDN) that distributes content globally via edge locations to reduce latency and improve the performance of applications. It caches frequently accessed content closer to end users, allowing faster delivery of both static and dynamic content. CloudFront integrates with services like Amazon S3, API Gateway, and Lambda@Edge to deliver secure and highly performant applications. Its caching and geographic distribution capabilities make it ideal for applications that need to serve content efficiently to a global audience.

AWS Lambda is a serverless compute service that executes code in response to events. Although it can perform processing tasks and integrate with other services, it does not provide global caching or content delivery. Lambda is designed for computation, not for distributing or accelerating content delivery across a global network.

Amazon S3 is an object storage service that stores data reliably at scale. While S3 can serve static content directly to users, it lacks a global network of edge locations to cache and accelerate content delivery. Using S3 alone can lead to higher latency for users far from the S3 bucket region. CloudFront complements S3 by caching content at edge locations worldwide to reduce latency and improve responsiveness.

Amazon API Gateway is a service for creating and managing APIs, allowing secure access to backend services. While it supports caching at the API level to improve performance, it is not a CDN and does not provide edge caching or global distribution of arbitrary content. API Gateway is focused on API management rather than content delivery.

CloudFront is correct because it is purpose-built for global content delivery and caching. It accelerates the distribution of web content, provides edge caching to reduce latency, and integrates seamlessly with S3 and other AWS services. By serving content closer to users and reducing the load on origin servers, CloudFront improves user experience, scalability, and reliability for applications worldwide.

Question 49 

Which service enables automatic scaling of containerized applications based on load?

A) Amazon ECS with Auto Scaling
B) AWS Lambda
C) Amazon RDS
D) Amazon S3

Answer:  A) Amazon ECS with Auto Scaling

Explanation:

Amazon ECS (Elastic Container Service) is a fully managed container orchestration service that supports running, scaling, and managing Docker containers. ECS integrates with Auto Scaling to automatically adjust the number of container instances or tasks based on predefined metrics such as CPU or memory utilization. This ensures that applications maintain performance under varying loads without manual intervention. Developers can define scaling policies that react to demand, enabling resilient, cost-efficient containerized workloads.

AWS Lambda automatically scales functions in response to incoming events, providing serverless elasticity. However, Lambda does not orchestrate containers or provide fine-grained control over containerized workloads. It is suitable for event-driven compute tasks but not for managing long-running container applications.

Amazon RDS is a managed relational database service that allows scaling of compute and storage resources. While RDS supports read replicas and automatic scaling to some extent, it is a database service, not a platform for running or scaling containers. Scaling RDS does not directly manage application workloads or containerized environments.

Amazon S3 provides scalable object storage for applications and static content. S3 does not offer compute resources or container orchestration, so it cannot automatically scale application workloads. Its role is strictly storage, making it irrelevant for container scaling.

ECS with Auto Scaling is correct because it allows containerized applications to dynamically respond to changes in demand. By scaling tasks and instances automatically, ECS ensures optimal resource utilization, performance, and cost-efficiency. It provides a managed container orchestration platform with robust scaling capabilities that Lambda, RDS, and S3 cannot offer for containerized workloads.

Question 50 

Which AWS service provides centralized logging, metrics, and alarms for applications?

A) AWS CloudWatch
B) AWS CloudTrail
C) AWS X-Ray
D) AWS Config

Answer:  A) AWS CloudWatch

Explanation:

AWS CloudWatch is a monitoring and observability service that collects metrics, logs, and events from AWS resources and applications. It provides real-time visibility into system performance, operational health, and application behavior. CloudWatch enables users to create dashboards, set alarms, and receive notifications based on thresholds or anomalies. Centralized logging and metrics aggregation allow developers and operators to identify and resolve issues quickly, improving reliability and reducing downtime.

AWS CloudTrail focuses on auditing API calls and tracking user activity for security and compliance purposes. While CloudTrail captures detailed logs of API requests and changes to AWS resources, it is not designed to aggregate application metrics or provide real-time monitoring. Its primary purpose is accountability and auditability rather than operational observability.

AWS X-Ray is a distributed tracing service that provides insights into application request flows, helping developers debug performance issues and identify bottlenecks. X-Ray traces requests through various services but does not provide comprehensive centralized logging or metric aggregation. Its focus is on performance analysis rather than broad monitoring and alerting.

AWS Config tracks resource configurations and evaluates compliance with policies. Although it can alert users to configuration changes and violations, it does not provide centralized logging of operational data or metrics for applications. Config is a compliance-focused service rather than a monitoring and alerting solution.

CloudWatch is correct because it offers centralized visibility into logs, metrics, and alarms, enabling proactive monitoring and troubleshooting. By aggregating operational data from across AWS services, CloudWatch allows teams to maintain application health, detect anomalies, and respond in real-time, making it the go-to service for monitoring and operational observability.

Question 51 

Which service enables real-time notifications to multiple subscribers?

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

Answer:  A) Amazon SNS

Explanation:

Amazon SNS, or Simple Notification Service, is designed to support a pub/sub messaging pattern. It enables messages to be pushed to multiple subscribers simultaneously through various endpoints such as email, SMS, HTTP/S, or even directly invoking Lambda functions. SNS ensures that notifications are delivered in real-time, which is crucial for event-driven architectures where multiple systems need to react immediately to the same event. It provides high reliability and scalability, making it suitable for distributed applications and large-scale systems.

Amazon SQS, or Simple Queue Service, is a fully managed message queue service. It enables asynchronous communication between distributed components, where messages are stored temporarily until they are retrieved by consumers. SQS is ideal for decoupling microservices but does not inherently push messages to multiple subscribers simultaneously. It works on a pull-based model, so consumers must poll the queue to receive messages. Therefore, it is not suitable for real-time broadcasting to multiple recipients.

AWS Lambda is a serverless compute service that executes code in response to events. While Lambda can be triggered by SNS or SQS messages, it is not a messaging service itself. Lambda’s primary function is to run code without provisioning servers, and it cannot natively broadcast messages to multiple subscribers. It is often used in conjunction with SNS to process events but does not provide the pub/sub mechanism directly.

Amazon Kinesis is designed for real-time data streaming. It collects, processes, and analyzes large volumes of streaming data such as logs, metrics, and IoT telemetry. Kinesis is optimized for high-throughput streaming analytics rather than instant notifications to multiple subscribers. It does not natively support the push-based pub/sub model, so it cannot replace SNS for real-time multi-recipient notifications.

SNS is the correct choice because it is purpose-built for delivering reliable, push-based messages to multiple subscribers in real time. It integrates seamlessly with Lambda, SQS, HTTP endpoints, and email/SMS channels, making it an ideal service for event-driven architectures where instant communication to several endpoints is required. Unlike SQS, Lambda, or Kinesis, SNS’s pub/sub model ensures notifications are distributed immediately and efficiently to all subscribers.

Question 52 

Which service allows you to manage keys and encrypt data in AWS services?

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

Answer:  A) AWS KMS

Explanation: 

AWS Key Management Service (KMS) is a centralized service that allows you to create, manage, and control encryption keys used across AWS services. It provides both symmetric and asymmetric key management, enabling developers to encrypt and decrypt data directly or via integration with services like S3, EBS, and RDS. KMS ensures that encryption keys are protected and access policies are enforceable, providing both security and compliance for sensitive data.

AWS Secrets Manager is a service for securely storing and rotating sensitive information such as passwords, API keys, or tokens. While it protects confidential data, it is not a general-purpose encryption service. Secrets Manager is more about secret lifecycle management than cryptographic key management, which makes it unsuitable for directly encrypting data at scale or across multiple AWS services.

Amazon S3 supports server-side encryption for objects stored in buckets. While S3 can encrypt data, it relies on KMS for key management when using AWS-managed keys or customer-managed keys. S3 alone does not offer the full capabilities of key lifecycle management, auditing, or policy enforcement. It is primarily a storage service, and its encryption features are dependent on integrating with KMS or providing client-side encryption.

AWS CloudTrail provides logging and auditing of API activity within an AWS account. It allows tracking of which user or service called specific APIs but does not provide key creation, management, or encryption capabilities. CloudTrail is important for compliance and monitoring, but it does not handle the core task of managing encryption keys.

KMS is the correct option because it is explicitly designed to securely manage cryptographic keys, enforce access policies, and integrate with other AWS services for data encryption. It provides centralized control, auditability, and secure storage of keys, ensuring that sensitive data is encrypted consistently across all services. Unlike Secrets Manager, S3, or CloudTrail, KMS is a purpose-built solution for encryption key management.

Question 53 

Which AWS service provides a managed message broker for applications using AMQP, MQTT, or JMS protocols?

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

Answer:  A) Amazon MQ

Explanation:

Amazon MQ is a managed message broker service that supports open-standard messaging protocols such as AMQP, MQTT, and JMS. It is designed to integrate seamlessly with existing enterprise applications that already rely on these protocols. By providing a managed broker, Amazon MQ reduces the operational overhead of maintaining message brokers, including patching, scaling, and monitoring. It is ideal for organizations migrating on-premises messaging systems to AWS or building new applications with protocol compatibility in mind.

Amazon SQS is a fully managed message queue service designed for decoupling distributed applications. SQS works with its own proprietary protocol and does not natively support AMQP, MQTT, or JMS. While it is excellent for queue-based architectures and asynchronous processing, it cannot directly serve applications that require standard messaging protocols.

Amazon SNS is a pub/sub service that allows broadcasting messages to multiple subscribers, including Lambda functions, HTTP endpoints, and email. SNS does not provide traditional message broker capabilities or support standard messaging protocols. It is optimized for push notifications rather than enterprise message integration.

AWS Lambda is a serverless compute service that runs code in response to events but cannot act as a message broker. Lambda functions can process messages delivered by SQS, SNS, or Amazon MQ but do not themselves provide broker capabilities or protocol support.

Amazon MQ is correct because it offers a fully managed message broker that supports standard protocols, ensuring compatibility with existing enterprise applications. Unlike SQS, SNS, or Lambda, Amazon MQ allows developers to migrate traditional messaging workloads to the cloud without rewriting application logic, providing a familiar, scalable, and reliable messaging environment.

Question 54 

Which service allows you to store key-value pairs for fast, low-latency access?

A) Amazon DynamoDB
B) Amazon RDS
C) Amazon S3
D) Amazon ElastiCache

Answer:  A) Amazon DynamoDB

Explanation:

Amazon DynamoDB is a fully managed NoSQL database optimized for key-value and document storage. It provides single-digit millisecond latency at any scale, making it ideal for applications that require extremely fast read and write operations. DynamoDB automatically handles scaling, replication, and backup, allowing developers to focus on application logic rather than database maintenance.

Amazon RDS is a managed relational database service supporting SQL databases such as MySQL, PostgreSQL, and Oracle. While RDS ensures data integrity and complex querying capabilities, relational databases are generally slower than DynamoDB for simple key-value access. The overhead of SQL queries and table joins can increase latency compared to a NoSQL key-value store.

Amazon S3 is an object storage service designed for storing files and unstructured data. S3 provides high durability but is not optimized for low-latency key-value lookups. Retrieving a single object from S3 involves network requests and HTTP calls, which cannot compete with the millisecond response times of DynamoDB.

Amazon ElastiCache is an in-memory caching service supporting Redis or Memcached. It delivers very fast data retrieval but is intended as a temporary cache rather than a persistent database. While it accelerates performance when used with databases, it does not provide the same durability and scalability guarantees as DynamoDB.

DynamoDB is correct because it combines the benefits of a fully managed, persistent NoSQL database with the ability to handle massive scale and extremely low-latency key-value access. Unlike RDS, S3, or ElastiCache, DynamoDB provides both fast access and persistent storage, making it suitable for applications such as gaming leaderboards, session stores, or real-time analytics.

Question 55 

Which AWS service enables developers to deploy RESTful APIs securely at scale?

A) Amazon API Gateway
B) AWS Lambda
C) Amazon EC2
D) Amazon CloudFront

Answer:  A) Amazon API Gateway

Explanation:

Amazon API Gateway is a fully managed service for creating, deploying, and managing RESTful and WebSocket APIs. It allows developers to implement features like authorization, throttling, caching, and monitoring without managing underlying servers. API Gateway integrates natively with Lambda for serverless architectures and with other AWS services for authentication and data access, providing a scalable and secure API platform.

AWS Lambda is a serverless compute service that executes code in response to events, including API requests. Lambda can serve as the backend for APIs but does not handle API endpoint management, throttling, or authentication by itself. Lambda works in conjunction with API Gateway to provide a complete API solution but cannot replace Gateway’s management features.

Amazon EC2 can host APIs by deploying web servers and backend applications. While EC2 provides full control over the server environment, developers must manually configure scaling, security, load balancing, and monitoring. This approach is less efficient for serverless or highly elastic applications compared to API Gateway.

Amazon CloudFront is a content delivery network that accelerates static and dynamic content delivery to users worldwide. While CloudFront improves API performance by caching responses closer to clients, it does not provide API creation, deployment, or security features. It is complementary to API Gateway but cannot replace its functionality.

API Gateway is correct because it provides a fully managed, scalable, and secure environment to deploy RESTful APIs at scale. Unlike Lambda, EC2, or CloudFront, it handles endpoint management, authentication, throttling, and monitoring, allowing developers to focus on API logic rather than infrastructure management. Its integration with serverless backends and security mechanisms makes it ideal for modern application architectures.

Question 56 

Which AWS service enables developers to deploy serverless functions triggered by various events?

A) AWS Lambda
B) Amazon EC2
C) AWS Step Functions
D) Amazon S3

Answer:  A) AWS Lambda

Explanation:

AWS Lambda is a serverless compute service that allows developers to run code in response to events without provisioning or managing servers. It can be triggered by a wide variety of AWS services such as S3, DynamoDB, CloudWatch Events, and API Gateway. Lambda automatically scales with the number of incoming events, ensuring that applications remain responsive even under variable loads. Developers only pay for the compute time used while the code executes, making it highly cost-efficient. The serverless nature of Lambda also reduces operational overhead because AWS handles the underlying infrastructure, patching, and scaling automatically.

Amazon EC2 provides virtual servers in the cloud, offering flexible compute capacity for running applications. Unlike Lambda, EC2 requires developers to manage the instances, including operating system updates, scaling, load balancing, and resource provisioning. While EC2 can host applications that respond to events, it does not inherently provide the event-driven, serverless capabilities that Lambda offers. EC2 is ideal for traditional or long-running applications where full control over the server environment is needed, but it lacks the simplicity and automatic scaling of serverless functions.

AWS Step Functions is a service designed for orchestrating workflows and managing task execution sequences. It coordinates multiple AWS services or Lambda functions in a defined order, allowing developers to build complex workflows with conditional logic, retries, and error handling. Step Functions itself does not execute code independently but relies on services like Lambda to perform actions. While it is complementary to Lambda in building event-driven applications, it is not a substitute for running serverless code directly in response to events.

Amazon S3 is an object storage service that enables developers to store and retrieve large amounts of data with high durability. S3 can trigger events such as object creation or deletion, but it does not execute custom code by itself. It is primarily a storage solution rather than a compute service. Developers often combine S3 with Lambda to respond to storage events, enabling workflows like image processing or automated backups. Lambda is the correct choice for event-driven compute because it runs code automatically in response to events from multiple AWS services, scales automatically, and eliminates the need to manage servers or infrastructure.

Question 57 

Which AWS service allows developers to orchestrate batch and sequential tasks for serverless applications?

A) AWS Step Functions
B) AWS Lambda
C) Amazon EC2
D) Amazon S3

Answer:  A) AWS Step Functions

Explanation:

AWS Step Functions is a fully managed service that enables developers to coordinate workflows of multiple tasks across AWS services. It allows for sequential, parallel, and conditional execution, supporting complex business logic. Developers can visualize workflows through state machines, which improve readability, maintainability, and error handling. Step Functions can also handle retries, failures, and branching, making serverless applications more reliable and resilient. By managing the orchestration, it reduces the need for custom code to control task execution order, timing, and dependencies.

AWS Lambda, while a serverless compute service, executes individual functions triggered by events. Lambda is excellent for handling event-driven workloads but does not provide a native way to sequence or coordinate multiple steps in a workflow. When multiple Lambda functions need to run in a specific order or with error handling, Step Functions becomes necessary to orchestrate them effectively.

Amazon EC2 offers flexible compute resources for running applications but does not provide workflow orchestration. Developers would need to manually implement scheduling, task execution, and error handling on EC2 instances. EC2 is better suited for long-running processes or traditional server-based applications but lacks the serverless orchestration capabilities of Step Functions.

Amazon S3 is an object storage service and does not offer any workflow orchestration capabilities. While it can trigger events, it cannot manage sequential or batch processing tasks on its own. Step Functions is the correct choice for orchestrating serverless workflows because it provides a visual interface, built-in error handling, and coordination of multiple AWS services, enabling developers to create complex, reliable, and scalable serverless applications without managing servers.

Question 58 

Which AWS service allows developers to securely store and rotate API keys and credentials?

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

Answer:  A) AWS Secrets Manager

Explanation:

AWS Secrets Manager is a service specifically designed for securely storing, retrieving, and rotating secrets such as API keys, database credentials, and other sensitive information. It provides automatic rotation capabilities, ensuring that secrets are regularly updated without manual intervention. Secrets Manager integrates with AWS services such as RDS, Redshift, and Lambda, and includes auditing features through CloudTrail. This centralized approach reduces security risks and simplifies credential management for developers and applications.

AWS KMS (Key Management Service) is primarily focused on managing encryption keys used to secure data. While KMS ensures that secrets can be encrypted, it does not store or rotate the actual credentials themselves. KMS is often used in conjunction with Secrets Manager to encrypt stored secrets securely.

AWS IAM (Identity and Access Management) controls permissions for users, roles, and services, determining who can access AWS resources. IAM does not function as a secure storage solution for secrets; instead, it defines and enforces access policies. Developers rely on IAM for authorization but still need a service like Secrets Manager to manage secret storage and rotation.

Amazon RDS is a managed relational database service. While it requires credentials for database access, it does not provide a dedicated mechanism for storing and rotating those credentials. Developers often use Secrets Manager to automatically rotate RDS credentials. Secrets Manager is the correct choice because it centralizes secret management, automates rotation, and integrates with multiple AWS services, ensuring secure, auditable handling of sensitive information.

Question 59 

Which AWS service allows real-time analysis of streaming data for analytics?

A) Amazon Kinesis Data Analytics
B) Amazon SQS
C) Amazon SNS
D) AWS Lambda

Answer:  A) Amazon Kinesis Data Analytics

Explanation:

Amazon Kinesis Data Analytics allows developers to process and analyze streaming data in real time using standard SQL queries. It can ingest data from Kinesis Data Streams or Firehose, perform transformations and aggregations, and output processed results to multiple destinations such as S3, Redshift, or Lambda. This capability enables immediate insights from incoming data, supporting applications like fraud detection, IoT telemetry analysis, and log processing. Kinesis Data Analytics is fully managed and scalable, so developers can focus on data processing logic rather than managing infrastructure.

Amazon SQS is a message queuing service that temporarily stores messages to decouple components of distributed systems. SQS ensures reliable message delivery but does not provide analytics or processing capabilities for streaming data. Its role is strictly queuing, not real-time data analysis.

Amazon SNS is a pub/sub messaging service that delivers messages to multiple subscribers in real time. While SNS supports notifications and message distribution, it does not natively perform analytics on streaming data. SNS is complementary to analytics pipelines, often feeding data into Kinesis or Lambda for processing.

AWS Lambda can process individual events in real time but does not provide built-in SQL-based analytics for streams. It is ideal for lightweight, event-driven processing but lacks the structured stream analytics capabilities of Kinesis Data Analytics. Kinesis Data Analytics is the correct service for real-time streaming data analysis because it combines scalability, managed infrastructure, and SQL-based processing to extract insights from live data streams efficiently.

Question 60 

Which AWS service is designed to provide a serverless event bus for routing events between applications?

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

Answer:  A) Amazon EventBridge

Explanation:

Amazon EventBridge is a serverless event bus that allows applications to route events from AWS services, SaaS applications, or custom sources to various targets like Lambda, SQS, or Kinesis. EventBridge supports advanced filtering, transformation, and routing rules, enabling developers to build complex, event-driven architectures. Its serverless nature means it automatically scales and removes the need to manage infrastructure. EventBridge simplifies integration between applications and services, providing a centralized mechanism for event delivery and routing.

Amazon SNS is a pub/sub messaging service focused on sending notifications to multiple subscribers. While SNS can deliver messages in real time, it does not offer advanced event routing, filtering, or transformation capabilities. It is mainly used for alerting and notification purposes rather than complex event-driven architecture.

Amazon SQS is a queue service that decouples system components and ensures reliable message delivery. SQS does not natively handle event routing or support multiple sources with sophisticated filtering or transformation rules. It is designed for asynchronous communication between services rather than event bus functionality.

AWS Lambda executes code in response to events but does not provide event bus functionality. It is often used as a target for EventBridge or SNS events rather than as a mechanism for routing or filtering events itself. EventBridge is the correct choice because it enables serverless, scalable event routing with advanced capabilities, supporting multiple sources and destinations to implement robust event-driven architectures.