Amazon AWS Certified DevOps Engineer — Professional DOP-C02 Exam Dumps and Practice Test Questions Set 8 Q106-120
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Question 106
A company is migrating a legacy application to AWS and wants to implement a CI/CD pipeline that builds, tests, and deploys containerized microservices on Amazon ECS. They need full integration with Git repositories, automated builds, artifact storage, and deployment triggers. Which combination of AWS services best meets these requirements?
A) AWS CodePipeline + AWS CodeBuild + Amazon ECR
B) AWS CloudFormation + Amazon S3
C) AWS Lambda + API Gateway
D) AWS Config + Systems Manager
Answer: A) AWS CodePipeline + AWS CodeBuild + Amazon ECR
Explanation:
AWS CodePipeline is a fully managed continuous integration and continuous delivery service that automates the build, test, and deployment phases for application releases. CodePipeline integrates natively with Git repositories, including AWS CodeCommit, GitHub, and Bitbucket. Whenever a developer commits code to the repository, CodePipeline can automatically trigger a pipeline execution. Pipelines are composed of stages such as source, build, test, and deploy, allowing end-to-end automation of application deployment workflows.
AWS CodeBuild is a fully managed build service that compiles source code, runs unit tests, and produces build artifacts. CodeBuild scales automatically, running multiple builds concurrently without the need to provision or manage build servers. Integration with CodePipeline allows CodeBuild to execute automatically whenever changes are detected in the source repository. This ensures consistent and repeatable builds, enforces testing procedures, and helps maintain code quality.
Amazon ECR (Elastic Container Registry) provides a secure, scalable container registry for storing Docker images. CodeBuild can build container images and push them directly to ECR. ECS can then pull these images for deployment, enabling seamless container-based CI/CD workflows. This integration ensures that all microservices are deployed using tested, versioned, and secured container images. ECR also supports image scanning, which adds an additional layer of security to the pipeline.
AWS CloudFormation combined with S3 primarily supports infrastructure provisioning. CloudFormation templates can define ECS clusters and services, and S3 can store artifacts or templates. However, this combination does not automate CI/CD workflows, build processes, or code testing. It is focused on infrastructure-as-code rather than full application deployment pipelines.
AWS Lambda and API Gateway provide serverless compute and API endpoints. While useful for certain application architectures, they do not provide CI/CD pipeline capabilities, artifact management, or automated container deployment.
AWS Config with Systems Manager focuses on compliance, configuration monitoring, and automated remediation. While they provide governance for resources, they do not integrate with Git repositories, perform builds, or deploy containerized applications.
By combining CodePipeline, CodeBuild, and ECR, the company gains a fully automated, end-to-end CI/CD pipeline for containerized microservices. It enables developers to push code changes, automatically build and test images, store artifacts securely, and deploy consistently to ECS. This approach reduces manual intervention, increases development speed, enforces quality, and integrates tightly with AWS services, making it the correct solution.
Question 107
A global e-commerce company needs to distribute static website content with low latency and high availability across multiple regions. They also need SSL termination, caching, and protection against DDoS attacks. Which combination of services should they use?
A) Amazon CloudFront + S3 + AWS WAF
B) Amazon Route 53 + EC2
C) AWS Lambda + DynamoDB
D) Amazon RDS + QuickSight
Answer: A) Amazon CloudFront + S3 + AWS WAF
Explanation:
Amazon CloudFront is a content delivery network (CDN) that caches static content at edge locations worldwide. By distributing content closer to end users, CloudFront reduces latency, improves load times, and enhances overall user experience. For a static website, the origin can be an S3 bucket configured as a website endpoint. CloudFront fetches content from S3 and caches it at edge locations, providing high availability even if the origin is temporarily unavailable.
S3 provides highly durable and scalable object storage. Static website assets such as HTML, CSS, JavaScript, and images are stored in S3. S3 ensures data durability, redundancy across availability zones, and automatic scaling to handle variable traffic volumes. Integration with CloudFront enables edge caching, reducing load on the origin and providing low-latency delivery worldwide.
AWS WAF (Web Application Firewall) provides protection against common web exploits and distributed denial-of-service (DDoS) attacks. WAF integrates with CloudFront to inspect HTTP/S requests at the edge before they reach the origin. Rules can be configured to block malicious traffic, restrict access based on IP addresses, or enforce rate limits. This combination ensures both content performance and security for global static website distribution.
Amazon Route 53 is a DNS service that can provide latency-based routing, but it does not provide caching, SSL termination, or edge protection. EC2 provides compute but is not required for serving static content.
AWS Lambda and DynamoDB are used for serverless compute and NoSQL data storage. They are not necessary for static website distribution and do not provide CDN functionality or edge caching.
Amazon RDS with QuickSight is for relational database storage and business intelligence visualization. They are not applicable for static website content delivery, caching, or DDoS protection.
By combining CloudFront, S3, and AWS WAF, the company can deliver a fast, reliable, and secure static website experience worldwide. CloudFront ensures low latency, S3 provides durable storage, and WAF protects against attacks. SSL termination at CloudFront ensures secure HTTPS connections without requiring complex configurations at the origin. This integrated solution meets all the requirements, making it the correct answer.
Question 108
A company uses Amazon VPC to host applications across multiple private subnets. They need a solution to enable centralized logging of all VPC traffic, analyze network flows, and detect anomalies or unauthorized access attempts. Which combination of AWS services should they use?
A) VPC Flow Logs + Amazon S3 + Amazon Athena + CloudWatch
B) AWS Config + Lambda
C) Amazon RDS + CloudFront
D) AWS Backup + SNS
Answer: A) VPC Flow Logs + Amazon S3 + Amazon Athena + CloudWatch
Explanation:
VPC Flow Logs capture IP traffic going to and from network interfaces within a VPC. They record metadata such as source and destination IP addresses, ports, protocols, bytes transferred, and whether traffic was accepted or rejected by security groups or network ACLs. Flow logs provide a comprehensive view of network activity, enabling teams to detect anomalous patterns or unauthorized access attempts. Flow logs can be configured at the VPC, subnet, or network interface level, providing granular monitoring for all network traffic within the environment.
Amazon S3 is a cost-effective, durable storage service that stores VPC Flow Logs over long periods. Storing logs in S3 allows for historical analysis, compliance retention, and integration with analytics tools. Logs are written in structured formats such as JSON or Parquet, facilitating automated processing and querying.
Amazon Athena is a serverless query service that allows teams to analyze S3-stored flow logs using standard SQL syntax. Analysts can identify trends, aggregate metrics, and search for unusual access patterns without setting up servers or databases. Athena’s serverless nature ensures scalability and cost efficiency, as it queries only the data required.
CloudWatch complements this solution by monitoring logs and metrics in real time. CloudWatch Alarms can be configured to alert teams on anomalous network behavior detected from flow log metrics. Integration with EventBridge allows automated responses to security events, such as isolating compromised instances or updating security groups.
AWS Config with Lambda focuses on configuration compliance and remediation. While useful for governance, it does not provide centralized network traffic logging or near real-time analytics for anomaly detection.
Amazon RDS and CloudFront serve database and content delivery use cases. They do not capture network flows or provide visibility into private VPC traffic.
AWS Backup with SNS is for data protection and notifications. It does not capture network traffic or enable analysis of VPC logs.
By combining VPC Flow Logs, S3, Athena, and CloudWatch, the company gains comprehensive visibility into all network traffic, the ability to query logs efficiently, detect anomalies, and automate responses to unauthorized access attempts. This approach is fully serverless, scalable, and provides centralized network observability, making it the correct solution.
Question 109
A company uses Amazon ECS with Fargate to run multiple microservices. They need to ensure that every container image is scanned for vulnerabilities before deployment and that noncompliant images are blocked automatically. Which combination of AWS services provides this capability?
A) Amazon ECR image scanning + AWS CodePipeline
B) AWS Config + Lambda
C) Amazon S3 + Athena
D) AWS CloudTrail + CloudWatch
Answer: A) Amazon ECR image scanning + AWS CodePipeline
Explanation:
Amazon Elastic Container Registry (ECR) provides a fully managed container image registry with the ability to scan images for vulnerabilities using Amazon Inspector’s vulnerability database. Enhanced image scanning detects known software vulnerabilities within all layers of a container image, producing detailed findings with severity ratings and remediation recommendations. By enabling image scanning on push or periodically, organizations can maintain security hygiene for container images.
AWS CodePipeline is a continuous integration and continuous delivery (CI/CD) service that automates build, test, and deployment processes. By integrating ECR image scanning with CodePipeline, organizations can enforce a policy that blocks deployment of images with critical or high-severity vulnerabilities. During the pipeline execution, CodePipeline can retrieve scan findings from ECR, evaluate compliance against predefined policies, and prevent noncompliant images from progressing to staging or production environments.
This combination provides end-to-end automation: developers push code changes or images, the pipeline builds the image, ECR performs vulnerability scanning, and CodePipeline enforces compliance gates before deployment. It ensures that only secure, tested container images are deployed to ECS Fargate, reducing operational risk and improving security posture.
AWS Config with Lambda focuses on infrastructure compliance and remediation. While it can detect configuration drift or noncompliant AWS resources, it does not natively scan container images or integrate with CI/CD pipelines to enforce deployment gates.
Amazon S3 with Athena provides storage and analytics capabilities but cannot perform vulnerability scanning of container images or enforce deployment compliance. S3 is suitable for artifact storage, and Athena allows query of stored datasets, but they do not provide automated security enforcement for ECS container deployments.
AWS CloudTrail with CloudWatch provides auditing, logging, and alerting capabilities. CloudTrail records API activity, and CloudWatch monitors resource metrics, but neither service scans container images or blocks deployment of noncompliant images automatically.
By combining ECR image scanning with CodePipeline, the company achieves fully automated, scalable, and enforceable container security. This ensures operational efficiency, regulatory compliance, and a reduced risk of deploying vulnerable images, making it the correct solution.
Question 110
A company runs multiple Lambda functions processing real-time events. They want to detect anomalies in function invocation metrics, automatically alert the team, and trigger remediation workflows when thresholds are breached. Which combination of services should they use?
A) CloudWatch metrics + CloudWatch Anomaly Detection + EventBridge
B) S3 + Athena
C) RDS + QuickSight
D) AWS Config + Systems Manager
Answer: A) CloudWatch metrics + CloudWatch Anomaly Detection + EventBridge
Explanation:
Amazon CloudWatch collects metrics for AWS Lambda functions, including invocation count, duration, error rates, throttles, and concurrency usage. By aggregating these metrics, CloudWatch provides visibility into the operational performance and health of serverless applications. Teams can monitor trends, identify anomalies, and define alarms based on static thresholds or expected patterns.
CloudWatch Anomaly Detection uses machine learning to continuously model normal behavior for Lambda metrics. It adapts to fluctuations in traffic or usage patterns, reducing false positives that occur with static thresholds. When metrics deviate significantly from expected behavior, Anomaly Detection triggers an alarm. For example, an unexpected spike in error rate, unusually long execution durations, or sudden throttling events can be detected automatically.
EventBridge integrates with CloudWatch to automate responses. When an anomaly is detected, EventBridge can trigger Lambda functions, Systems Manager Automation workflows, or SNS notifications. These automated actions can perform remediation such as restarting functions, invoking retries, updating configuration, or alerting the development team. This approach ensures rapid incident response, minimizes downtime, and reduces manual operational burden.
S3 and Athena provide storage and query capabilities but are unsuitable for real-time monitoring or automated anomaly detection. Logs must be written to S3 and queried manually, which cannot meet operational requirements for real-time Lambda metrics monitoring.
RDS with QuickSight supports relational data storage and visualization but does not provide operational metric collection, anomaly detection, or automated remediation for Lambda functions.
AWS Config and Systems Manager monitor resource configuration compliance and automate remediation for misconfigured resources. They do not collect runtime Lambda metrics or detect anomalies in invocation patterns.
By combining CloudWatch metrics, Anomaly Detection, and EventBridge, the company achieves real-time observability, automated anomaly detection, and immediate operational responses. This solution is fully managed, scalable, and minimizes operational overhead, making it the correct choice.
Question 111
A company runs a global web application and wants to ensure users are routed to the lowest-latency AWS region. They also need automated failover in case of regional outages and health monitoring of endpoints. Which AWS service combination should they implement?
A) Route 53 latency-based routing + health checks + CloudWatch
B) CloudFront + S3
C) Direct Connect + VPC Peering
D) Lambda + DynamoDB
Answer: A) Route 53 latency-based routing + health checks + CloudWatch
Explanation:
Amazon Route 53 provides latency-based routing to direct users to the AWS region with the lowest network latency. Multiple endpoints across different regions can be configured, ensuring optimal performance and minimal response times for global users. Latency-based routing evaluates user request origin against available endpoints and routes traffic to the fastest one.
Health checks integrated with Route 53 continuously monitor the availability and performance of endpoints. If a regional endpoint fails or experiences degraded performance, Route 53 automatically reroutes traffic to healthy regions. This provides automated failover, enhancing application availability and reducing downtime for users.
CloudWatch complements this solution by monitoring endpoint health and operational metrics in real time. CloudWatch alarms notify teams when endpoints become unhealthy or exhibit unusual latency. Integration with EventBridge enables automated incident response workflows, such as notifying support teams, scaling resources, or triggering remediations. CloudWatch dashboards provide visual insights into traffic distribution, latency trends, and regional performance metrics.
CloudFront with S3 provides content delivery acceleration and edge caching but does not provide DNS-based latency routing or health-based failover. CloudFront is optimized for content delivery, not global routing decisions based on latency.
Direct Connect with VPC Peering provides private connectivity between data centers and VPCs. While it improves network performance for specific workloads, it does not automatically route user traffic globally or monitor endpoint health for failover purposes.
Lambda with DynamoDB is used for serverless compute and NoSQL data storage. While it can process data and store state, it does not provide global traffic routing, latency evaluation, or automated failover.
The combination of Route 53 latency-based routing, health checks, and CloudWatch provides automated, low-latency global traffic routing with high availability. Users are directed to the fastest and healthiest region, endpoints are continuously monitored, and alerts are generated for anomalies. This fully managed, integrated solution meets all operational, performance, and reliability requirements, making it the correct answer.
Question 112
A company uses Amazon ECS with Fargate to run multiple microservices. They want to enforce that only approved container images are deployed, block images with vulnerabilities, and automatically alert teams when a policy violation occurs. Which combination of AWS services is best suited for this requirement?
A) Amazon ECR image scanning + AWS CodePipeline + SNS
B) AWS Config + CloudTrail
C) Amazon S3 + Athena
D) AWS Backup + Lambda
Answer: A) Amazon ECR image scanning + AWS CodePipeline + SNS
Explanation:
Amazon Elastic Container Registry (ECR) provides image scanning capabilities to detect vulnerabilities in container images. Enhanced scanning, powered by Amazon Inspector, identifies security issues in all layers of a container and assigns severity levels. By enabling scan-on-push, images are analyzed immediately after they are uploaded, ensuring early detection of potential threats. Findings include detailed information about affected packages and recommended actions for remediation. This helps prevent deployment of vulnerable or noncompliant images.
AWS CodePipeline can integrate with ECR to create automated CI/CD pipelines that include validation gates. When a container image is scanned and found to contain critical or high-severity vulnerabilities, CodePipeline can halt the deployment automatically. This ensures that only approved, secure images are deployed to ECS Fargate. Pipelines can also include additional stages for building, testing, and approving images, providing end-to-end control over the deployment process.
Amazon SNS (Simple Notification Service) provides real-time notifications to development or operations teams when policy violations are detected. Integration with CodePipeline or ECR scan findings allows instant alerts via email, SMS, or other endpoints. Teams are informed of security risks and can take immediate action to remediate vulnerabilities, reducing operational risk and enhancing compliance.
AWS Config combined with CloudTrail provides configuration compliance and audit logging. Config evaluates resource settings against predefined rules, and CloudTrail records API calls. While useful for tracking changes and auditing activity, they do not scan container images, enforce deployment policies, or automatically block noncompliant images, making them unsuitable for this use case.
Amazon S3 with Athena provides data storage and query capabilities. It can store logs or container metadata but does not perform vulnerability scanning or integrate with CI/CD pipelines to enforce deployment compliance. Athena is limited to querying stored data, not enforcing automated policy gates.
AWS Backup with Lambda ensures backups and recovery, but it does not scan container images, enforce security policies, or provide notifications for noncompliant deployments. Backup workflows focus on data protection rather than operational security for containerized applications.
By combining ECR image scanning, CodePipeline, and SNS, organizations gain a fully automated solution for ensuring secure container deployments. Images are scanned immediately, deployment gates prevent noncompliant images from reaching production, and teams are notified instantly. This approach provides end-to-end security enforcement, automated governance, and operational visibility, making it the correct solution.
Question 113
A company is using AWS Lambda functions triggered by SQS queues. They want to centralize logging, detect anomalies in invocation patterns, and automatically alert the operations team when error rates exceed normal thresholds. Which combination of AWS services should they implement?
A) CloudWatch Logs + CloudWatch Anomaly Detection + EventBridge
B) Amazon S3 + Athena
C) AWS Config + Systems Manager
D) Amazon RDS + QuickSight
Answer: A) CloudWatch Logs + CloudWatch Anomaly Detection + EventBridge
Explanation:
CloudWatch Logs collects log data from AWS Lambda functions automatically. Each function can be configured to stream logs to CloudWatch, providing centralized visibility into errors, performance metrics, and invocation patterns. This centralized logging enables DevOps teams to quickly identify issues and analyze trends without managing separate logging infrastructure. Logs include timestamps, request IDs, and error details, which are critical for debugging and operational analysis.
CloudWatch Anomaly Detection applies machine learning to Lambda metrics and log-derived metrics. It creates a dynamic model of expected behavior based on historical patterns, enabling detection of anomalies such as spikes in error rates, unusual invocation volumes, or unexpected latencies. This approach reduces false positives compared to static thresholds and provides early warning of potential operational problems. For example, a sudden surge in failed invocations triggered by SQS messages can be detected automatically.
EventBridge integrates seamlessly with CloudWatch alarms and Anomaly Detection. When an anomaly is detected, EventBridge can trigger automated workflows such as invoking a Lambda remediation function, sending alerts via SNS, or logging the event to a central dashboard. This ensures that operations teams are notified in real time and can respond quickly to incidents, minimizing downtime or service degradation.
Amazon S3 combined with Athena can store logs and run queries for analysis, but this approach is not real-time. It requires manual querying or scheduled batch processes, which delays detection of operational anomalies. S3 and Athena do not provide automated alerts or integration with event-driven workflows.
AWS Config with Systems Manager focuses on infrastructure compliance and configuration management. While it can detect drift or enforce compliance, it does not monitor runtime Lambda function metrics, detect anomalies, or alert operations teams about unexpected behavior in real time.
Amazon RDS with QuickSight allows storage of structured data and visualization, but it does not collect or analyze Lambda function logs in real time. QuickSight is suitable for dashboards and analytics, but it does not provide anomaly detection or automated operational workflows for serverless applications.
By combining CloudWatch Logs, CloudWatch Anomaly Detection, and EventBridge, organizations gain centralized logging, dynamic anomaly detection, and automated operational response. This approach ensures proactive monitoring, rapid detection of issues, and real-time notifications, providing full observability and operational control for Lambda applications triggered by SQS. This combination meets all requirements, making it the correct solution.
Question 114
A company operates a global API and wants to ensure requests are routed to the lowest-latency AWS region, with automatic failover if an endpoint becomes unhealthy. They also require real-time monitoring of endpoint health and traffic patterns. Which AWS service combination should they use?
A) Route 53 latency-based routing + health checks + CloudWatch
B) CloudFront + S3
C) Direct Connect + VPC Peering
D) Lambda + DynamoDB
Answer: A) Route 53 latency-based routing + health checks + CloudWatch
Explanation:
Amazon Route 53 provides latency-based routing, enabling traffic to be directed to the AWS region with the lowest latency for a given user. By configuring multiple endpoints across regions, Route 53 evaluates request origins and routes users to the endpoint with optimal response time. This ensures that global users experience minimal latency and improved performance.
Health checks in Route 53 continuously monitor endpoint availability and responsiveness. If an endpoint becomes unavailable or fails to meet performance thresholds, Route 53 automatically reroutes traffic to a healthy endpoint. This failover mechanism enhances global application availability and ensures continuity of service without manual intervention. Health checks can monitor HTTP/S endpoints, TCP ports, or even specific application-level response codes.
CloudWatch complements Route 53 by providing real-time monitoring of endpoint performance and operational metrics. Metrics such as latency, error rates, and request counts are captured and displayed in dashboards for visibility. Alarms can be configured to notify teams when endpoints become unhealthy or exhibit abnormal behavior. Integration with EventBridge allows automated workflows to respond to incidents, such as alerting on-call engineers or initiating remediation procedures.
CloudFront with S3 provides edge caching and content delivery acceleration, but it does not provide DNS-based latency routing or automated health-based failover across regions. While CloudFront improves performance for static content, it does not handle global API traffic routing decisions based on latency.
Direct Connect with VPC Peering provides private network connectivity and optimized routing between VPCs. However, it does not manage global traffic routing for users or provide endpoint health monitoring and failover capabilities.
Lambda with DynamoDB is used for serverless compute and NoSQL data storage. While it can process API requests or maintain state, it does not provide global DNS routing, latency optimization, or automated failover for endpoints.
Combining Route 53 latency-based routing with health checks and CloudWatch delivers a fully managed, global solution for low-latency traffic routing, automated failover, and real-time monitoring. Users are directed to the fastest healthy region, endpoints are continuously evaluated, and operational insights are available in dashboards. This approach provides performance, availability, and observability for global APIs, making it the correct solution.
Question 115
A company runs multiple containerized applications on Amazon ECS with Fargate. They want to automatically detect when tasks exceed CPU or memory limits, trigger alerts, and scale the service dynamically. Which combination of AWS services best meets these requirements?
A) CloudWatch metrics + ECS Service Auto Scaling
B) AWS Config + Lambda
C) S3 + Athena
D) AWS Backup + SNS
Answer: A) CloudWatch metrics + ECS Service Auto Scaling
Explanation:
Amazon CloudWatch provides monitoring for ECS Fargate tasks and services. It collects metrics such as CPU utilization, memory usage, running task counts, and service health. By analyzing these metrics, teams can identify when containers are exceeding allocated resources, which may lead to degraded performance or throttling. CloudWatch alarms can be configured to trigger notifications when thresholds are breached. For example, if CPU utilization exceeds 80% over a sustained period, an alarm can indicate that the service may require scaling. Memory metrics provide similar visibility into resource saturation.
ECS Service Auto Scaling integrates with CloudWatch metrics to automatically adjust the number of running tasks. Auto Scaling policies define conditions for scaling in or out based on resource utilization, ensuring that the application maintains performance while optimizing costs. For example, when CPU utilization is consistently high, additional tasks can be launched to handle increased load. Conversely, during periods of low demand, tasks can be terminated to reduce operational expenses. This automated approach eliminates the need for manual intervention and ensures that applications remain responsive under varying workloads.
AWS Config with Lambda provides compliance monitoring and automated remediation for infrastructure configuration. While useful for detecting configuration drift, it does not monitor runtime metrics or dynamically scale containerized services based on CPU or memory utilization.
S3 with Athena enables storage and querying of structured data but does not provide real-time performance monitoring or scaling capabilities for ECS workloads. Logs can be stored in S3 and queried using Athena, but this approach introduces latency and does not allow automated task scaling.
AWS Backup with SNS focuses on data protection and alerting. Backup ensures recoverability of resources, and SNS can send notifications about backup status. However, these services do not monitor ECS metrics or trigger automatic scaling actions based on utilization.
By combining CloudWatch metrics with ECS Service Auto Scaling, the company gains a fully automated solution for monitoring and scaling containerized applications. CloudWatch ensures visibility into resource usage, and Auto Scaling adjusts task counts dynamically, maintaining performance and availability. This approach provides operational efficiency, cost optimization, and reliability, making it the correct solution.
Question 116
A company runs a global API and wants to route users to the lowest-latency AWS region. They also require automatic failover if an endpoint becomes unhealthy and real-time monitoring of endpoint performance. Which AWS service combination should they implement?
A) Route 53 latency-based routing + health checks + CloudWatch
B) CloudFront + S3
C) Direct Connect + VPC Peering
D) Lambda + DynamoDB
Answer: A) Route 53 latency-based routing + health checks + CloudWatch
Explanation:
Amazon Route 53 provides latency-based routing to direct users to the region that offers the lowest network latency. Multiple endpoints can be configured across AWS regions, and Route 53 evaluates user request origins to select the endpoint with optimal performance. This ensures that global users experience minimal response times and improved application performance.
Health checks in Route 53 continuously monitor endpoint availability and responsiveness. If an endpoint fails or its performance degrades below defined thresholds, Route 53 automatically reroutes traffic to healthy endpoints. This failover mechanism improves global availability and ensures continuity of service without manual intervention. Health checks can monitor HTTP/S responses, TCP ports, or specific application-level status codes.
CloudWatch provides real-time monitoring of endpoints and operational metrics. Metrics such as latency, error rates, and request counts can be visualized on dashboards. Alarms notify operations teams when endpoints become unhealthy or exhibit abnormal behavior. Integration with EventBridge allows automated workflows, including scaling resources, notifying teams, or triggering remediations.
CloudFront with S3 accelerates content delivery via edge caching but does not provide DNS-based latency routing or automated failover. While CloudFront improves performance for static content, it cannot route traffic globally based on latency or health.
Direct Connect with VPC Peering improves network connectivity but does not manage global user traffic routing or provide endpoint health monitoring. It is focused on private connectivity, not public API traffic management.
Lambda with DynamoDB enables serverless compute and NoSQL storage but does not provide latency-based routing, failover, or monitoring.
The combination of Route 53 latency-based routing, health checks, and CloudWatch ensures low-latency traffic routing, automated failover, and real-time observability. Users are directed to the fastest healthy endpoint, endpoints are continuously monitored, and operational insights are available through CloudWatch dashboards. This integrated approach meets all performance, availability, and monitoring requirements, making it the correct solution.
Question 117
A company uses AWS Lambda functions to process sensitive financial transactions. They want to enforce encryption of environment variables, prevent unauthorized code changes, and maintain an auditable compliance trail. Which combination of AWS services meets these requirements?
A) AWS Config + Lambda + KMS
B) Amazon S3 + Athena
C) CloudFront + WAF
D) QuickSight + CloudTrail
Answer: A) AWS Config + Lambda + KMS
Explanation:
AWS Config continuously monitors AWS resources and evaluates them against predefined compliance rules. For Lambda functions handling sensitive financial transactions, Config can ensure that environment variables are encrypted using AWS Key Management Service (KMS). If a Lambda function violates encryption requirements, Config flags it as noncompliant and logs the event for auditing purposes. This continuous monitoring provides visibility into compliance status and helps organizations meet regulatory requirements.
KMS provides centralized key management for encryption. By integrating KMS with Lambda environment variables, organizations ensure that sensitive data is encrypted at rest and can only be accessed by authorized principals. KMS also provides detailed audit logs, enabling tracking of key usage, decryption requests, and administrative actions. This helps maintain a robust security posture and compliance trail for regulatory audits.
Lambda allows role-based permissions to restrict changes to function code and environment variables. By combining Lambda with Config and KMS, organizations achieve multi-layered protection. Config monitors compliance continuously, KMS enforces encryption, and Lambda controls access to code. Automated remediation can be implemented using EventBridge or Systems Manager to correct noncompliant functions automatically.
Amazon S3 and Athena provide storage and analytics capabilities, but do not enforce encryption of Lambda environment variables, prevent unauthorized code changes, or provide compliance auditing for serverless functions.
CloudFront and WAF focus on content delivery and application security, but cannot manage Lambda function compliance, encrypt environment variables, or prevent unauthorized code modifications.
QuickSight with CloudTrail enables visualization and auditing. CloudTrail logs API activity, while QuickSight provides dashboards for analysis. However, this combination does not enforce encryption or prevent code changes automatically. It is primarily useful for post-facto auditing rather than proactive compliance enforcement.
By combining AWS Config, Lambda, and KMS, organizations achieve continuous compliance monitoring, enforced encryption, access control, and a complete audit trail. This solution ensures that sensitive financial data is protected, regulatory requirements are met, and operational governance is maintained, making it the correct solution.
Question 118
A company runs multiple Amazon ECS services on Fargate. They want to automatically detect when tasks are under high CPU or memory pressure, send alerts, and scale services dynamically without manual intervention. Which combination of AWS services should they implement?
A) CloudWatch metrics + ECS Service Auto Scaling
B) AWS Config + Lambda
C) Amazon S3 + Athena
D) AWS Backup + SNS
Answer: A) CloudWatch metrics + ECS Service Auto Scaling
Explanation:
Amazon CloudWatch collects and provides metrics for ECS Fargate services and tasks, including CPU and memory utilization, running task counts, and service health. Monitoring CPU and memory usage helps DevOps teams understand resource consumption patterns and identify potential performance bottlenecks. CloudWatch metrics can be aggregated, visualized on dashboards, and used to configure alarms that notify operations teams if resource usage exceeds defined thresholds. For example, a sustained CPU utilization above 80% triggers an alarm, indicating that the service may require additional capacity.
ECS Service Auto Scaling works in tandem with CloudWatch metrics to automatically adjust the number of running tasks in a service. Auto Scaling policies define rules for scaling out (adding tasks) or scaling in (removing tasks) based on observed metrics. When resource utilization exceeds thresholds, new tasks are launched automatically, ensuring that applications maintain performance under increased load. During periods of low demand, tasks can be scaled down to reduce costs. This combination enables fully automated and responsive scaling without manual intervention.
AWS Config with Lambda primarily focuses on configuration compliance and drift detection. While Config can monitor ECS resource settings and Lambda can remediate noncompliant configurations, this combination does not provide runtime performance monitoring, alerting, or automatic task scaling based on CPU or memory utilization.
Amazon S3 with Athena allows for storage and analysis of structured data. While ECS logs can be stored in S3 and queried with Athena, this is a batch process and does not enable real-time monitoring or automated scaling actions.
AWS Backup, combined with SN, focuses on protecting resources and sending notifications related to backup status. These services do not provide visibility into ECS task metrics or implement dynamic scaling of services based on resource consumption.
By combining CloudWatch metrics with ECS Service Auto Scaling, organizations gain real-time observability into task performance and automated scaling based on demand. CloudWatch ensures visibility and proactive alerting, while Auto Scaling maintains application performance and optimizes resource utilization. This fully managed approach minimizes operational overhead and ensures consistent performance under varying workloads, making it the correct solution.
Question 119
A global e-commerce company wants to route API requests to the lowest-latency AWS region, automatically fail over if an endpoint is unhealthy, and monitor endpoint performance in real time. Which AWS service combination fulfills these requirements?
A) Route 53 latency-based routing + health checks + CloudWatch
B) CloudFront + S3
C) Direct Connect + VPC Peering
D) Lambda + DynamoDB
Answer: A) Route 53 latency-based routing + health checks + CloudWatch
Explanation:
Amazon Route 53 provides latency-based routing, which directs user requests to the region that delivers the lowest network latency. By configuring multiple endpoints in different AWS regions, Route 53 ensures that global users experience minimal response times, improving performance and user experience. Latency-based routing evaluates the origin of each request and dynamically selects the endpoint with the fastest response.
Health checks in Route 53 continuously monitor endpoint availability and responsiveness. If an endpoint fails or its performance drops below specified thresholds, Route 53 automatically reroutes traffic to healthy endpoints. This failover mechanism improves global application availability, ensuring continuity of service without requiring manual intervention. Health checks can be configured to monitor HTTP/S responses, TCP ports, or application-level indicators, providing granular control over failover behavior.
CloudWatch complements Route 53 by providing real-time monitoring of endpoint performance. Metrics such as latency, error rates, and request volumes are captured and displayed on dashboards. Alarms notify operations teams when endpoints become unhealthy or performance degrades. Integration with EventBridge allows automated workflows to respond to incidents, such as scaling resources, notifying on-call engineers, or triggering remediations. CloudWatch dashboards provide operational insights into traffic patterns, latency trends, and health status across regions.
CloudFront with S3 accelerates static content delivery using edge caching but does not perform DNS-based latency routing or automatic failover across regions. While CloudFront improves response times for static assets, it does not route API traffic based on latency or monitor endpoint health dynamically.
Direct Connect with VPC Peering provides private connectivity between on-premises networks and VPCs, but it does not offer global user routing, latency-based traffic distribution, or automated failover mechanisms.
Lambda with DynamoDB provides serverless compute and storage capabilities but does not perform latency-based routing, failover, or real-time monitoring of API endpoints.
The combination of Route 53 latency-based routing, health checks, and CloudWatch ensures global users are directed to the fastest healthy endpoint, endpoints are continuously monitored, and operational teams are alerted in real time. This fully managed solution optimizes latency, ensures high availability, and provides observability, making it the correct solution.
Question 120
A company uses AWS Lambda functions to process sensitive financial transactions. They want to enforce encryption of environment variables, prevent unauthorized code changes, and maintain an auditable compliance trail. Which combination of AWS services is most appropriate?
A) AWS Config + Lambda + KMS
B) Amazon S3 + Athena
C) CloudFront + WAF
D) QuickSight + CloudTrail
Answer: A) AWS Config + Lambda + KMS
Explanation:
AWS Config provides continuous monitoring of AWS resources, including Lambda functions. By defining rules, Config ensures that environment variables are encrypted using AWS Key Management Service (KMS). If a Lambda function is noncompliant, such as having unencrypted variables, Config records the violation and generates audit logs. This allows the company to maintain a detailed, auditable compliance trail for regulatory purposes.
AWS Key Management Service (KMS) provides centralized encryption key management. By encrypting Lambda environment variables with KMS, sensitive financial data is protected at rest. KMS logs all key usage events, including who accessed or decrypted a key, providing a detailed audit trail for security and compliance. This ensures that only authorized principals can access sensitive information, maintaining data confidentiality and integrity.
Lambda itself enforces role-based permissions to prevent unauthorized code modifications. By combining Lambda with Config and KMS, the company achieves a multi-layered security strategy: Config monitors compliance continuously, KMS enforces encryption, and Lambda controls access to code. Integration with EventBridge or Systems Manager allows automatic remediation when violations occur, such as re-encrypting environment variables or restricting access.
Amazon S3 with Athena is suitable for storing and analyzing data, but it does not enforce encryption on Lambda environment variables, prevent unauthorized code changes, or provide proactive compliance monitoring.
CloudFront and WAF protect web applications from attacks and provide content delivery, but they do not manage Lambda configuration, enforce encryption, or prevent code changes.
QuickSight, combined with CloudTrail, provides auditing and visualization. CloudTrail logs API activities, and QuickSight enables analysis. However, they do not proactively enforce encryption or prevent unauthorized code changes. They are primarily post-facto auditing tools.
By combining AWS Config, Lambda, and KMS, the company ensures that sensitive financial data is encrypted, code integrity is maintained, and an auditable compliance trail is preserved. This integrated solution provides proactive monitoring, enforcement of security policies, and operational visibility, making it the correct solution.