Amazon AWS Certified DevOps Engineer — Professional DOP-C02 Exam Dumps and Practice Test Questions Set 4 Q46-60
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Question 46
A DevOps engineer wants to implement a CI/CD pipeline that automatically deploys containerized applications to Amazon EKS clusters with rollback capabilities if health checks fail. Which AWS service combination is most appropriate?
A) AWS CodePipeline + AWS CodeBuild + AWS CodeDeploy + Amazon EKS
B) AWS CloudFormation + AWS Config
C) Amazon EC2 Auto Scaling + CloudWatch Alarms
D) Amazon S3 + Lambda
Answer: A) AWS CodePipeline + AWS CodeBuild + AWS CodeDeploy + Amazon EKS
Explanation:
AWS CodePipeline orchestrates CI/CD workflows, enabling automated builds, tests, and deployments triggered by changes in code repositories. In a containerized application deployed to Amazon EKS, CodePipeline can manage the end-to-end deployment process, integrating seamlessly with CodeBuild and CodeDeploy. AWS CodeBuild provides a fully managed build environment for compiling code, running tests, and building Docker images for containerized workloads. Amazon EKS orchestrates Kubernetes clusters, providing scalable and highly available containerized deployments.
AWS CodeDeploy integrates with EKS for application deployments using rolling or blue/green strategies. It monitors application health using Kubernetes probes or custom CloudWatch metrics. If health checks fail during deployment, CodeDeploy automatically rolls back to the previous stable version, reducing downtime and minimizing risk. This approach ensures continuous delivery with reliability, allowing teams to focus on application logic rather than infrastructure management.
AWS CloudFormation automates infrastructure provisioning as code, but does not orchestrate application deployment workflows or provide automated rollback for containerized workloads. While CloudFormation templates can define EKS clusters and related resources, they cannot monitor deployment health or automatically revert failed deployments, limiting their suitability for CI/CD automation.
Amazon EC2 Auto Scaling, combined with CloudWatch Alarms, can scale EC2 instances and respond to metrics, but it does not manage container builds, testing, or orchestrated deployments to EKS. This approach would require significant custom automation to achieve the same level of CI/CD workflow management provided by CodePipeline and CodeDeploy.
Amazon S3 and Lambda can provide object storage and serverless functions, but cannot orchestrate CI/CD pipelines for containerized applications. S3 and Lambda lack integrated deployment health monitoring, rollback capabilities, or container orchestration features.
The combination of CodePipeline, CodeBuild, CodeDeploy, and EKS is optimal because it enables automated, reliable, and scalable CI/CD pipelines for containerized applications. CodePipeline orchestrates stages, CodeBuild compiles and tests images, EKS manages cluster orchestration, and CodeDeploy handles deployment strategies with automated rollback. Integration with CloudWatch allows monitoring of application metrics, providing visibility and alerting for operational issues. This setup aligns with DevOps best practices, reducing operational risk, ensuring repeatability, and improving deployment frequency without sacrificing reliability. Teams can maintain high availability, minimize downtime, and deliver updates safely while leveraging managed AWS services, streamlining both operational and developmental workflows for complex microservices architectures.
Question 47
A company wants to implement centralized audit and compliance monitoring for AWS accounts, including recording API activity, detecting unauthorized changes, and providing automated remediation. Which service combination is most suitable?
A) AWS CloudTrail + AWS Config + AWS Systems Manager
B) Amazon CloudWatch + Lambda
C) Amazon S3 + Athena
D) AWS CodePipeline + CodeBuild
Answer: A) AWS CloudTrail + AWS Config + AWS Systems Manager
Explanation:
AWS CloudTrail records API activity across AWS accounts, including management, data, and service events. CloudTrail logs allow DevOps teams to track all actions taken by users, roles, or services, providing a foundation for auditing and compliance monitoring. CloudTrail integrates with CloudWatch or S3 to store logs centrally and can trigger notifications or Lambda functions when specific events occur, enabling near real-time monitoring of changes.
AWS Config continuously evaluates resources against defined compliance rules, such as ensuring encryption on S3 buckets, limiting overly permissive IAM roles, or enforcing tagging policies. Config provides visibility into resource changes and automatically evaluates compliance, highlighting non-compliant resources for remediation. Config rules can trigger notifications via SNS or invoke automation workflows when violations are detected, ensuring timely corrective actions.
AWS Systems Manager complements CloudTrail and Config by automating operational and remediation tasks. For example, when Config detects a non-compliant resource, Systems Manager Automation documents can be executed to revert changes, remediate misconfigurations, or apply security patches. This integration enables fully automated governance and compliance workflows, reducing manual intervention and operational overhead.
Amazon CloudWatch and Lambda could provide monitoring and custom automation, but they lack the centralized audit, historical tracking, and built-in compliance evaluation features offered by CloudTrail and Config. CloudWatch metrics focus on operational health rather than comprehensive governance and audit compliance.
Amazon S3 and Athena enable batch analysis of logs, which is useful for reporting or forensic analysis, but do not provide automated compliance evaluation or remediation. Analysis is delayed until queries are ru,n and does not provide proactive enforcement.
CodePipeline and CodeBuild automate application build and deployment, but do not provide centralized audit or compliance enforcement. They are intended for CI/CD workflows rather than governance or operational compliance.
The combination of CloudTrail, Config, and Systems Manager is optimal because it provides end-to-end auditing, compliance evaluation, and automated remediation. CloudTrail records all API activity, Config continuously evaluates resources against organizational policies, and Systems Manager executes automation documents to resolve non-compliance automatically. This integrated approach reduces operational risk, ensures adherence to regulatory and internal governance standards, and provides comprehensive visibility across multiple accounts and regions. It also supports DevSecOps practices by enabling automated detection and remediation of security and configuration violations, improving operational efficiency, reducing human error, and maintaining continuous compliance across the organization. CloudTrail logs provide historical context for audits, Config rules enforce organizational policies, and Systems Manager automation ensures consistent, repeatable remediation processes, creating a robust governance and compliance framework.
Question 48
A DevOps engineer needs to deploy a fault-tolerant, low-latency database for globally distributed users, with automatic multi-region replication and no infrastructure management overhead. Which AWS service is most appropriate?
A) Amazon DynamoDB Global Tables
B) Amazon RDS Multi-AZ
C) Amazon Aurora Multi-Region
D) Amazon ElastiCache
Answer: A) Amazon DynamoDB Global Tables
Explanation:
Amazon DynamoDB Global Tables is a fully managed, multi-region, multi-master NoSQL database that provides automatic replication across regions. It is ideal for globally distributed applications requiring low-latency reads and writes in multiple locations. Each write to any region is asynchronously replicated to all other regions, ensuring eventual consistency while maintaining high availability. DynamoDB abstracts infrastructure management, allowing DevOps teams to focus on application logic rather than database maintenance, scaling, or replication. Global Tables support automated failover, provide high durability, and integrate seamlessly with IAM for access control, CloudWatch for metrics and monitoring, and Lambda for event-driven workflows.
Amazon RDS Multi-AZ provides high availability within a single region by replicating data to a standby instance in a different Availability Zone. While it ensures failover in the same region, it does not provide automatic multi-region replication, limiting its suitability for globally distributed low-latency access. Cross-region replication is possible with RDS read replicas, but it requires manual configuration and does not support multi-master writes.
Amazon Aurora Multi-Region supports cross-region replication for high availability and disaster recovery. However, Aurora replication is typically read-only in secondary regions, and managing failover or multi-region write operations can add operational complexity. Aurora requires more infrastructure management compared to serverless DynamoDB Global Tables.
Amazon ElastiCache provides in-memory caching for performance optimization but is not a primary data store. ElastiCache does not provide durable storage or automatic multi-region replication, making it unsuitable as a globally available database.
DynamoDB Global Tables is the best solution because it provides fully managed, automatic multi-region replication, low-latency access for global users, high availability, and scalability without infrastructure management. DevOps teams can rely on DynamoDB to handle replication, failover, scaling, and durability automatically. Integration with CloudWatch allows monitoring of throughput, latency, and errors, while IAM ensures secure access management. Global Tables provide a serverless database experience with predictable performance and operational simplicity, making it ideal for modern applications that require consistent low-latency access across multiple geographic regions. By using DynamoDB Global Tables, organizations can achieve fault tolerance, high availability, and disaster recovery while minimizing operational complexity and aligning with best practices for global-scale application design.
Question 49
A DevOps engineer wants to implement automated testing of infrastructure as code templates to validate security compliance, best practices, and functionality before deployment. Which AWS service or combination is most appropriate?
A) AWS CloudFormation + AWS CloudFormation Guard (cfn-guard)
B) AWS Config + Amazon SNS
C) AWS Systems Manager + CloudWatch
D) AWS CodeBuild + Amazon S3
Answer: A) AWS CloudFormation + AWS CloudFormation Guard (cfn-guard)
Explanation:
AWS CloudFormation allows organizations to define infrastructure as code using templates that describe resources and their configurations. Before deploying these templates, it is critical to validate that they comply with security policies, best practices, and functional requirements. AWS CloudFormation Guard (cfn-guard) is a tool that enables rule-based validation of CloudFormation templates. It evaluates templates against policies such as enforcing encryption, restricting public access, limiting open security groups, and other organizational standards.
Using CloudFormation combined with cfn-guard allows DevOps engineers to run automated checks as part of CI/CD pipelines. Templates can be validated for compliance before deployment, reducing the risk of misconfigurations, security vulnerabilities, and operational errors. Integration with CodePipeline or other CI/CD systems ensures that infrastructure is continuously validated and compliant before being applied to production environments.
AWS Config monitors deployed resources for compliance after creation, but does not validate templates or infrastructure code before deployment. Config evaluates live resources, providing auditing and alerting for non-compliance, but cannot prevent non-compliant templates from being deployed. Therefore, relying solely on Config does not achieve pre-deployment validation.
AWS Systems Manager provides operational management capabilities, such as patching, automation, and configuration management. While Systems Manager can automate remediation and operational tasks, it does not validate CloudFormation templates or enforce infrastructure-as-code policies before deployment.
AWS CodeBuild can run custom scripts for testing and validation, but it does not provide built-in rules for evaluating infrastructure-as-code compliance. Using CodeBuild alone would require additional custom scripts to mimic the functionality of cfn-guard, increasing operational complexity.
CloudFormation combined with cfn-guard is the optimal solution because it enables DevOps teams to perform automated pre-deployment validation, enforce security and compliance rules, and integrate seamlessly with CI/CD workflows. This approach ensures consistent, repeatable infrastructure deployments, reduces the risk of human error, and supports DevSecOps practices by embedding security checks into the development lifecycle. Validation rules can be updated centrally, allowing organizations to maintain compliance with evolving policies and regulatory requirements. By using this combination, teams achieve proactive governance, secure and compliant infrastructure, and improved confidence in deployment processes, while minimizing operational overhead and avoiding misconfigurations that could lead to downtime or security incidents.
Question 50
A company wants to implement real-time cost monitoring and alerting for AWS resources across multiple accounts. The alerts should trigger when spending exceeds predefined thresholds. Which AWS service combination is most suitable?
A) AWS Cost Anomaly Detection + Amazon SNS
B) AWS Config + CloudWatch
C) AWS CloudTrail + Lambda
D) Amazon S3 + Athena
Answer: A) AWS Cost Anomaly Detection + Amazon SNS
Explanation:
AWS Cost Anomaly Detection provides machine-learning-based monitoring of AWS usage and spending. It automatically establishes a baseline for expected costs for individual services, accounts, or linked accounts within an organization. When actual spending deviates from the baseline, Cost Anomaly Detection identifies the anomaly and generates an alert. Integration with Amazon SNS allows real-time notifications to be sent to operations teams, finance departments, or management. SNS supports multiple endpoints such as email, SMS, and HTTP/S endpoints, ensuring that alerts reach the appropriate stakeholders promptly.
AWS Config monitors resource configuration compliance, not cost or spending. While Config is essential for governance and compliance, it does not evaluate cost patterns or trigger cost-related notifications. It is more suitable for auditing resource setups rather than financial monitoring.
AWS CloudWatch provides operational metrics monitoring and alerts, but it does not natively support financial metrics for AWS service usage or anomaly detection. Custom CloudWatch metrics could theoretically track cost data if integrated with billing reports, but this requires complex setup and does not leverage AWS’s built-in anomaly detection capabilities.
AWS CloudTrail records API activity, including usage of AWS services, but it does not evaluate cost trends or trigger real-time alerts based on spending thresholds. CloudTrail is primarily intended for auditing and security purposes rather than financial monitoring.
Amazon S3 and Athena can store and analyze historical billing data, but this approach is batch-oriented. It does not support real-time anomaly detection or proactive alerting, making it unsuitable for immediate cost notifications. Queries must be run manually or scheduled, delaying responses to unexpected spikes in spending.
Cost Anomaly Detection combined with SNS is the optimal solution because it continuously monitors AWS costs across accounts, detects unusual spending patterns in real time, and notifies relevant teams automatically. This allows organizations to proactively address unexpected cost increases, identify misconfigured or underutilized resources, and maintain financial control. Alerts can trigger investigations, automated remediation, or budget adjustments without human delay. Integration with AWS Organizations enables monitoring of multiple accounts from a centralized management account, ensuring scalability and visibility across large environments. This combination reduces financial risk, supports budgeting goals, and aligns with DevOps best practices for automated monitoring and alerting. Cost Anomaly Detection provides actionable insights, supports granular monitoring of service-level spending, and leverages machine learning to adapt to seasonal or cyclical variations in usage. By integrating with SNS, the organization ensures that cost anomalies are acted upon promptly, avoiding surprises on AWS bills and enabling more efficient financial management of cloud resources.
Question 51
A DevOps engineer wants to implement a fully automated, scalable, and secure container image repository with vulnerability scanning integrated into the CI/CD pipeline. Which AWS service is most appropriate?
A) Amazon ECR (Elastic Container Registry)
B) Amazon S3
C) AWS CodeCommit
D) Amazon CloudWatch
Answer: A) Amazon ECR (Elastic Container Registry)
Explanation:
Amazon Elastic Container Registry (ECR) is a fully managed container image registry that allows teams to store, manage, and deploy Docker container images. ECR integrates seamlessly with CI/CD pipelines, supporting automated builds, pushes, and deployments. It provides built-in vulnerability scanning capabilities powered by Amazon Inspector, which analyzes container images for known software vulnerabilities. This integration ensures that only secure images are promoted through CI/CD pipelines, reducing security risks in production environments.
ECR supports fine-grained access control through AWS Identity and Access Management (IAM) roles and policies, ensuring that only authorized users and services can push or pull images. It is fully managed, automatically scales to handle large numbers of images and requests, and integrates with services like ECS, EKS, and Lambda for deployment. ECR also supports image lifecycle policies to automatically remove old or unused images, optimizing storage and cost management.
Amazon S3 is an object storage service, suitable for storing static files or backups, but not optimized for container image storage, versioning, or CI/CD integration. S3 does not provide vulnerability scanning, fine-grained access for container deployments, or integration with ECS/EKS pipelines.
AWS CodeCommit is a source code repository designed for managing application code and version control. While it integrates with CI/CD pipelines, it is not intended for storing, scanning, or managing container images, and does not provide automated vulnerability detection for containers.
Amazon CloudWatch provides monitoring and logging for AWS resources, but does not serve as a container image registry. It cannot store, manage, or scan container images, making it unsuitable for this use case.
Amazon ECR is the optimal solution because it provides a fully managed, scalable, and secure registry for container images with integrated vulnerability scanning. This allows DevOps teams to maintain a secure CI/CD pipeline, detect and remediate security issues before deployment, and manage container images efficiently. ECR simplifies operational overhead, ensures compliance with security policies, and supports automated deployment workflows for ECS, EKS, and Lambda environments. Its integration with IAM, lifecycle policies, and CloudWatch metrics ensures operational visibility, security, and scalability. By using ECR, organizations can automate the container lifecycle from build to deployment while maintaining security, compliance, and operational efficiency in a DevOps environment.
Question 52
A DevOps engineer needs to implement a serverless CI/CD pipeline that triggers deployments when code is committed, runs automated tests, and updates Lambda functions across multiple environments. Which AWS service combination is most suitable?
A) AWS CodePipeline + AWS CodeBuild + AWS CodeDeploy + Lambda
B) AWS CloudFormation + AWS Config
C) Amazon S3 + Amazon Athena
D) AWS Systems Manager + CloudWatch
Answer: A) AWS CodePipeline + AWS CodeBuild + AWS CodeDeploy + Lambda
Explanation:
AWS CodePipeline orchestrates CI/CD workflows by automating build, test, and deployment stages triggered by changes in a source code repository such as AWS CodeCommit, GitHub, or Bitbucket. In a serverless environment, CodePipeline can coordinate the workflow to ensure seamless deployments to Lambda functions across multiple environments, such as development, staging, and production.
AWS CodeBuild provides a fully managed build service to compile source code, run unit and integration tests, and create deployment artifacts, including zipped packages for Lambda functions. CodeBuild ensures that only tested and verified code progresses through the pipeline, reducing the risk of introducing errors into production. Integration with CodePipeline allows automatic promotion of successful builds to deployment stages.
AWS CodeDeploy integrates with Lambda to automate deployments, manage versions, and implement deployment strategies such as canary or linear deployments. This ensures minimal disruption to running functions by gradually shifting traffic to the new version. If errors or failures are detected during deployment through CloudWatch monitoring or configured alarms, CodeDeploy can automatically roll back to the previous stable version, maintaining service availability and reliability.
AWS CloudFormation allows infrastructure provisioning as code, which is critical for managing environments, but does not orchestrate CI/CD pipelines for serverless applications. CloudFormation can define Lambda functions and related resources, but it lacks integrated build, test, and automated deployment capabilities with rollback.
Amazon S3 and Athena are suitable for object storage and querying historical data, but do not provide CI/CD orchestration or deployment automation. S3 could store deployment artifacts, but this would require additional custom automation for builds, tests, and Lambda deployments.
AWS Systems Manager and CloudWatch provide operational management and monitoring capabilities. Systems Manager can automate operational tasks such as patching or configuration management, and CloudWatch provides metrics and alarms, but neither provides full CI/CD orchestration, automated testing, or deployment management.
The combination of CodePipeline, CodeBuild, CodeDeploy, and Lambda is optimal because it enables fully automated, scalable, and secure serverless CI/CD pipelines. This setup ensures that code changes automatically trigger testing and deployment across multiple environments without manual intervention. Canary or linear deployment strategies, integrated with automated rollback, reduce operational risk while allowing frequent deployments. CloudWatch integration provides monitoring, logging, and alerting to detect errors during deployment. By automating the entire process, DevOps teams achieve faster release cycles, higher reliability, and improved operational efficiency while maintaining alignment with DevSecOps best practices. The solution also reduces manual effort, enforces quality gates through automated testing, and allows secure, repeatable deployments of serverless applications in multiple environments.
Question 53
A company wants to automatically remediate non-compliant AWS resources, such as unencrypted S3 buckets or overly permissive security groups. Which AWS service combination allows continuous evaluation and automated remediation?
A) AWS Config + AWS Systems Manager
B) Amazon CloudWatch + Lambda
C) AWS CloudTrail + Amazon S3
D) AWS CodePipeline + CodeBuild
Answer: A) AWS Config + AWS Systems Manager
Explanation:
AWS Config continuously evaluates the configuration of AWS resources against predefined rules. Managed rules or custom Config rules can ensure resources comply with organizational policies, such as requiring S3 buckets to be encrypted, enforcing tagging, or restricting security group permissions. Config provides real-time detection of non-compliant resources, recording the state of compliance over time for auditing purposes.
AWS Systems Manager integrates with Config to enable automated remediation. When Config identifies a non-compliant resource, it can trigger Systems Manager Automation documents (runbooks) to remediate the violation automatically. For example, a non-compliant S3 bucket could be encrypted, or a security group with overly permissive rules could be restricted according to policy. This approach allows proactive management of compliance violations without manual intervention, reducing operational risk and ensuring consistent enforcement of organizational policies.
Amazon CloudWatch and Lambda can provide monitoring and custom automation. While this combination could detect changes or operational anomalies, it lacks a prebuilt compliance evaluation for AWS resources. Creating automated remediation workflows with CloudWatch and Lambda requires significant custom development, testing, and maintenance.
AWS CloudTrail records API activity for auditing, but does not evaluate resource compliance or implement automatic remediation. CloudTrail logs are useful for forensic analysis and tracking actions but do not enforce policies in real time.
AWS CodePipeline and CodeBuild orchestrate CI/CD workflows, managing build, test, and deployment processes. While these services automate application delivery, they are not intended for resource compliance monitoring or automated remediation of non-compliant infrastructure.
The combination of AWS Config and Systems Manager is optimal because Config continuously monitors resources, evaluates compliance against defined rules, and provides immediate notification of violations. Systems Manager enables automated remediation, ensuring that non-compliant resources are corrected without manual effort. This approach supports governance, regulatory compliance, and DevOps best practices by providing automated, repeatable, and auditable compliance enforcement. Teams can maintain continuous security and operational standards while reducing human error, improving efficiency, and maintaining visibility across multiple accounts and regions. Config tracks historical compliance, providing insight into trends and areas requiring attention, while Systems Manager automates corrective actions to minimize downtime, maintain security posture, and ensure resources are consistently configured according to policy.
Question 54
A DevOps engineer needs to deploy a multi-region, highly available API service that can automatically scale, provide caching at edge locations, and protect against DDoS attacks. Which AWS service combination is most suitable?
A) Amazon API Gateway + AWS Lambda + Amazon CloudFront + AWS WAF
B) AWS Systems Manager + EC2 Auto Scaling
C) AWS CloudFormation + AWS Config
D) Amazon S3 + Amazon CloudTrail
Answer: A) Amazon API Gateway + AWS Lambda + Amazon CloudFront + AWS WAF
Explanation:
Amazon API Gateway, combined with AWS Lambda, provides a fully managed, serverless API solution. API Gateway exposes endpoints securely and scales automatically to handle varying levels of traffic, while Lambda executes the underlying application logic without requiring server management. This ensures high availability and reliability for API services.
Amazon CloudFront, a global content delivery network (CDN), caches API responses at edge locations worldwide, reducing latency for geographically distributed users. CloudFront improves performance by serving content closer to users, decreasing load on backend services, and reducing operational costs.
AWS WAF (Web Application Firewall) protects the API endpoints from common web exploits and distributed denial-of-service (DDoS) attacks. WAF rules can block malicious requests, filter traffic, and provide additional security layers without affecting legitimate users. Integration with API Gateway and CloudFront ensures that APIs are protected globally while maintaining performance and availability.
AWS Systems Manager, combined with EC2 Auto Scaling, can provide scalable infrastructure for traditional applications, but it requires manual configuration, server management, and security implementation. This approach increases operational overhead and lacks the fully serverless, edge-optimized architecture required for global low-latency APIs.
AWS CloudFormation combined with Config provides infrastructure automation and compliance auditing, but it does not serve dynamic API requests or provide DDoS protection. These services are intended for provisioning and governance rather than application execution and global scaling.
Amazon S3 combined with CloudTrail is suitable for storing static content and auditing API activity, but it cannot serve dynamic API requests, perform serverless logic execution, scale automatically, or provide global caching and DDoS protection.
The combination of API Gateway, Lambda, CloudFront, and WAF is optimal because it provides a serverless, highly available, low-latency API solution with built-in global caching and security against DDoS attacks. This architecture minimizes operational overhead, scales automatically with demand, and ensures secure delivery of application functionality to a global user base. CloudFront improves response times by serving content at edge locations, WAF protects against malicious traffic, and Lambda handles application logic without server management. Integration with CloudWatch allows monitoring, logging, and alerting for operational metrics, ensuring visibility and observability. This setup aligns with DevOps best practices, providing automated scaling, global performance optimization, and security while reducing operational complexity, cost, and risk for multi-region API deployments.
Question 55
A DevOps engineer wants to implement automated blue/green deployments for containerized applications running on Amazon ECS. The deployment should minimize downtime and allow instant rollback if issues occur. Which AWS service combination is most appropriate?
A) AWS CodeDeploy + Amazon ECS + AWS CodePipeline
B) AWS CloudFormation + AWS Config
C) Amazon EC2 Auto Scaling + CloudWatch Alarms
D) Amazon S3 + Lambda
Answer: A) AWS CodeDeploy + Amazon ECS + AWS CodePipeline
Explanation:
AWS CodeDeploy integrates with Amazon ECS to manage blue/green deployments for containerized applications. A blue/green deployment involves running two separate environments: the existing (blue) and the new (green). CodeDeploy gradually shifts traffic from the blue environment to the green environment, monitoring application health using ECS service metrics and CloudWatch alarms. If any issues are detected, CodeDeploy can automatically roll back traffic to the blue environment, ensuring minimal downtime and preserving user experience.
AWS CodePipeline orchestrates the CI/CD workflow, automating builds, tests, and deployment stages. When combined with CodeBuild, container images are built, tested, and pushed to a registry like Amazon ECR. CodePipeline triggers CodeDeploy to deploy the new image to ECS with blue/green deployment strategies. This integration ensures seamless automation, reliable deployments, and consistent delivery practices.
AWS CloudFormation is primarily an infrastructure-as-code tool and cannot orchestrate application deployment workflows or automated rollbacks. CloudFormation templates can define ECS services and clusters, but cannot execute deployment strategies such as blue/green or handle runtime monitoring of deployment health.
Amazon EC2 Auto Scaling with CloudWatch Alarms provides horizontal scaling based on resource metrics. While this approach can scale ECS instances, it does not orchestrate container deployments, manage deployment strategies, or automate rollback, requiring significant custom automation for full blue/green functionality.
Amazon S3 and Lambda are not suitable for orchestrating containerized deployments. S3 is object storage, and Lambda executes serverless functions; neither service manages ECS deployments or supports traffic-shifting strategies.
The combination of CodeDeploy, ECS, and CodePipeline is optimal because it automates the complete lifecycle of containerized applications with minimal downtime. CodePipeline handles CI/CD orchestration, CodeBuild ensures tested and verified images, ECS hosts the containers, and CodeDeploy manages traffic shifting, health monitoring, and rollback. This setup aligns with DevOps best practices by reducing operational risk, increasing deployment reliability, and supporting repeatable, automated processes. Blue/green deployments allow rapid testing of new versions in production environments without impacting end users, providing confidence in release quality while maintaining high availability. Integration with CloudWatch ensures real-time monitoring of deployment success, errors, and resource utilization, further enhancing operational visibility and reducing the time to detect and respond to issues.
Question 56
A company wants to monitor application performance across multiple AWS accounts and regions with anomaly detection, real-time dashboards, and notifications for deviations. Which AWS service combination is most suitable?
A) Amazon CloudWatch Cross-Account Observability + Amazon SNS
B) AWS Config + AWS CloudTrail
C) Amazon S3 + Amazon Athena
D) AWS Systems Manager + CloudWatch Logs
Answer: A) Amazon CloudWatch Cross-Account Observability + Amazon SNS
Explanation:
Amazon CloudWatch Cross-Account Observability enables centralized monitoring of metrics, logs, and traces from multiple AWS accounts and regions. This is ideal for organizations managing distributed applications or microservices across accounts. Cross-account observability consolidates operational data into a single account, allowing DevOps teams to monitor application health, request latency, error rates, and other metrics on real-time dashboards.
Anomaly detection in CloudWatch leverages machine learning to establish normal patterns for metrics. When actual metrics deviate from expected values, CloudWatch flags anomalies. Integration with Amazon SNS ensures that notifications are sent immediately to relevant stakeholders via email, SMS, or HTTP endpoints. This enables rapid response to performance degradation, operational issues, or potential incidents.
AWS Config evaluates resource compliance against policies, such as encryption or tagging requirements. While Config is excellent for governance and auditing, it does not provide operational monitoring, real-time dashboards, or anomaly detection of application metrics.
AWS CloudTrail logs API activity for auditing and security purposes. While CloudTrail is essential for governance and forensic analysis, it does not provide real-time operational monitoring, anomaly detection, or alerting on metric deviations.
Amazon S3 and Athena provide batch-oriented analysis of logs and metrics. This setup is useful for historical analysis, reporting, or trend evaluation, but lacks real-time monitoring and anomaly detection capabilities necessary for operational alerting.
AWS Systems Manager and CloudWatch Logs provide monitoring and operational automation for managed resources. While useful for certain operational tasks, this combination does not provide centralized cross-account monitoring, machine-learning-based anomaly detection, or real-time dashboards.
The combination of CloudWatch Cross-Account Observability and SNS is optimal because it enables centralized, real-time operational visibility across multiple accounts and regions. Machine-learning-based anomaly detection identifies performance deviations without relying solely on static thresholds. SNS ensures rapid delivery of alerts to operational teams, enabling proactive incident management. Dashboards consolidate metrics, logs, and traces, facilitating correlation and analysis. This solution supports DevOps best practices for observability, allowing teams to maintain service reliability, optimize performance, and reduce mean time to resolution (MTTR). Cross-account observability ensures that teams can monitor multiple environments from a single pane of glass, providing operational efficiency, consistency, and timely decision-making across distributed applications.
Question 57
A DevOps engineer needs a centralized solution to manage secrets, automate rotation, and allow applications to retrieve secrets securely at runtime. Which AWS service is most suitable?
A) AWS Secrets Manager
B) AWS Systems Manager Parameter Store
C) AWS Config
D) Amazon S3
Answer: A) AWS Secrets Manager
Explanation:
AWS Secrets Manager is a fully managed service for storing, managing, and rotating secrets such as database credentials, API keys, or configuration strings. It allows applications to retrieve secrets programmatically at runtime without embedding credentials in code. Secrets Manager supports automatic rotation, enabling secure credential updates without redeploying applications or Lambda functions. Integration with IAM ensures fine-grained access control, allowing only authorized applications or services to access secrets.
AWS Systems Manager Parameter Store can store configuration values and secure strings encrypted with KMS. While Parameter Store supports versioning and encryption, it does not provide built-in automatic rotation. Custom automation would be required to rotate secrets, increasing operational overhead.
AWS Config monitors resource configurations for compliance but does not manage secrets or their lifecycle. Config is focused on auditing and policy enforcement rather than secure secret management.
Amazon S3 is object storage, which could store encrypted secrets, but it does not provide automated rotation, secure retrieval at runtime, or fine-grained access control specific to secrets. Using S3 for secret management increases security risks and requires additional custom development.
AWS Secrets Manager is optimal because it centralizes secret management, enables automatic rotation, ensures secure access at runtime, and integrates with monitoring and auditing tools. This reduces operational risk, enhances security posture, and supports DevOps best practices for managing sensitive information. Secrets Manager allows DevOps teams to maintain compliance, automate credential lifecycle management, and prevent exposure of secrets, while minimizing manual intervention and operational complexity.
Question 58
A DevOps team needs to implement automated vulnerability scanning of container images during the CI/CD pipeline and prevent the deployment of insecure images. Which AWS service is most suitable?
A) Amazon ECR (Elastic Container Registry)
B) Amazon S3
C) AWS CodeCommit
D) AWS CloudTrail
Answer: A) Amazon ECR (Elastic Container Registry)
Explanation:
Amazon ECR is a fully managed container image registry that integrates seamlessly with AWS CI/CD pipelines, including CodePipeline and CodeBuild. ECR supports automated vulnerability scanning of container images using Amazon Inspector, which analyzes images for known security vulnerabilities. When an image is pushed to ECR, the scanning process identifies CVEs (Common Vulnerabilities and Exposures) and generates reports. These reports can be integrated into the CI/CD pipeline to prevent the promotion of insecure images to production environments, ensuring that only secure, verified images are deployed.
ECR provides fine-grained access control through AWS IAM, allowing DevOps teams to enforce least-privilege permissions for pushing or pulling images. It supports versioning and lifecycle policies to manage image retention, automatically deleting older or unused images to optimize storage and reduce cost. Integration with CloudWatch allows monitoring of image scans, repository activity, and other metrics.
Amazon S3 is object storage, suitable for storing artifacts or backups, but not optimized for container images or vulnerability scanning. While S3 can store Docker images, it lacks integrated scanning, CI/CD integration, and deployment support. Using S3 for this purpose would require extensive custom automation.
AWS CodeCommit is a source code repository designed for storing and managing application code. While it integrates with CI/CD pipelines, it does not store, scan, or manage container images. Security scanning would require additional tools and custom scripting.
AWS CloudTrail records API activity and provides auditing capabilities. CloudTrail is valuable for tracking changes and compliance, but it does not perform image scanning or prevent the deployment of insecure container images.
ECR is the optimal solution because it provides a fully managed, secure, and scalable container registry with built-in vulnerability scanning. It ensures DevOps teams can detect and remediate vulnerabilities early in the development lifecycle, preventing insecure images from reaching production. Integration with CI/CD pipelines enables automated enforcement of security policies, aligning with DevSecOps best practices. Lifecycle policies reduce operational overhead, and IAM integration ensures controlled access. ECR’s seamless integration with CodeBuild, CodePipeline, and ECS/EKS allows organizations to maintain a secure, efficient, and automated container deployment process, reducing risk, improving compliance, and maintaining application reliability. By providing end-to-end container image management, ECR enhances security posture and operational efficiency, supporting automated detection, remediation, and governance in modern DevOps environments.
Question 59
A company wants to implement continuous compliance auditing across AWS accounts to ensure that resources meet organizational policies and automatically notify teams when non-compliance is detected. Which AWS service combination is most suitable?
A) AWS Config + Amazon SNS
B) AWS CloudTrail + Lambda
C) Amazon S3 + Athena
D) AWS Systems Manager + CloudWatch
Answer: A) AWS Config + Amazon SNS
Explanation:
AWS Config continuously evaluates AWS resources against pre-defined compliance rules. Managed rules or custom rules can enforce organizational policies, such as ensuring encryption on S3 buckets, enforcing tagging standards, or limiting overly permissive IAM roles and security group settings. Config maintains a historical record of compliance status, providing insight into resource drift over time and enabling auditing for regulatory and governance purposes.
Integration with Amazon SNS allows Config to automatically notify relevant teams when non-compliance is detected. Notifications can be sent via email, SMS, or to downstream systems such as ticketing or incident management platforms. This ensures that compliance violations are addressed quickly, minimizing security risks and operational disruptions.
AWS CloudTrail records API activity for auditing purposes. While it provides a log of changes and can be used to track resource modifications, it does not automatically evaluate compliance or send notifications based on policy violations. CloudTrail is more reactive and requires additional tools for automated compliance enforcement.
Amazon S3 and Athena allow storage and querying of resource data or logs for batch analysis. While this setup is useful for historical reporting, it does not provide continuous compliance evaluation or real-time notifications. Queries must be executed manually or on a schedule, which delays detection and remediation of violations.
AWS Systems Manager provides operational automation and configuration management. While it can automate remediation tasks, it does not continuously evaluate compliance across resources or provide a centralized alerting mechanism without significant custom automation. CloudWatch monitors metrics and logs but does not enforce compliance policies or provide historical tracking of resource configurations.
The combination of AWS Config and SNS is optimal because it continuously evaluates resources, enforces compliance rules, and provides real-time notifications. This approach ensures that non-compliant resources are identified and addressed promptly, reducing security risks and operational issues. Config’s historical data allows auditing and reporting for regulatory compliance, while SNS ensures timely awareness and escalation. This integrated solution supports DevOps and DevSecOps practices by embedding compliance checks into operational workflows, automating detection, and enabling proactive remediation. By using Config and SNS, organizations maintain consistent governance across multiple accounts and regions, improve operational efficiency, and minimize the risk of misconfigured or non-compliant resources. Continuous compliance monitoring ensures operational excellence, reduces manual effort, and aligns with industry best practices for secure and reliable cloud operations.
Question 60
A DevOps engineer wants to implement a global, low-latency, highly available API for users around the world. The API should automatically scale, provide caching at edge locations, and protect against web attacks. Which AWS service combination is most suitable?
A) Amazon API Gateway + AWS Lambda + Amazon CloudFront + AWS WAF
B) AWS Systems Manager + EC2 Auto Scaling
C) AWS CloudFormation + AWS Config
D) Amazon S3 + CloudTrail
Answer: A) Amazon API Gateway + AWS Lambda + Amazon CloudFront + AWS WAF
Explanation:
Amazon API Gateway exposes API endpoints and manages requests, throttling, authentication, and security. Combined with AWS Lambda, API Gateway enables a fully serverless, scalable solution where Lambda functions handle application logic without server management. This combination ensures that APIs automatically scale to handle varying traffic loads and remain highly available.
Amazon CloudFront caches API responses at edge locations globally, reducing latency for geographically distributed users. CloudFront improves performance, decreases origin load, and provides faster response times, making the API highly responsive to users worldwide. Integration with API Gateway ensures that API requests benefit from caching and edge optimization without changes to the backend logic.
AWS WAF protects APIs from common web exploits and distributed denial-of-service (DDoS) attacks. WAF rules allow filtering of malicious traffic, blocking harmful requests, and protecting API endpoints. When combined with CloudFront and API Gateway, WAF ensures global security coverage while maintaining performance.
AWS Systems Manager with EC2 Auto Scaling provides a scalable infrastructure for traditional applications. While it can automate scaling and operational tasks, it requires server management, patching, and security configuration, increasing operational overhead. It does not provide serverless execution, global edge caching, or integrated DDoS protection for APIs.
AWS CloudFormation, combined with AWS Config, allows infrastructure provisioning and compliance auditing. These services cannot execute application logic, scale APIs globally, or provide edge caching and DDoS protection.
Amazon S3, combined with CloudTrail, can store static content and log API activity, but does not provide dynamic API execution, low-latency global scaling, or automated security protections.
API Gateway, Lambda, CloudFront, and WAF are the optimal solution because they provide a serverless, highly available, globally distributed API with low-latency performance, automatic scaling, and integrated security protections. CloudFront reduces latency through caching at edge locations, Lambda ensures scalable application execution, API Gateway manages API endpoints, and WAF protects against attacks. CloudWatch integration provides monitoring and observability for API performance and errors. This architecture minimizes operational overhead, supports DevOps best practices, enhances security, and delivers reliable, high-performance APIs for global users. By combining serverless execution, edge caching, and integrated security, teams can achieve rapid deployments, consistent performance, and robust protection with minimal operational complexity.