Amazon AWS-DevOps-Engineer-Professional-KR exam dumps - AWS Certified DevOps Engineer - Professional (DOP-C01 Korean Version)

  • Exam Code: AWS-DevOps-Engineer-Professional-KR
  • Exam Name: AWS Certified DevOps Engineer - Professional (DOP-C01 Korean Version)
  • Updated: Jun 01, 2026     Q & A: 575 Questions and Answers

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Training Materials for Obtaining AWS DevOps – Engineer Professional Certification

Candidates can leverage their chances to get the passing score in the exam for the AWS Certified DevOps – Engineer Professional certification if they use the right prep tools, such as:

  • AWS Certified DevOps Engineer Professional – Practice Questions by IP Specialist

    This Amazon book includes detailed explanations of each practice question for test DOP-C01. Therefore, the readers will know exactly how to find the correct answer to questions when it comes to the official validation. The guide was developed based on different scenarios, which means that it combines theoretical knowledge with the practical one. In all, the readers will receive 350+ practice questions and answers that follow the exam blueprint. Thus, it’ll help the candidates understand whether they are prepared to take the official exam and identify the topics on which they should focus more. Besides, it includes a career report. Overall, it is a step-by-step guide for aspiring candidates that helps them understand their future prospects and towards which industry the candidates are moving. Also, applicants will find the monetary benefits of the AWS Certified DevOps Engineer Professional and how they can get certified.

  • DevOps Engineering on AWS

    This is one of the official training resources provided by Amazon which helps the candidates understand DevOps practices, cultural philosophies, and tools to increase the organization’s capability to deliver, develop, and maintain services and apps at the highest velocity while using AWS systems. The topics covered by this course are related to continuous delivery and integration, micro-services, logging, monitoring, collaboration, and communication. The course objectives are the following:

    • Understanding the benefits and responsibilities of DevOps autonomous teams;
    • Leveraging AWS Cloud9 to ensure the highest level of code writing, running, and debugging;
    • Implementing and designing an AWS infrastructure so that they support DevOps development projects;
    • Using DevOps best practices for delivering, maintaining, and developing services and apps on AWS at high velocity;
    • Hosting highly scalable and secure Git repositories with the help of AWS CodeCommit features;
    • Building CI/CD pipelines to manage app deployment on Amazon EC2, as well as using serverless applications and container-based apps;
    • Monitoring apps and environments with the help of AWS technologies and tools;
    • Integrating security and testing into CI/CD pipelines;
    • Using AWS CloudFormation to deploy various environments.

    The target audience for this type of class is formed of DevOps architects and engineers, as well as system administrators, operations engineers, and developers. Apart from theoretical knowledge acquired during this training, you will also manage to practice with hands-on exercises & labs that deal with workflows for multi-pipelines.

  • AWS Certified DevOps Engineer Professional – Technology Workbook by IP Specialist

    This workbook is also available on Amazon.com and it was written by a team of skilled engineers who used their knowledge to help the reader understand which skills he/she needs to develop to get the passing score in the certification exam. This guide covers the official DOP-C01 exam blueprint. Therefore, it’s impossible for candidates to miss any topic which will be tested in the real exam. Besides, it includes additional training resources such as 350+ practice questions, mind maps, acronyms, diagrams, and references. Also, the readers will find answers to all their questions related to getting the AWS DevOps Engineer – Professional certification. What’s more, each answer to a practice question comes with a detailed explanation to help the candidates understand how to think correctly on each topic and what they should do to improve their knowledge. Finally, just like other books published by IP Specialist, this one also comes with several freebies, among which the readers may receive a career report that will help them understand how to build a successful career with this AWS certification.

AWS-DevOps Exam Syllabus Topics:

SectionObjectives

SDLC Automation - 22%

Apply concepts required to automate a CI/CD pipeline- Set up repositories
- Set up build services
- Integrate automated testing (e.g., unit tests, integrity tests)
- Set up deployment products/services
- Orchestrate multiple pipeline stages
Determine source control strategies and how to implement them- Determine a workflow for integrating code changes from multiple contributors
- Assess security requirements and recommend code repository access design
- Reconcile running application versions to repository versions (tags)
- Differentiate different source control types
Apply concepts required to automate and integrate testing- Run integration tests as part of code merge process
- Run load/stress testing and benchmark applications at scale
- Measure application health based on application exit codes (robust Health Check)
- Automate unit tests to check pass/fail, code coverage
  • CodePipeline, CodeBuild, etc.

- Integrate tests with pipeline

Apply concepts required to build and manage artifacts securely- Distinguish storage options based on artifacts security classification
- Translate application requirements into Operating System and package configuration (build specs)
- Determine the code/environment dependencies and required resources
  • Example: CodeDeploy AppSpec, CodeBuild buildspec

- Run a code build process

Determine deployment/delivery strategies (e.g., A/B, Blue/green, Canary, Red/black) and how to implement them using AWS services- Determine the correct delivery strategy based on business needs
- Critique existing deployment strategies and suggest improvements
- Recommend DNS/routing strategies (e.g., Route 53, ELB, ALB, load balancer) based on business continuity goals
- Verify deployment success/failure and automate rollbacks

Configuration Management and Infrastructure as Code - 19%

Determine deployment services based on deployment needs- Demonstrate knowledge of process flows of deployment models
- Given a specific deployment model, classify and implement relevant AWS services to meet requirements
  • Given the requirement to have DynamoDB choose CloudFormation instead of OpsWorks
  • Determine what to do with rolling updates
Determine application and infrastructure deployment models based on business needs- Balance different considerations (cost, availability, time to recovery) based on business requirements to choose the best deployment model
- Determine a deployment model given specific AWS services
- Analyze risks associated with deployment models and relevant remedies
Apply security concepts in the automation of resource provisioning- Choose the best automation tool given requirements
- Demonstrate knowledge of security best practices for resource provisioning (e.g., encrypting data bags, generating credentials on the fly)
- Review IAM policies and assess if sufficient but least privilege is granted for all lifecycle stages of a deployment (e.g., create, update, promote)
- Review credential management solutions (e.g., EC2 parameter store, third party)
- Build the automation
  • CloudFormation template, Chef Recipe, Cookbooks, Code pipeline, etc.
Determine how to implement lifecycle hooks on a deployment- Determine appropriate integration techniques to meet project requirements
- Choose the appropriate hook solution (e.g., implement leader node selection after a node failure) in an Auto Scaling group
- Evaluate hook implementation for failure impacts (if a remote call fails, if a dependent service is temporarily unavailable (i.e., Amazon S3), and recommend resiliency improvements
- Evaluate deployment rollout procedures for failure impacts and evaluate rollback/recovery processes
Apply concepts required to manage systems using AWS configuration management tools and services- Identify pros and cons of AWS configuration management tools
- Demonstrate knowledge of configuration management components
- Show the ability to run configuration management services end to end with no assistance while adhering to industry best practices

Monitoring and Logging - 15%

Determine how to set up the aggregation, storage, and analysis of logs and metrics- Implement and configure distributed logs collection and processing (e.g., agents, syslog, flumed, CW agent)
- Aggregate logs (e.g., Amazon S3, CW Logs, intermediate systems (EMR), Kinesis FH – Transformation, ELK/BI)
- Implement custom CW metrics, Log subscription filters
- Manage Log storage lifecycle (e.g., CW to S3, S3 lifecycle, S3 events)
Apply concepts required to automate monitoring and event management of an environment- Parse logs (e.g., Amazon S3 data events/event logs/ELB/ALB/CF access logs) and correlate with other alarms/events (e.g., CW events to AWS Lambda) and take appropriate action
- Use CloudTrail/VPC flow logs for detective control (e.g., CT, CW log filters, Athena, NACL or WAF rules) and take dependent actions (AWS step) based on error handling logic (state machine)
- Configure and implement Patch/inventory/state management using ESM (SSM), Inspector, CodeDeploy, OpsWorks, and CW agents
  • EC2 retirement/maintenance

- Handle scaling/failover events (e.g., ASG, DB HA, route table/DNS update, Application Config, Auto Recovery, PH dashboard, TA)
- Determine how to automate the creation of monitoring

Apply concepts required to audit, log, and monitor operating systems, infrastructures, and applications- Monitor end to end service metrics (DDB/S3) using available AWS tools (X-ray with EB and Lambda)
- Verify environment/OS state through auditing (Inspector), Config rules, CloudTrail (process and action), and AWS APIs
- Enable, configure, and analyze custom metrics (e.g., Application metrics, memory, KCL/KPL) and take action
- Ensure container monitoring (e.g., task state, placement, logging, port mapping, LB)
- Distinguish between services that enable service level or OS level monitoring
  • Example: AWS services that use OS agents (e.g., Inspector, SSM)
Determine how to implement tagging and other metadata strategies- Segregate authority based on tagging (lifecycle stages – dev/prod) with Condition context keys
- Utilize Amazon S3 system/user-defined metadata for classification and automation
- Design and implement tag-based deployment groups with CodeDeploy
- Best practice for cost allocation/optimization with tagging

Policies and Standards Automation - 10%

Apply concepts required to enforce standards for logging, metrics, monitoring, testing, and security- Detect, report, and respond to governance and security violations
- Apply logging standards across application, operating system, and infrastructure
- Apply context specific application health and performance monitoring
- Outline standards for delivery models for logs and metrics (e.g., JSON, XML, Data Normalization)
Determine how to optimize cost through automation- Prioritize automation effort to reduce labor costs
- Implement right sizing of workload based on metrics
- Assess ways to improve time to market through automating process orchestration and repeatable tasks
- Diagnose outliers to determine use case fit
  • Example: Configuration drift

- Measure and automate cost optimization through events

  • Example: Trusted Advisor
Apply concepts required to implement governance strategies- Generalize governance standards across CI/CD pipeline
- Outline and measure the real-time status of compliance with governance strategies
- Report on compliance with governance strategies
- Deploy governance policies related to self-service capabilities
  • Example: Service Catalog, CFN Nag

Incident and Event Response - 18%

Troubleshoot issues and determine how to restore operations- Given an issue, evaluate how to narrow down the unhealthy components as quickly as possible
- Given an increase in load, determine what steps to take to mitigate the impact
- Determine the causes and impacts of a failure
  • Example: Deployment, operations

- Determine the best way to restore operations after a failure occurs
- Investigate and correlate logged events with application components

  • Example: application source code
Determine how to automate event management and alerting- Set up automated restores from backup in the event of a catastrophic failure
- Set up methods to deliver alerts and notifications that are appropriate for different types of events
- Assess the quality/actionability of alerts
- Configure metrics appropriate to an application’s SLAs
- Proactively update limits
Apply concepts required to implement automated healing- Set up the correct scaling strategy to enable auto-healing when a failure occurs (e.g., with Auto Scaling policies)
- Use the correct rollback strategy to avoid impact from failed deployments
- Configure Route 53 to ensure cross-Region failover
- Detect and respond to maintenance or Spot termination events
Apply concepts required to set up event-driven automated actions- Configure Lambda functions or CloudWatch actions to implement automated actions
- Set up CloudWatch event rules and/or Config rules and targets
- Use AWS Systems Manager or Step Functions to coordinate components (e.g., Lambda, use maintenance windows)
- Configure a build/roll-out process to automatically respond to critical software updates

High Availability, Fault Tolerance, and Disaster Recovery - 16%

Determine appropriate use of multi-AZ versus multi-Region architectures- Determine deployment strategy based on HA/DR requirements
- Determine data replication strategy based on cost and durability requirements
- Determine infrastructure, platform, and services based on HA/DR requirements
- Design for HA/FT/DR based on service availability (i.e., global/regional/single AZ)
Determine how to implement high availability, scalability, and fault tolerance- Design deployment strategy to support HA/FT/scalability
- Assess statefulness of application infrastructure components
- Use load balancing to distribute traffic across multiple AZ/ASGs/instance types (spot/M4 vs C4) /targets
- Use appropriate caching solutions to improve availability and performance
Determine the right services based on business needs (e.g., RTO/RPO, cost)- Determine cost-effective storage solution for your application
  • Example: tiered, archival, EBS type, hot/cold

- Choose a database platform and configuration to meet business requirements
- Choose a cost-effective compute platform based on business requirements

  • Example: Spot

- Choose a deployment service/model based on business requirements

  • Example: Code Deploy, Blue/Green deployment

- Determine when to use managed service vs. self-managed infrastructure (Docker on EC2 vs. ECS)

Determine how to design and automate disaster recovery strategies- Automate failure detection
- Automate components/environment recovery
- Choose appropriate deployment strategy for environment recovery
- Design automation to support failover in hybrid environment
Evaluate a deployment for points of failure- Determine appropriate deployment-specific health checks
- Implement failure detection during deployment
- Implement failure event handling/response
- Ensure that resources/components/processes exist to react to failures during deployment
- Look for exit codes on each event of the deployment
- Map errors to different points of deployment

Reference: https://aws.amazon.com/certification/certified-devops-engineer-professional/

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