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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)

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Amazon AWS Certified DevOps Engineer - Professional Sample Questions (Q200-Q205):

NEW QUESTION # 200
An application has microservices spread across different AWS accounts and is integrated with an on-premises legacy system for some of its functionality.
Because of the segmented architecture and missing logs, every time the application experiences issues, it is taking too long to gather the logs to identify the issues. A DevOps Engineer must fix the log aggregation process and provide a way to centrally analyze the logs.
Which is the MOST efficient and cost-effective solution?

  • A. Collect system logs and application logs by using the Amazon CloudWatch Logs agent. Install a CloudWatch Logs agent for on-premises resources. Store all logs in an S3 bucket in a central account.
    Set up an Amazon S3 trigger and an AWS Lambda function to analyze incoming logs and automatically identify anomalies. Use Amazon Athena to run ad hoc queries on the logs in the central account.
  • B. Collect system logs and application logs by using the Amazon CloudWatch Logs agent. Use the Amazon S3 API to export on-premises logs, and store the logs in an S3 bucket in a central account.
    Build an Amazon EMR cluster to reduce the logs and derive the root cause.
  • C. Collect system logs and application logs using the Amazon CloudWatch Logs agent. Install the CloudWatch Logs agent on the on-premises servers. Transfer all logs from AWS to the on-premises data center. Use an Amazon Elasticsearch Logstash Kibana stack to analyze logs on premises.
  • D. Collect system logs and application logs by using the Amazon CloudWatch Logs agent. Use the Amazon S3 API to import on-premises logs. Store all logs in S3 buckets in individual accounts. Use Amazon Macie to write a query to search for the required specific event-related data point.

Answer: A


NEW QUESTION # 201
You have been asked to de-risk deployments at your company. Specifically, the CEO is concerned about outages that occur because of accidental inconsistencies between Staging and Production, which sometimes cause unexpected behaviors in Production even when Staging tests pass. You already use Docker to get high consistency between Staging and Production for the application environment on your EC2 instances. How do you further de-risk the rest of the execution environment, since in AWS, there are many service components you may use beyond EC2 virtual machines?

  • A. Develop models of your entire cloud system in CloudFormation. Use this model in Staging and Production to achieve greater parity. */
  • B. Use AMIs to ensure the whole machine, including the kernel of the virual machines, is consistent, since Docker uses Linux Container (LXC) technology, and we need to make sure the container environment is consistent.
  • C. Use AWS Config to force the Staging and Production stacks to have configuration parity. Any differences will be detected for you so you are aware of risks.
  • D. Use AWS ECS and Docker clustering. This will make sure that the AMIs and machine sizes are the same across both environments.

Answer: A

Explanation:
Explanation
After you have your stacks and resources set up, you can reuse your templates to replicate your infrastructure in multiple environments. For example, you can create environments for development, testing, and production so that you can test changes before implementing them into production. To make templates reusable, use the parameters, mappings, and conditions sections so that you can customize your stacks when you create them. For example, for your development environments, you can specify a lower-cost instance type compared to your production environment, but all other configurations and settings remain the same For more information on Cloudformation best practices please refer to the below link:
* http://docs.aws.amazon.com/AWSCIoudFormation/latest/UserGuide/best-practices.html


NEW QUESTION # 202
A user is creating a new EBS volume from an existing snapshot.
The snapshot size shows 10 GB. Can the user create a volume of 30 GB from that snapshot?

  • A. Yes
  • B. No
  • C. Provided the original volume has set the change size attribute to true
  • D. Provided the snapshot has the modify size attribute set as true

Answer: A

Explanation:
A user can always create a new EBS volume of a higher size than the original snapshot size. The user cannot create a volume of a lower size. When the new volume is created the size in the instance will be shown as the original size. The user needs to change the size of the device with resize2fs or other OS specific commands.


NEW QUESTION # 203
A company is migrating an application to AWS that runs on a single Amazon EC2 instance. Because of licensing limitations, the application does not support horizontal scaling. The application will be using Amazon Aurora for its database.
How can the DevOps Engineer architect automated healing to automatically recover from EC2 and Aurora failures, in addition to recovering across Availability Zones (AZs), in the MOST cost-effective manner?

  • A. Assign an Elastic IP address on the instance. Create a second EC2 instance in a second AZ. Create an Amazon CloudWatch Events rule to trigger an AWS Lambda function to move the Elastic IP address to the second instance when the first instance fails. Use a single-node Aurora instance.
  • B. Create an EC2 instance and enable instance recovery. Create an Aurora database with a read replica in a second AZ, and promote it to a primary database instance if the primary database instance fails.
  • C. Create an Amazon CloudWatch Events rule to trigger an AWS Lambda function to start a new EC2 instance in an available AZ when the instance status reaches a failure state. Create an Aurora database with a read replica in a second AZ, and promote it to a primary database instance when the primary database instance fails.
  • D. Create an EC2 Auto Scaling group with a minimum and maximum instance count of 1, and have it span across AZs. Use a single-node Aurora instance.

Answer: C

Explanation:
Explanation/Reference:


NEW QUESTION # 204
A Development team is working on a serverless application in AWS. To quickly identify and remediate potential production issues, the team decides to roll out changes to a small number of users as a test before the full release. The DevOps Engineer must develop a solution to minimize downtime and impact. Which of the following solutions should be used to meet the requirements?
(Select TWO.)

  • A. Create an ELB Network Load Balancer with two target groups. Set up the Network Load Balancer for Amazon API Gateway private integration Associate one target group with the current version and the other target group with the new version. Configure the load balancer to route 10% of incoming traffic to the new version. As the new version becomes stable, detach the old version from the load balancer.
  • B. Create a rollover record set in AWS Route 53 pointing to the AWS Lambda endpoints for the old and new versions. Configure Route 53 to route 10% of incoming traffic to the new version. As the new version becomes stable, update the DNS record to route all traffic to the new version.
  • C. Create an Application Load Balancer with two target groups. Set up the Application Load Balancer for Amazon API Gateway private integration. Associate one target group to the current version and the other target group to the new version. Configure API Gateway to route 10% of incoming traffic to the new version. As the new version becomes stable, configure API Gateway to send all traffic to the new version and detach the old version from the load balancer.
  • D. In Amazon API Gateway, create a canary release deployment by adding canary settings to the stage of a regular deployment. Configure API Gateway to route 10% of the incoming traffic to the canary release. As the canary release is considered stable, promote it to a production release
  • E. Create an alias for an AWS Lambda function pointing to both the current and new versions.
    Configure the alias to route 10% of incoming traffic to the new version. As the new version is considered stable, update the alias to route all traffic to the new version.

Answer: A,D


NEW QUESTION # 205
......

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