AWS Certified DevOps Engineer Professional exam basically validates technical expertise in provisioning, operating, and managing distributed application systems on the AWS platform. It validates an examinee’s ability to demonstrate aws training in chennai 

• Implement and manage continuous delivery systems and methodologies on AWS aws training in chennai 
• Implement and automate security controls, governance processes, and compliance validation aws training in chennai 
• Define and deploy monitoring, metrics, and logging systems on AWS
• Implement systems that are highly available, scalable, and self-healing on the AWS platform aws training in chennai 
• Design, manage, and maintain tools to automate operational processes

This course is designed to provide you with the knowledge and skills required to pass the AWS Certified DevOps Engineer – Professional exam and to successfully apply these skills in the workplace. aws devops training in chennai

Chapter 1 SDLC Automation (Domain 1)

1. CICD Overview aws training in chennai 
2. CodeCommit – Overview
3. CodeCommit – First Repo & HTTPS config
4. CodeCommit – clone, add, commit, push
5. CodeCommit – Branches and Pull Requests
6. CodeCommit – Securing the Repository and Branches
7. CodeCommit – Triggers & Notifications
8. CodeCommit – & AWS Lambda
9. CodeBuild – Overview aws devops training in chennai
10. CodeBuild – First Build aws devops training in chennai
11. CodeBuild – Docker, ECR & buildspec.yml
12. CodeBuild – Environment Variables & Parameter Store
13. CodeBuild – Artifacts and S3
14. CodeBuild – CloudWatch Events, CloudWatch Logs, CloudWatch Metrics & Triggers aws training in chennai 
15. CodeBuild – Validating CodeCommit Pull Requests
16. CodeDeploy – Introduction & Overview
17. CodeDeploy – Deployment Groups
18. CodeDeploy – Deployment Configurations
19. CodeDeploy – Hooks & Environment Variables
20. CodeDeploy – CloudWatch Events, CloudWatch Logs, CloudWatch Alarms, Triggers aws training in chennai 
21. CodeDeploy – Deploy to AWS Lambda
22. CodePipeline – Overview aws training in chennai 
23. CodePipeline – CodeCommit & CodeDeploy
24. CodePipeline – Adding CodeBuild
25. CodePipeline – Artifacts, Encryption and S3
26. CodePipeline – Manual Approval Steps
27. CodePipeline – CloudWatch Events Integration
28. CodePipeline – Stage Actions, Sequential & Parallel
29. CodePipeline – CloudFormation

Chapter 2 Configuration Management and Infrastructure as Code (Domain 2)

1. CloudFormation Overview
2. CloudFormation Parameters
3. CloudFormation Resources
4. CloudFormation Mappings
5. CloudFormation Outputs
6. CloudFormation Conditions
7. CloudFormation Intrinsic Functions
8. CloudFormation User Data
9. CloudFormation cfn-init
10. CloudFormation cfn-signal and wait conditions
11. CloudFormation cfn-signal failures troubleshooting
12. CloudFormation Rollbacks
13. CloudFormation Nested Stacks
14. CloudFormation ChangeSets
15. CloudFormation DeletionPolicy
16. CloudFormation TerminationProtection
17. CloudFormation – Stack Policies
18. Elastic Beanstalk – EB CLI
19. Elastic Beanstalk – Saved Configurations
20. Elastic Beanstalk – .ebextensions for configs
21. Elastic Beanstalk – .ebextensions for resources
22. Elastic Beanstalk – .ebextensions for commands & container commands
23. Elastic Beanstalk – Good Features to Know
24. Elastic Beanstalk – Rolling Updates Strategies
25. Elastic Beanstalk – Rolling Updates Hands On
26. Elastic Beanstalk – Swap URL (Blue / Green)
27. Elastic Beanstalk – Worker Environments
28. Elastic Beanstalk – Multi Docker Integration
29. Lambda – Overview
30. Lambda – Sources and Use Cases
31. Lambda – Security, Environment Variables, KMS and SSM
32. Lambda – Versions, Aliases and Canary Routing
33. Lambda – SAM Framework
34. Lambda – SAM and CodeDeploy

Chapter 3 Monitoring and Logging (Domain 3)

1. CloudTrail – Overview
2. CloudTrail – Log Integrity
3. CloudTrail – Cross Account Logging
4. Kinesis – Data Streams Overview
5. Kinesis – Data Firehose & Analytics Overview
6. Kinesis – Data Firehose Hands On
7. CloudWatch Metrics – Overview
8. CloudWatch Metrics – Metrics to Know
9. CloudWatch Metrics – Custom Metrics
10. CloudWatch Metrics – Exports
11. CloudWatch Alarms – Overview
12. CloudWatch Alarms – Billing Alarms
13. CloudWatch Logs – Console Overview
14. CloudWatch – Unified CloudWatch Agent Part I
15. CloudWatch – Unified CloudWatch Agent Part II
16. CloudWatch Logs – Metric Filters & Alarms
17. CloudWatch Logs – Export to S3
18. CloudWatch Events – Overview
19. CloudWatch Events – Integration with CloudTrail API
20. CloudWatch Events – vs S3 Events
21. CloudWatch Dashboards – Overview
22. X-Ray – Overview
23. X-Ray – DevOps automation
24. Amazon ES – ElasticSearch + Logstash + Kibana

Chapter 4 Policies and Standards Automation (Domain 4)

1. SSM – Overview & Quick Setup
2. SSM – EC2 Setup
3. SSM – On-Premise Setup
4. SSM – Automations
5. SSM – Session Manager & Cleanup
6. Config – Overview
7. Config – Rules
8. Config – Automations
9. Config – Multi Account
10. Service Catalog – Overview
11. Service Catalog – Hands On
12. Inspector – Setup & Run
13. Inspector – Automationsaws training in chennai 
14. EC2 Instance Complianceaws training in chennai 
15. Health – Service Health Dashboard & Personal Health Dashboard
16. Trusted Advisor – Overview
17. Trusted Advisor – Automations
18. Trusted Advisor – Automating Refreshesaws training in chennai 
19. GuardDuty – Overviewaws training in chennai 
20. GuardDuty – Automationsaws training in chennai 
21. Macie – Hands On
22. Secrets Manager – Hands On
23. License Manager – Hands On
24. Cost Allocation Tags
25. Data Protection & Network Protection in AWS

Chapter 5 & 6 Incident and Event Response (Domain 5) & HA, Fault Tolerance, and DR (Domain 6)

1. ASG – From Launch Configuration
2. ASG – From Launch Templates
3. ASG – Scheduled Actions
4. ASG – Scaling Policies
5. ASG – ALB Integration
6. ASG – HTTPS on ALB
7. ASG – Suspending Processes & Troubleshooting
8. ASG – Lifecycle Hooks
9. ASG – Termination Policies
10. ASG – Integration with SQS
11. ASG – Monitoringaws training in chennai 
12. ASG – CloudFormation CreationPolicy
13. ASG – CloudFormation UpdatePolicy
14. ASG – CodeDeploy Integration
15. ASG – CodeDeploy Integration Troubleshooting
16. ASG – Cleanup
17. ASG – Deployment Strategiesaws training in chennai 
18. DynamoDB – Review Part I
19. DynamoDB – Review Part II
20. DynamoDB – Patterns
21. S3 – Review
22. Multi AZ – Overview
23. Multi Region – Overview
24. StackSets – Warning
25. Multi Region – CloudFormation StackSets
26. Multi Region – CodePipeline
27. Disaster Recovery – Overview
28. Disaster Recovery – DevOps Checklist
29. On-Premise Strategies with AWSaws training in chennai 
30. Multi Account – AWS Organization Overview
31. Multi Account – AWS Organization Hands On
32. Multi Account – Services Integration

Sample Questions

1, You’ve been tasked with implementing an automated data backup solution for your application servers that run on Amazon EC2 with Amazon EBS volumes. You want to use a distributed data store for your backups to avoid single points of failure and to increase the durability of the data. Daily backups should be retained for 30 days so that you can restore data within an hour. How can you implement this through a script that a scheduling daemon runs daily on the application servers?

A) Write the script to call the ec2-create-volume API, tag the Amazon EBS volume with the current date time group, and copy backup data to a second Amazon EBS volume. Use the ec2-describe-volumes API to enumerate existing backup volumes. Call the ec2-delete-volume API to prune backup volumes that are tagged with a date-time group older than 30 days.

B) Write the script to call the Amazon Glacier upload archive API, and tag the backup archive with the current date-time group. Use the list vaults API to enumerate existing backup archives. Call the delete vault API to prune backup archives that are tagged with a date-time group older than 30 days.

C) Write the script to call the ec2-create-snapshot API, and tag the Amazon EBS snapshot with the current date-time group. Use the ec2-describe-snapshots API to enumerate existing Amazon EBS snapshots. Call the ec2-delete-snapshot API to prune Amazon EBS snapshots that are tagged with a date-time group older than 30 days.

D) Write the script to call the ec2-create-volume API, tag the Amazon EBS volume with the current date-time group, and use the ec2-copy-snapshot API to back up data to the new Amazon EBS volume. Use the ec2-describe-snapshot API to enumerate existing backup volumes. Call the ec2-delete-snaphot API to prune backup Amazon EBS volumes that are tagged with a date-time group older than 30 days.

2, You work for a startup that has developed a new photo-sharing application for mobile devices. Over recent months your application has increased in popularity; this has resulted in a decrease in the performance of the application due to the increased load. Your application has a two-tier architecture that is composed of an Auto Scaling PHP application tier and a MySQL RDS instance initially deployed with AWS CloudFormation. Your Auto Scaling group has a min value of 4 and a max value of 8. The desired capacity is now at 8 due to the high CPU utilization of the instances. After some analysis, you are confident that the performance issues stem from a constraint in CPU capacity, while memory utilization remains low. You therefore decide to move from the general-purpose M3 instances to the compute-optimized C3 instances. How would you deploy this change while minimizing any interruption to your end users?

A) Sign into the AWS Management Console, copy the old launch configuration, and create a new launch configuration that specifies the C3 instances. Update the Auto Scaling group with the new launch configuration. Auto Scaling will then update the instance type of all running instancesaws training in chennai 

B) Sign into the AWS Management Console and update the existing launch configuration with the new C3 instance type. Add an UpdatePolicy attribute to your Auto Scaling group that specifies an AutoScaling RollingUpdate.

C) Update the launch configuration specified in the AWS CloudFormation template with the new C3 instance type. Run a stack update with the new template. Auto Scaling will then update the instances with the new instance type.

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D) Update the launch configuration specified in the AWS CloudFormation template with the new C3 instance type. Also add an UpdatePolicy attribute to your Auto Scaling group that specifies an AutoScalingRollingUpdate. Run a stack update with the new template.

3, You have a complex system involving networking, IAM policies, and multiple, three-tier applications. You are still receiving requirements for the new system, so you don’t yet know how many AWS components will be present in the final design. You would like to start defining these AWS resources using AWS CloudFormation so that you can automate and version-control your infrastructure. How would you use AWS CloudFormation to provide agile new environments for your customers in a cost-effective, reliable manner?

A) Create one single template by hand to encompass all resources that you need for the system, so you only have a single template to version-control.

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B) Create multiple separate templates for each logical part of the system, create nested stacks in AWS CloudFormation and maintain several templates to version-control.

C) Create multiple separate templates for each logical part of the system, and provide the outputs from one to the next using an Amazon Elastic Compute Cloud (EC2) Instance running the SDK for finer granularity of control.

D) Manually construct the networking layer using Amazon Virtual Private Cloud (VPC) because this does not change often and then define all other ephemeral resources using AWS CloudFormation.

 

4,You have implemented a system to automate deployments of your configuration and application dynamically after an Amazon EC2 instance in an Auto Scaling group is launched. Your system uses a configuration management tool that works in a standalone configuration, where there is no master node. Due to the volatility of application load, new instances must be brought into service within three minutes of the launch of the instance operating system. The deployment stages take the following times to complete:

 

• Installing configuration management agent: 2mins
• Configuring instance using artifacts: 4mins
• Installing application framework: 15mins
• Deploying application code: 1min

 

What process should you use to automate the deployment using this type of standalone agent configuration?

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A) Configure your Auto Scaling launch configuration with an Amazon EC2 UserData script to install the agent, pull configuration artifacts and application code from an Amazon S3 bucket, and then execute the agent to configure the infrastructure and application.

B) Build a custom Amazon Machine Image that includes all components pre-installed, including an agent, configuration artifacts, application frameworks, and code. Create a startup script that executes the agent to configure the system on startup.

C) Build a custom Amazon Machine Image that includes the configuration management agent and application framework pre-installed. Configure your Auto Scaling launch configuration with an Amazon EC2 UserData script to pull configuration artifacts and application code from an Amazon S3 bucket, and then execute the agent to configure the system.

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D) Create a web service that polls the Amazon EC2 API to check for new instances that are launched in an Auto Scaling group. When it recognizes a new instance, execute a remote script via SSH to install the agent, SCP the configuration artifacts and application code, and finally execute the agent to configure the system.aws training in chennai