AWS - Certified DevOps Engineer Professional Training in Mumbai, India
Course Highlights
Training Mode
Classroom and Online
Learning Method
Lecture & Self-Study
Duration
1 Months
Training Hours
2 Hours per day
Hands on Labs (Physical Devices)
Yes
Study Material
Yes
Certificate
Yes
Batches
Weekdays (Mon-Fri) & Weekend (Sat-Sun)
Price
Enquire now
AWS - Certified DevOps Engineer Professional - Course Overview
The most reliable institute for AWS Certified DevOps Engineer Professional Training in Mumbai, Octa Networks provides Certified, passionate and experienced faculties who mentor, guide and train students and professionals towards achieving this certification. AWS Certified DevOps Engineer Professional Training Students can opt for the convenient method of training delivery as per their convenience.
Octa Networks provides AWS Certified DevOps Engineer Professional course in Mumbai Centre using AWS products and solutions in AWS Certified DevOps Engineer Professional lab Facility which is available 24x7. AWS Certified DevOps Engineer Professional syllabus is designed to validate skillsets related to Provisioning, operating, managing AWS environments.
AWS - Certified DevOps Engineer Professional - Course Details
Course Duration
- 1 month of Instructor-led classroom training
- 1 month of instructor-led online training
Who should enroll?
- Anyone having Diploma, BA, BCOM, BSC, BE or BCA Degree
- Architects
- IT Managers
- Software Developers
- Project Managers
What you'll learn in this course?
In this AWS Certified DevOps Engineer – Professional certification course, you will learn:
- SDLC Automation
- Configuration Management and Infrastructure-as-a-Code
- Monitoring and Logging
- Policies and Standards Automation
- Incident and Event Response
- Fault Tolerance and Disaster Recovery
What is AWS Certified DevOps Engineer Professional - Course Curriculum?
Octa Networks have designed the course curriculum for AWS Certified DevOps Engineer Professional in alignment with the guidelines provided for DOP-C01 Certification.
Prerequisite:
We recommend that attendees of this AWS DevOps certification course have the following prerequisites:
- Working knowledge of DevOps and Amazon Web Services
- Familiarity with AWS Development or AWS System Administration
- Working knowledge of one or more high-level programming languages, such as C#, Java, PHP, Ruby, or Python
- Intermediate knowledge of administering Linux or Windows systems at the command-line level
- Working experience with AWS using both the AWS Management Console and the AWS Command Line Interface (AWS CLI)
Training Outline:
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1.1 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
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1.2 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
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1.3 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
- Integrate tests with pipeline
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1.4 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
- Run a code build process
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1.5 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
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2.1 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
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2.2 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
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2.3 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
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2.4 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
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2.5 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
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3.1 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)
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3.2 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
- 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
-
3.3 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
-
3.4 Determine how to implement tagging and other metadata strategies
- Segregate authority based on tagging (lifecycle stages – dev/prod) with Condition contextkeys
- 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
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4.1 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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4.2 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
- Measure and automate cost optimization through events
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4.3 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
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5.1 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
- Determine the best way to restore operations after a failure occurs
- Investigate and correlate logged events with application components
-
5.2 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
-
5.3 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
-
5.4 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
-
6.1 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)
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6.2 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
-
6.3 Determine the right services based on business needs (e.g., RTO/RPO, cost)
- Determine cost-effective storage solution for your application
- Choose a database platform and configuration to meet business requirements
- Choose a cost-effective compute platform based on business requirements
- Choose a deployment service/model based on business requirements
- Determine when to use managed service vs. self-managed infrastructure (Docker on EC2 vs. ECS)
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6.4 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
-
6.5 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
What Devices are used during Hands-on Labs?
The hands-on labs will touch upon the below major services and concepts:
- Regions and Availability Zones
- VPC (Virtual Private Cloud)
- Private Subnet / Public Subnet
- Security Groups / NACL (Network Access Control Lists)
- EC2 (Elastic Compute Cloud) / Launch Templates / AMIs
- ELB (Elastic Load Balancing) / ALB (Application Load Balancer)
- Auto-Scaling Groups
- S3 (Simple Storage Service)
- NAT Gateway
- VPC Gateway Endpoint
- RDS (Relational Database Service)
- Multi-AZ RDS Deployment
- SNS (Simple Notification Service)
What Jobs are available after the course?
- Cloud Architect
- Cloud Developer
- Cloud Systems Administrator
- Cloud DevOps Engineer
- Cloud Security Engineer
- Cloud Network Engineer
- Cloud Data Architect
- Cloud Consultant
Do you provide Placement Assistance, post completion of the training?
We are 100% committed to offer placement assistance to our students. Industry approved Resume Templates are provided to candidates as guidance to assist them in writing their resumes. We also provide students with FAQ interview questionnaire to help them prepare for their job interviews.
What is expected salary after AWS Certified DevOps Engineer Professional Training Course?
On an average a AWS Certified DevOps Engineer Professional with 3-5 years of experience gets salary in the range of INR 60,000 to 70,000 per month in India.
After AWS Certified DevOps Engineer Professional training course, what is the Next Step?
Learning never stops. We always recommend Solutions Architect Professional Lab training. There is huge demand for AWS Certified Solutions Architect Professionals in market. These training and certification will establish your authority as an industry expert and provide you better career opportunities in the market.
Exam
| Exam Name | Exam Code | Duration | Cost | Registration: |
|
AWS - DevOps Engineer Professional |
DOP-C01 |
3 Hours | 300 USD | Pearson VUE |
Training Plan & Schedule
Training Plan & Schedule
| AWS - Certified DevOps Engineer Professional Training | |||
|
Batch | Weekdays (Mon-Fri) | Weekend (Sat-Sun) |
|
Mode | Classroom / Online | Classroom / Online |
|
Hours | 2 Hours/Day | 4 Hours/Day |
|
Duration | 1 Month | 2 Months |
| Date | Course | Training Type | Batch | Register |
| 10 August 2020 | AWS - DevOps Professional | Classroom / Online | Weekdays (Mon-Fri) | Enquire now |
| 15 August 2020 | AWS - DevOps Professional | Classroom / Online | Weekend (Sat-Sun) | Enquire now |
| 24 August 2020 | AWS - DevOps Professional | Classroom / Online | Weekdays (Mon-Fri) | Enquire now |
| 29 August 2020 | AWS - DevOps Professional | Classroom / Online | Weekend (Sat-Sun) | Enquire now |
Student Reviews
Octanetwrks is great training institute for techi and have greate trainer. Thanks for arranging this session.
madhusudan kumar singh
Octa networks is the best networking team
Rashi Patole
It's a good institution for learning. I'm doing my ccie from here, and there teaching explanation is very helpful for understanding the concept in very simple way. Would suggest to my friends and colleagues.
Akhil Singh
Frequently Asked Question
Octa Networks provides AWS Certified DevOps Engineer Professional training in Mumbai. Octa Networks has AWS Certified DevOps Engineer Professional batches scheduled as per the convenience of the certification aspirants. Regular (Mon-Fri) classroom training takes 4 weeks or 40 hours.
AWS Certified DevOps Engineer Professional certificate is valid for three years. Valid certifications can be recertified by retaking the current associate certificate exams or professional certification exam in the respective tracks only. e.g. passing either the AWS Certified Solutions Architect - Professional exam for the Architect path or AWS Certified DevOps Engineer - Professional exam for the Developer or Operations path.
No. Candidates are no longer required to have a Professional-level certification before pursuing Professional-level certification. Similarly they are not required to have Foundational or Associate certification before pursuing Specialty certification.
The AWS Certified DevOps Engineer Professional Certification is the professional level certification which opens the doors of opportunities in the industry by improving the chances of getting hired by global companies. Successful completion of prestigious AWS Certified DevOps Enginner Professional Training and Certification enhances your job profile. It also validates participant’s proficiency in provisioning, operating and managing AWS environments.
The prime objective of the AWS Certified DevOps Engineer Professional training is to develop skilled professionals who can understand core AWS services, uses, and DevOps engineer role which can be put into practice across the globe. The average salary ranges from 3,00,000 – 4,00,000 INR.
AWS certifications are valid for three years. Recertification helps strengthen the overall value of AWS certification. Recertification validates the consistency and interest levels of an individual to the employers about his credentials covering the latest AWS knowledge, skills, and best practices.
