- In the Google Cloud DevOps training program, you will learn to develop, deploy and monitor GCP services. During the training, you will learn to develop software delivery pipelines, streamline communication, spot bugs, deploy/monitor services, etc. Furthermore, you will learn about optimizing service performance and implementing service monitoring strategies. You will also learn about building and implementing CI/CD pipelines.
- Things you will learn:
- The Google Cloud DevOps training program is perfect for aspiring Google Cloud DevOps engineers who wish to become competent in building and managing services on GCP.
- Prerequisites:
- This course is for:
Defining SLO
How to manage the service life cycle
GCP fundamentals
Building CI/CD pipelines
How to configure secure storage methods
How to make changes in infrastructure safer and quicker
CI/CD tooling
Implementing service monitoring strategies
Basic computer knowledge
Basic knowledge of service life cycle
Passion for learning
Basic knowledge about GCP
Basic knowledge about implementing service monitoring strategies
GCP newbies
Aspiring Google Cloud DevOps engineers
Engineering graduates
GCP professionals who are looking to train for other roles
Students who want to clear the Google Cloud DevOps Engineer exam
- The Google Cloud DevOps training program will help you become an expert in applying site reliability engineering principles, managing service life cycle, managing service incidents, etc. Additionally, you will master all the skills that an expert Google Cloud DevOps engineer must possess.
- Our Google Cloud DevOps faculty will help you:
Provide quality Knowledge about GCP services
Make students expert in managing the service life cycle
Make students proficient in implementing service monitoring strategies
Help students understand how to build CI/CD pipelines
Prepare students so that they can easily clear the Google Cloud DevOps Engineer exam
Make students understand the responsibilities of a Google Cloud DevOps Engineer
Make students comfortable in configuring secure storage methods
Become comfortable in managing the service life cycle
Learn how to implement service monitoring strategies
Become an expert in building CI/CD pipelines
Help you understand the responsibilities of a Google Cloud DevOps Engineer
Become a competent Google Cloud DevOps Engineer
Easily clear the Google Cloud DevOps Engineer exam
Become an expert in applying site reliability engineering principles
Help you become an expert in managing server incidents
- Despite the slowdown in the economy and business world due to the Covid pandemic, a survey by Puppet shows that the salaries of Cloud DevOps engineers have increased all over the world. Similarly, as per the survey of job search sites like Monster and Naukri, a skilled Google Cloud DevOps engineer can earn a large sum of money for their services.
- As per Glassdoor, a Google Cloud DevOps engineer can earn approximately 7,00,000 per year as a fresher. In contrast to that, an experienced Google Cloud DevOps engineer can earn anywhere between 16,00,000 to 38,00,000 per year, depending upon his expertise in working with GCP and skills.
- By pursuing your career as a Google Cloud DevOps engineer, you can get access to lots of opportunities. Moreover, you will also earn a large sum of money for your services. For example, you may earn around 16 LPA to 38 LPA for your services.
- Roles that you can take after completing the Google Cloud DevOps engineer training program:
- As per various surveys conducted all over the world, the demand for skilled Google Cloud DevOps engineers is increasing in the market with each passing year. This is mainly because of the increase in the number of firms transferring their infrastructure to the cloud, and if experts are to be believed, then this trend is expected to continue in the upcoming years.
Google Cloud DevOps engineer
Google Cloud Professional
Contributor to the Google Cloud DevOps community
Train for roles like Google Cloud Architect, Google Cloud Associate, etc.
- A Cloud DevOps engineer helps a firm in building software delivery pipelines and ensuring that they are reliable and operational. Other than this, a Goggle Cloud DevOps engineer also helps a firm in deploying services on the GCP and implementing service monitoring strategies. This is the main reason why Google Cloud DevOps engineers are so popular among firms and are considered a vital asset of an organization.
- Here’s why Google Cloud DevOps engineers are so famous:
Mentor team members
Help an organization develop and implement service monitoring services
Manges services incidents
Manage the service life cycle
- The job of a Google Cloud DevOps engineer is not that easy. He performs lots of complex tasks and responsibilities in a company. For example, he develops software delivery pipelines and manages the service life cycle. He also helps its client in implementing service monitoring services. In short, the work of a DevOps engineer is not a kid’s play and requires one to have a respectable amount of knowledge about GCP and GCP services.
- Key responsibilities of a Google Cloud DevOps Engineer:
Implement reliability engineering principles to a service
Optimize service performance
Implement service monitoring strategies
Building/implementing CI/CD pipelines
Manage service incidents
Mentor team members
Develop secure storage methods
Manage service incidents
- The demand for competent DevOps engineers is huge in the market. This is because of the value that DevOps engineers add to an organization. This is the primary reason why companies that use cloud computing services are in constant search of skilled Google Cloud DevOps engineers. Moreover, this is the primary reason that DevOps engineers charge hefty money for their services.
- Top hiring companies for Google Cloud DevOps Engineers:
Saksoft Limited
Code Clouds
Acesoft Labs
FedEx
Suki
Accenture
- Once you submit all your assignments and complete your classes, you will be awarded a training certificate from Croma Campus. With the training certificate of Croma Campus, you can easily stand out from the crowd in front of employers and increase your chances of getting the job.
- Plus, you will get the following services once you complete the training program:
- Advantages of getting certification:
100% placement support
Interview grooming sessions
Resume preparation
Access to our portal (job portal)
Recognized certification
Hefty remuneration
Help you show your skills and expertise as a Google Cloud DevOps engineer
Hike in salary
Lots of job opportunities
Why Should You Do Google Cloud DevOps Engineer Training Program?
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Plenary for Google Cloud-Professional Cloud DevOps Engineer
Track | Week Days | Weekends | Fast Track |
---|---|---|---|
Course Duration | 40-45 Days | 7 Weekends | 8 Days |
Hours | 1 Hrs. Per Day | 2 Hrs. Per Day | 6+ Hrs. Per Day |
Training Mode | Classroom/Online | Classroom/Online | Classroom/Online |
Course Price at :
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Program Core Credentials
Trainer Profiles
Industry Experts
Trained Students
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Success Ratio
100%
Corporate Training
For India & Abroad
Job Assistance
100%
BATCH TIMINGS
Google Cloud-Professional Cloud DevOps Engineer Upcoming Batches
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CURRICULUM & PROJECTS
Google Cloud-Professional Cloud DevOps Engineer
- Balance change, velocity, and reliability of the service
Discover SLIs (availability, latency, etc.)
Define SLOs and understand SLAs
Agree to consequences of not meeting the error budget
Construct feedback loops to decide what to build next
Toil automation
- Manage service life cycle
Manage a service (e.g., introduce a new service, deploy it, maintain and retire it)
Plan for capacity (e.g., quotas and limits management)
- Ensure healthy communication and collaboration for operations
Prevent burnout (e.g., set up automation processes to prevent burnout)
Foster a learning culture
Foster a culture of blamelessness
- Design CI/CD pipelines
Immutable artifacts with Container Registry
Artifacts repositories with Container Registry
Deployment strategies with Cloud Build, Spinnaker
Deployment to hybrid and multi-cloud environments with Anthos, Spinnaker, Kubernetes
Artifacts versioning strategy with Cloud Build, Container Registry
CI/CD pipeline triggers with Cloud Source Repositories, Cloud Build GitHub App, Cloud Pub/Sub
Testing a new version with Spinnaker
Configure deployment processes (e.g., approval flows
- Implement CI/CD pipelines
CI with Cloud Build
CD with Cloud Build
Open source tooling (e.g. Jenkins, Spinnaker, Git Lab, Concourse)
Auditing and tracing of deployments (e.g., CSR, Cloud Build, Cloud Audit Logs)
- Manage configuration and secrets
Secure storage methods
Secret rotation and configuration changes
- Manage infrastructure as code
Terraform / Cloud Deployment Manager
Infrastructure code versioning
Make infrastructure changes safer
Immutable architecture
- Deploy CI/CD tooling
Centralized tools vs. multiple tools (single vs multi-tenant)
Security of CI/CD tooling
- Manage different development environments (e.g., staging, production, etc.):
Decide on the number of environments and their purpose
Create environments dynamically per feature branch with GKE, Cloud Deployment Manager
Local development environments with Docker, Cloud Code, Scaffold
- Secure the deployment pipeline:
Vulnerability analysis with Container Registry
Binary Authorization
IAM policies per environment
- Manage application logs
Collecting logs from Compute Engine, GKE with Stackdriver Logging, Fluentd
Collecting third-party and structured logs with Stackdriver Logging, Fluentd
Sending application logs directly to Stackdriver API with Stackdriver Logging
- Manage application metrics with Stackdriver Monitoring
Collecting metrics from Compute Engine
Collecting GKE/Kubernetes metrics
Use metric explorer for ad hoc metric analysis
- Manage Stackdriver Monitoring platform
Creating a monitoring dashboard
Filtering and sharing dashboards
Configure third-party alerting in Stackdriver Monitoring (i.e., Pager Duty, Slack, etc.)
Define alerting policies based on SLIs with Stackdriver Monitoring
Automate alerting policy definition with Cloud DM or Terraform
Implementing SLO monitoring and alerting with Stackdriver Monitoring
Understand Stackdriver Monitoring integrations (e.g., Grafana, BigQuery)
Using SIEM tools to analyze audit/flow logs (e.g., Splunk, Data dog)
Design Stackdriver Workspace strategy
- Manage Stack Driver Logging platform
Enabling data access logs (e.g., Cloud Audit Logs)
Enabling VPC flow logs
Viewing logs in the GCP Console
Using basic vs. advanced logging filters
Implementing logs-based metrics
Understanding the logging exclusion vs. logging export
Selecting the options for logging export
Implementing a project-level / org-level export
Viewing export logs in Cloud Storage and BigQuery
Sending logs to an external logging platform
- Implement logging and monitoring access controls:
Set ACL to restrict access to audit logs with IAM, Stack driver Logging
Set ACL to restrict export configuration with IAM, Stack driver Logging
Set ACL to allow metric writing for custom metrics with IAM, Stack driver Monitoring
- Identify service performance issues
Evaluate and understand user impact (Stackdriver Service Monitoring for App Engine, Istio)
Utilize Stackdriver to identify cloud resource utilization
Utilize Stackdriver Trace/Profiler to profile performance characteristics
Interpret service mesh telemetry
Troubleshoot issues with the image/OS
Troubleshoot network issues (e.g., VPC flow logs, firewall logs, latency, view network details)
- Debug application code:
Application instrumentation
Stackdriver Debugger
Stackdriver Logging
Stackdriver Trace
Debugging distributed applications
App Engine local development server
Stackdriver Error Reporting
Stackdriver Profiler
- Optimize resource utilization:
Identify resource costs
Identify resource utilization levels
Develop plan to optimize areas of greatest cost or lowest utilization
Manage pre-emptible VMs
Work with committed-use discounts
TCO considerations
Consider network pricing
- Coordinate roles and implement communication channels during a service incident:
Define roles (incident commander, communication lead, operations lead)
Handle requests for impact assessment
Provide regular status updates, internal and external
Record major changes in incident state (When mitigated When all clear etc.)
Establish communications channels (email, IRC, Hangouts, Slack, phone, etc.)
Scaling response team and delegation
Avoid exhaustion / burnout
Rotate / hand over roles
Manage stakeholder relationships
- Investigate incident symptoms impacting users
Identify probable causes of service failure
Evaluate symptoms against probable causes; rank probability of cause based on observed behavior
Perform investigation to isolate most likely actual cause
Identify alternatives to mitigate issue
- Mitigate incident impact on users:
Roll back release
Drain / redirect traffic
Turn off experiment
Add capacity
- Resolve issues (e.g., Cloud Build, Jenkins):
Code change / fix bug
Verify fix
Declare all-clear
- Document issue in a post-mortem:
Document root causes
Create and prioritize action items
Communicate post-mortem to stakeholders
- Tips to clear an Interview
- Common Interview questions and answers
- Google Professional Cloud DevOps Engineer Interview Questions and Answers
- Resume Building Guide
- Attempt for the Global Certification Exam
- Earn Credentials and Start applying for Jobs
+ More Lessons
Mock Interviews
Projects
Phone (For Voice Call):
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FAQ's
- Basic computer knowledge
- Basic knowledge of service life cycle
- Basic knowledge about GCP
- Passion for learning
- Basic knowledge about implementing service monitoring strategies
The Google Cloud DevOps enginner course can be completed in 35-45 days
You will learn from a skilled Google Cloud DevOps engineer
You can earn around ₹7,00,000 – ₹38,00,00 PA after completing the Google Cloud DevOps engineer training program
- - Build an Impressive Resume
- - Get Tips from Trainer to Clear Interviews
- - Attend Mock-Up Interviews with Experts
- - Get Interviews & Get Hired
If yes, Register today and get impeccable Learning Solutions!
Google Professional Cloud DevOps Engineer (GCP)
Google Professional Cloud DevOps Engineer (GCP) exam has been designed to test technical skills related to the job role. Candidates preparing for the exam should have hands-on experience.
Multiple Choice and Multi-Response Questions
Proctored Exam
$ 200 USD
120 Minutes
60 Questions
70% and above
Training Features
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The most traditional way to learn with increased visibility,monitoring and control over learners with ease to learn at any time from internet-connected devices.
Real-life Case Studies
Case studies based on top industry frameworks help you to relate your learning with real-time based industry solutions.
Assignment
Adding the scope of improvement and fostering the analytical abilities and skills through the perfect piece of academic work.
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