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Become an expert in monitoring and optimizing GCP apps. Enroll now to learn from a Google Cloud DevOps engineer.

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Course Duration

30 Hrs.

Live Project

2 Project

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Guaranteed

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Live Online /Self-Paced/Classroom

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250+

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  • 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:
    • 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

  • 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:
    • Basic computer knowledge

      Basic knowledge of service life cycle

      Passion for learning

      Basic knowledge about GCP

      Basic knowledge about implementing service monitoring strategies

  • This course is for:
    • 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

Google Cloud-Professional Cloud DevOps Engineer

About-Us-Course

  • 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.
    • 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

  • Our Google Cloud DevOps faculty will help you:
    • 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:
    • 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.

  • 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.

  • 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:
    • 100% placement support

      Interview grooming sessions

      Resume preparation

      Access to our portal (job portal)

  • Advantages of getting certification:
    • 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 :
24,75027,500
10% OFF Expires in00D:00H:00M:00S

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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

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  • 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

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  • 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

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  • 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

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  • 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

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  • 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
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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

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  • - Attend Mock-Up Interviews with Experts
  • - Get Interviews & Get Hired
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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.

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Format

Multiple Choice and Multi-Response Questions

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Type

Proctored Exam

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Cost

$ 200 USD

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Time

120 Minutes

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No of Questions

60 Questions

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Passing Score

70% and above

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