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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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- These days, the companies develop their software and strive to deliver the software rapidly. However, rapid delivery is only one feature; the software must be operational, secure, observable, and manageable. That's why DevOps skills become essential.
- Google Cloud provides multiple services to develop, test, deploy, monitor and manage the software. In fact, a DevOps engineer serves as a mediator between the development team and the operations team.
- The GCP DevOps Engineer Online Course describes how DevOps is implemented on Google Cloud Platform. The course focuses on such subjects as Continuous Integration, Continuous Delivery, application deployment, troubleshooting, monitoring, securing, containers, and software reliability.
- The Google Cloud Platform DevOps Engineer Course may prove beneficial for developers, cloud engineers, system administrators, DevOps engineers, and IT professionals wishing to study Google Cloud. Depending on a particular course, you will have an opportunity to learn Cloud Build, Cloud Deploy, Google Kubernetes Engine, Cloud Monitoring, and Cloud Logging services.
- The Google Cloud Platform Professional Cloud DevOps Engineer certification involves such fields as creation of CI/CD pipelines, Site Reliability Engineering (SRE), monitoring of systems, debugging, and performance tuning along with cost optimization. Google recommends having Google Cloud practical experience before taking this professional certification.
Google Professional Cloud DevOps Engineer Training
- In this GCP DevOps Engineer Online Course, learners can study:
- The Google Cloud DevOps Engineer Course focuses on practical work so learners can understand how software moves from code to testing, deployment, monitoring, and production support.
- Pre-Requisites
- There are no formal prerequisites for the Google Professional Cloud DevOps Engineer certification exam. However, learning becomes easier if you know:
- Beginners can start with cloud and DevOps basics before moving to advanced topics. For the professional certification, Google recommends real industry experience with Google Cloud.
Google Cloud and DevOps basics
DevOps lifecycle
Continuous Integration and Continuous Delivery
Cloud Build
Cloud Deploy
Google Kubernetes Engine
Containers and container deployment
Infrastructure and application delivery
Cloud Monitoring and Cloud Logging
Site Reliability Engineering
Incident management
Troubleshooting
Security and access management
Performance improvement
Cost optimization
Real project examples
Basic cloud concepts
Linux basics
Basic networking
Git and version control
Basic programming or scripting
Basic DevOps concepts
Containers and Kubernetes basics
- The following candidates can join the Google Cloud DevOps Engineer Training Classes:
- The course can be useful for both beginners and experienced professionals, but advanced certification preparation is better suited to learners who already have practical cloud experience.
Fresh IT graduates
Software developers
Cloud engineers
DevOps engineers
System administrators
Linux professionals
Cloud support engineers
Site reliability engineers
Infrastructure professionals
Working IT professionals
- Google Cloud and DevOps Basics:
- CI/CD Pipeline:
- Google Cloud's DevOps guidance highlights continuous integration and continuous delivery as important technical capabilities for reliable software delivery.
- Container and Kubernetes:
- Monitoring and Logging:
- Site Reliability Engineering:
- SRE is an important part of the current Professional Cloud DevOps Engineer certification scope.
- Security and Access:
- Performance and Cost:
- Google's current Professional Cloud DevOps Engineer exam also includes performance and cost optimization.
- Real Project Scenarios:
Understanding Google Cloud
Understanding DevOps
DevOps lifecycle
Source code and version control
Build and release process
Cloud-based development
Continuous Integration
Continuous Delivery
Automated builds
Automated testing
Deployment pipelines
Release management
Pipeline troubleshooting
Container basics
Container images
Google Kubernetes Engine
Application deployment
Kubernetes workloads
Scaling applications
Managing container-based services
Cloud Monitoring
Cloud Logging
Metrics and dashboards
Logs and alerts
Application monitoring
Finding system problems
Troubleshooting production issues
SRE basics
Service reliability
Service level concepts
Error budgets
Incident management
Reducing downtime
Learning from incidents
Identity and access basics
IAM
Secure deployment
Access control
Secret management concepts
Security checks in pipelines
Compliance basics
Application performance
Resource usage
Monitoring cloud workloads
Finding performance issues
Reducing unnecessary resource use
Understanding cloud costs
Creating a CI/CD pipeline
Deploying an application
Containerizing an application
Deploying workloads on GKE
Setting monitoring alerts
Finding a failed deployment
Handling a production incident
Improving application reliability
- The tools covered in the GCP DevOps Engineer Online Course can include:
- Google Cloud:
- Cloud Build:
- Cloud Deploy:
- Google Kubernetes Engine:
- Cloud Monitoring and Cloud Logging:
- Git and DevOps Tools:
- The exact tools used by a training provider can differ. Learners should check the current course lab list before enrolling.
Compute services
Cloud storage
IAM
Cloud networking
Cloud monitoring
Cloud logging
Automated builds
Build triggers
Testing
CI pipelines
Build automation
Delivery pipelines
Application releases
Deployment automation
Release management
Container orchestration
Application deployment
Cluster basics
Scaling
Workload management
Metrics
Logs
Dashboards
Alerts
Troubleshooting
Application visibility
Source control
Branch management
Code review
Build automation
Deployment workflows
- Following are some roles that professionals can take up after completing Google Professional Cloud DevOps Engineer Training:
- Google Cloud DevOps Engineer:
- Cloud Engineer:
- Site Reliability Engineer:
- DevOps Engineer:
- Cloud Support Engineer:
Build CI/CD pipelines
Manage application releases
Monitor cloud services
Troubleshoot deployment problems
Deploy cloud workloads
Manage cloud infrastructure
Configure access
Monitor cloud resources
Improve service reliability
Monitor production systems
Handle incidents
Find repeated system problems
Automate software delivery
Connect development and operations
Improve deployment processes
Manage DevOps tools
Check cloud issues
Monitor applications
Troubleshoot basic problems
Support cloud environments
- There is no definite salary range for a Google Cloud DevOps Engineer because it varies depending on experience, employer, place of work, position, cloud expertise, DevOps expertise, and other technical expertise.
- Rather than focusing on fixed salary figures, one should seek to find out from recent postings of the kind of position and level one seeks. Getting certified just shows what one knows and does not guarantee salary and position.
- Entry-Level Professionals:
- Possible work areas include:
- Mid-Level Professionals:
- Possible work areas include:
- Experienced Professionals:
- Possible work areas include:
Cloud support
Junior DevOps work
Application deployment support
Monitoring and testing
CI/CD pipeline management
Cloud infrastructure
Production support
Kubernetes deployments
Monitoring and incident handling
DevOps architecture
SRE practices
Production system management
Cloud automation
Reliability and cost improvement
- DevOps and Google Cloud skills can be used across different industries:
- Information Technology:
- Banking and Finance:
- E-commerce and Retail:
- Healthcare:
- Media and Entertainment:
- SaaS Companies:
- Consulting:
Cloud applications
CI/CD pipelines
Application support
Cloud infrastructure
Secure application delivery
Monitoring
Automation
Cloud infrastructure
Application deployment
Scaling
Monitoring
Release automation
Cloud applications
Data systems
Monitoring
Secure access
Application delivery
Cloud infrastructure
Automated deployments
Performance monitoring
Cloud applications
Continuous delivery
Kubernetes
Production monitoring
Cloud migration
DevOps implementation
CI/CD projects
Google Cloud solutions
- Module 1: Google Cloud and DevOps Introduction:
- Module 2: Source Control and Build:
- Module 3: CI/CD and Deployment:
- Module 4: Containers and GKE:
- Module 5: Monitoring and Logging:
- Module 6: SRE and Reliability:
- Module 7: Security and Optimization:
- Module 8: Real Project Scenarios:
Google Cloud basics
DevOps concepts
DevOps lifecycle
Cloud project basics
Git basics
Source code management
Cloud Build
Build triggers
Automated testing
CI/CD concepts
Deployment pipelines
Cloud Deploy
Release management
Deployment troubleshooting
Container concepts
Container images
Kubernetes basics
GKE
Application deployment
Cloud Monitoring
Cloud Logging
Metrics
Dashboards
Alerts
Troubleshooting
SRE concepts
Service reliability
Error budgets
Incident response
Production improvement
IAM
Secure deployments
Access control
Performance optimization
Cost optimization
Build a CI/CD pipeline
Deploy an application
Monitor a live workload
Fix deployment issues
Handle a production incident
Improve reliability
- The demand for cloud and DevOps skills has made these areas important for many software teams. Google Cloud's own certification material focuses on software delivery, SRE, monitoring, troubleshooting, performance, and cost optimization rather than only learning individual cloud services.
- After learning these skills, you can:
- The Google Professional Cloud DevOps Engineer Training can also be used as part of a certification preparation plan. Google provides an official learning path, exam guide, sample questions, and hands-on learning resources for the certification.
Understand how cloud applications are delivered.
Build and manage CI/CD pipelines.
Learn containers and Kubernetes deployment.
Monitor applications and cloud services.
Understand SRE and incident handling.
Work with Google Cloud DevOps tools.
Prepare for the Professional Cloud DevOps Engineer certification.
- You May Also Read:
Why Should You Do Google Cloud DevOps Engineer?
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CURRICULUM & PROJECTS
Google Professional Cloud DevOps Engineer Training Program
- 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 a service (e.g., introduce a new service, deploy it, maintain and retire it)
- Plan for capacity (e.g., quotas and limits management)
- Prevent burnout (e.g., set up automation processes to prevent burnout)
- Foster a learning culture
- Foster a culture of blamelessness
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- 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
- 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)
- Secure storage methods
- Secret rotation and configuration changes
- Terraform / Cloud Deployment Manager
- Infrastructure code versioning
- Make infrastructure changes safer
- Immutable architecture
- Centralized tools vs. multiple tools (single vs multi-tenant)
- Security of CI/CD tooling
- 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
- Vulnerability analysis with Container Registry
- Binary Authorization
- IAM policies per environment
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- 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
- Collecting metrics from Compute Engine
- Collecting GKE/Kubernetes metrics
- Use metric explorer for ad hoc metric analysis
- 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
- 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
- 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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- 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)
- Application instrumentation
- Stackdriver Debugger
- Stackdriver Logging
- Stackdriver Trace
- Debugging distributed applications
- App Engine local development server
- Stackdriver Error Reporting
- Stackdriver Profiler
- 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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- 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
- 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
- Roll back release
- Drain / redirect traffic
- Turn off experiment
- Add capacity
- Code change / fix bug
- Verify fix
- Declare all-clear
- Document root causes
- Create and prioritize action items
- Communicate post-mortem to stakeholders
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