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Learn to develop secure and reliable GCP solutions. Join now and learn from a competent Google Cloud architect.

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Course Duration

30 Hrs.

Live Project

2 Project

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Google Cloud

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CURRICULUM & PROJECTS

Google Professional Cloud Architect Training Program

    Designing a solution infrastructure that meets business requirements. Considerations include:

    • Business use cases and product strategy
    • Cost optimization
    • Supporting the application design
    • Integration with external systems
    • Movement of data
    • Design decision trade-offs
    • Build, buy, or modify
    • Success measurements (e.g., key performance indicators [KPI], return on investment [ROI], metrics)
    • Compliance and observability

    Designing a solution infrastructure that meets technical requirements. Considerations include:

    • High availability and failover design
    • Elasticity of cloud resources
    • Scalability to meet growth requirements
    • Performance and latency

    Designing network, storage, and compute resources. Considerations include:

    • Integration with on-premises/multi-cloud environments
    • Cloud-native networking (VPC, peering, firewalls, container networking)
    • Choosing data processing technologies
    • Choosing appropriate storage types (e.g., object, file, RDBMS, NoSQL, New SQL)
    • Choosing compute resources (e.g., pre-emptible, custom machine type, specialized workload)
    • Mapping compute needs to platform products

    Creating a migration plan (i.e., documents and architectural diagrams). Considerations include:

    • Integrating solution with existing systems
    • Migrating systems and data to support the solution
    • Licensing mapping
    • Network planning
    • Testing and proof of concept
    • Dependency management planning

    Envisioning future solution improvements. Considerations include:

    • Cloud and technology improvements
    • Business needs evolution
    • Evangelism and advocacy
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    Configuring network topologies. Considerations include:

    • Extending to on-premises (hybrid networking)
    • Extending to a multi-cloud environment that may include GCP to GCP communication
    • Security and data protection

    Configuring individual storage systems. Considerations include:

    • Data storage allocation
    • Data processing/compute provisioning
    • Security and access management
    • Network configuration for data transfer and latency
    • Data retention and data life cycle management
    • Data growth management

    Configuring compute systems. Considerations include:

    • Compute system provisioning
    • Compute volatility configuration (preemptible vs. standard)
    • Network configuration for compute nodes

    Infrastructure provisioning technology configuration (e.g. Chef/Puppet/Ansible/Terraform/Deployment Manager)

    Container orchestration with Kubernetes

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    Designing for security. Considerations include:

    • Identity and access management (IAM)
    • Resource hierarchy (organizations, folders, projects)
    • Data security (key management, encryption)
    • Penetration testing
    • Separation of duties (SoD)
    • Security controls (e.g., auditing, VPC Service Controls, organization policy)
    • Managing customer-managed encryption keys with Cloud KMS

    Designing for compliance. Considerations include:

    • Legislation (e.g., health record privacy, children’s privacy, data privacy, and ownership)
    • Commercial (e.g., sensitive data such as credit card information handling, personally identifiable information [PII])
    • Industry certifications (e.g., SOC 2)
    • Audits (including logs)
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    Analyzing and defining technical processes. Considerations include:

    • Software development life cycle plan (SDLC)
    • Continuous integration / continuous deployment
    • Troubleshooting / post mortem analysis culture
    • Testing and validation
    • Service catalogue and provisioning
    • Business continuity and disaster recovery

    Analyzing and defining business processes. Considerations include:

    • Stakeholder management (e.g. influencing and facilitation)
    • Change management
    • Team assessment / skills readiness
    • Decision-making process
    • Customer success management
    • Cost optimization / resource optimization (capex / opex)

    Developing procedures to ensure resilience of solution in production (e.g., chaos engineering)

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    Advising development/operation team(s) to ensure successful deployment of the solution. Considerations include:

    • Application development
    • API best practices
    • Testing frameworks (load/unit/integration)
    • Data and system migration tooling

    Interacting with Google Cloud using GCP SDK (gcloud, gsutil, and bq). Considerations include:

    • Local installation
    • Google Cloud Shell
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    Monitoring/logging/profiling/alerting solution

    Deployment and release management

    Assisting with the support of solutions in operation

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Course Design By

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30 Hrs.
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Weekday1 Hr/Day
Weekend2 Hr/Day
Training ModeClassroom/Online
Flexible Batches For You
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    28-Jun-2025*

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    30-Jun-2025*

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    02-Jul-2025*

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  • flexible-focus-icon

    28-Jun-2025*

  • Weekend
  • SAT - SUN
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    30-Jun-2025*

  • Weekday
  • MON - FRI
  • Mor | Aft | Eve - Slot
  • flexible-white-icon

    02-Jul-2025*

  • Weekday
  • MON - FRI
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SELF ASSESSMENT

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Google Professional Cloud Architect Training Program

Category Associate
Exam Name: Google Professional Cloud Architect
Exam Code: PCA
Exam Duration: 120 Mins
Exam Format: Multiple Choice and Multiple Select Questions
Passing Score: 70% (Score not officially disclosed by Google)

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FAQ's

It validates your ability to design, develop, and manage secure, scalable cloud solutions on Google Cloud.

IT professionals, cloud architects, and system administrators aiming to work on Google Cloud Platform.

Basic knowledge of cloud computing and experience with GCP is recommended.

Typically 6–8 weeks, depending on the learning pace and course provider.

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