DASVM’s GCP course content is designed in reference with Google Cloud Certified - Professional Cloud Architect exam. The Cloud Architect course focuses on familiarizing new learners with the basic concepts and then moves on to build a deeper understanding of the Platform. You will learn how to manage GCP services such as compute services, database services, security services, networking services, IAM etc.
Course Objectives:
Upon completion of the Google Cloud architect course, you will be able to:
- Understand the Google Cloud Platform (GCP)
- Learn About GCP Services - Compute Services, Networking Services, Storage Services, Big Data and Artificial Intelligence Services, Tools and Operations
- Manage Google Cloud Platform with Console and Command Line
- Work with gcloud, gsutil, and other Command Line Tools
- Create static, dynamic, and cloud routes
- Use GCP firewall rules and demonstrate how to use VPC peering
- Handle traffic using autoscaling
- Set IAM Policy at different levels
- Work with KMS
- Demonstrate the use of Compute Engine and Virtual Machines
- Use Data Service Options in GCP
- Create Kubernetes cluster in GCP using GKE
- Demonstrate App Engine and Recall Cloud Functions
- Demonstrate the use of Cloud Source Repository
- Use cloud logging and monitoring services
- Use the Deployment manager
- Demonstrate how to use managed Services
Course content
Introduction to Google Cloud Platform
- Introduction to Cloud Computing
- Overview of Google Cloud Platform
- Useful Links and Documentation
- Google Cloud Platform Resource Overview : Compute
- Google Cloud Platform Resource Overview : Networking
- Google Cloud Platform Resource Overview : Storage
- Google Cloud Platform Resource Overview : Big Data and Artificial Intelligence
- Google Cloud Platform Resource Overview: Tools and Operations
Lab:
- Creating a Free Google Cloud Platform Account
- Navigating to Google Cloud Platform: Services and Products
Managing GCP
- Managing Google Cloud Platform with Console
- Managing Google Cloud Platform with Command Line
- Google Cloud SDK Installation
- Understand gcloud, gsutil, and other Command-Line Tools
- Google Cloud Platform Projects and Billings
- Understand GCP Projects
- Project User Roles
Lab:
- Getting Started with Google Web console
- Getting Started with Cloud Shell and gcloud
- Projects in the Cloud Console
Google Cloud Platform: Virtual Networks
- Global Footprint: Regions, Zones, and Edge Locations
- Virtual Private Cloud
- Cloud Load Balancing
- Virtual Private Network
Lab:
- GCP Load Balancing HTTP traffic
- VPC networking fundamentals
- VPN Gateway
Security & Identity Fundamentals
- Overview of IAM
- IAM Service Account
- Identity Aware Proxy (IAP)
- Cloud KMS
Lab:
- IAM Custom Roles
- IAP Demo
- Service Account in GCP
- Getting started with KMS
Compute Services
- Compute Engine and Virtual Machines
- Machine types in Compute Engines
- compute options
- Disk options
- Advanced options in compute engine
Lab:
- Compute Engine Demo
- Creating a auto-scaled Managed Instance Groups
- Snapshots and Images Demo
Data Storage Services
- Data Service Options
- GCP Storage
- Cloud SQL
- Cloud Spanner
- Cloud Datastore and Cloud Firestore
- Cloud Bigtable
Lab:
- Cloud Spanner Demo
- Cloud Datastore Demo
- Cloud Bigtable Demo
- Cloud SQL Demo
- Cloud Storage Bucket Demo
Architecting with Google Kubernetes Engine
- Monolithic and Microservice Architecture
- Containers
- Docker
- Kubernetes
- Google Kubernetes Engine
- Helm Package Manager
Lab:
- Container Registry Demo
- GKE Demo
- Deploying a Memcached service to GKE
Application Development
- Compute Service and App Engine
- Cloud Function
- Cloud Run
- Cloud VMware Engine
Lab:
- Deploying an Application in Google App Engine
- Using Cloud Functions
- Using Cloud Run
DevOps
- Introduction to DevOps
- Cloud Source Repository
- Jenkins with Google Cloud
- Cloud Logging Services
- Cloud Monitoring Service
Lab:
- Cloud Logging and Sinks
- Cloud Monitoring
- Cloud Source Repository
- Jenkins in GKE
Automation
- Cloud Resources
- Configuration
- Template
- Deployment Manager
Lab:
- Using Deployment Manager
Big Data and AI Services
- Managed Services
- Dataflow
- Pub/Sub
- BigQuery
- DataLab
Lab:
- Cloud Dataflow Demo
GCP Architect Cheat Sheet and Case Studies
- Cheat sheets for various GCP services
- Real world implementations of GCP in various Case Studies
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Course Prerequisites
- Firstly, a solid understanding of Cloud architecture, encompassing key concepts and components, serves as the bedrock for comprehending advanced topics.
- Secondly, participants should have a firm grasp of the fundamentals of Cloud Computing, ensuring familiarity with core principles and practices within the Cloud domain.
- Lastly, a basic understanding of virtualization, networking, and databases is required, as these elements play integral roles in the broader landscape of Cloud technology. This foundational knowledge forms the basis for a comprehensive and successful journey through the Google Cloud Certification Training.
Who can attend
The following professionals can go for this Google cloud course:
- Individuals looking to establish their credibility and value in the market as experienced Cloud Architects
- Professionals aspiring to clear the Google Cloud Certified Professional Cloud Architect exam
- System Administrators
- Cloud Professionals
- Solutions Architects
- Infrastructure Architects
- Site Reliability Engineers
- Technical Leads
Number of Hours: 40hrs
Certification
GCP Professional Cloud Architect (GCP PCA)
Key features
- One to One Training
- Online Training
- Fastrack & Normal Track
- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Virtual Live Experience
- Preparing for Certification
FAQs
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- Resume Modification
- Mock Interviews
- Video Tutorials
- Materials
- Real Time Projects
- Materials
- Preparing for Certification
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