Google Cloud Platform Training by Experts
Our Training Process

Google Cloud Platform - Syllabus, Fees & Duration
Module 1: Overview Cloud & Google Cloud Platform
- Cloud overview & Characteristics
 - Cloud Service Model (IAAS, PAAS, SAAS)
 - Cloud Deployment Model (Public, Private, Hybrid)
 - Google Cloud Plateform (GCP) Infrastructure Overview
 - Create GCP Account & Console Overview
 - Organizations, Folder, Project, Resource & Billing
 - Google Cloud Architecture Framework
 
Module 2: Virtual Machines
- Compute Engine (VM): Types & Options
 - VM Instance Lifecycle & Common Operations
 - Machine Types & Compute Options (VCPU And Memory) In Compute Engine
 - Images & Snapshots
 - Disk Types: Local SSD, Persistent & Balanced
 
Module 3: Virtual Networks
- Virtual Private Cloud (VPC) & Types, Subnets
 - Ip Addresses (Public/Private), Nic
 - Routes & Route Table
 - Firewalls
 - Network Topology Options
 
Module 4: Cloud IAM
- IAM Basic: Authentication, Authorization & MFA
 - Roles, Members, Service Account, Policy
 - Resource Hierarchy
 - Cloud IAM Best Practices
 
Module 5: Data Storage Services
- Google Cloud Storage Overview & Structure
 - Storage Classes, Versioning & Lifecycle Policies
 - Cloud SQL For Database (MySQL, Postgresql and SQL Server)
 - Cloud Spanner: Fully Managed Relational DB
 - Cloud Datastore
 - Cloud Bigtable: NOSQL Big Data Service
 
Module 6: App Engine, Functions, Cloud Run
- App Engine: Serverless Web Apps
 - App Engine Environments: Standard Vs Flexible
 - Cloud Functions: Events & Triggers
 - Cloud Run: Serverless Containers
 
Module 7: Resource Management
- Cloud Resource Manager Overview
 - Quotas, Labels, Names & Billing
 
Module 8: Resource Monitoring
- Stackdriver: Cloud Monitoring & Logging
 - Logging, Error Reporting, Tracing, Debugging
 
Module 9: Interconnecting Networks
- Virtual Private Network (VPN) & Its Types
 - VPC Peering (Public & Private)
 - Cloud DNS, Cloud Interconnect & Cloud Router
 
Module 10: Load Balancing & Autoscaling
- Load Balancing Types: Internal, External, Global & Regional
 - Https, Network, SSL & TCP Load Balancers
 - Cross-Region and Content-Based Load Balancing
 - Autoscaling Policies & Configuration
 
Module 11: Google Kubernetes Engine
- Microservices, Containers, Docker & Kubernetes
 - GCP Kubernetes Engine (GKE), Understand the Relationship
 	Between Kubernetes
	
and Google Kubernetes Engine (GKE) - Kubernetes Architecture : Clusters, Node, Node Pools, Pods, Services
 - Deploy & Manage Workloads on GKE
 
Module 12: Maintenance & Monitoring
- Capacity Planning and Cost Optimization
 - Deployment, Monitoring and Alerting, And Incident Response
 - Monitoring and Alerting
 
Module 13: Cloud Migrations
- Understanding Migration Used Cases
 - Understanding Migration Tools and Process
 
This syllabus is not final and can be customized as per needs/updates
			
													
												
							
		
								
							
			 The structure of Google's VMs allows them to be transferred without halting.  architecture; provide a complete set of data analytics workloads, ranging from data warehousing to streaming to business intelligence; allow clients to operationalize machine learning; enable smart open-source technologies to provide flexibility and options, and fabricate for businesses of any size.  Security scanners, administration and command centers, threat detection tools, binary authorization settings, and information loss prevention instruments are all part of the architecture.  Our professionals will teach you about Google's worldwide infrastructure, network services, storage goods, compute services, availability zones, and cloud services.  Because Google has the greatest data sets, it can train its machine literacy models with a lot more data than any other firm, pushing the foundries for perfection and performance, for example in assessing photos, written text, language, and facial recognition. js, Python, Java, Net, and Go programming. 
Our Google Cloud Training Trivandrum strives to provide high-quality instruction that practically covers fundamental concepts.  Google Cloud supports Ruby or Node.  Users can simply demand that they be charged for the computing time they use, and they will be eligible for lucrative discount rates for long-running workloads.  It offers a comprehensive set of IAAS, PAAS, and CAAS services.