Google Cloud Platform Training by Experts

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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

Download Syllabus - Google Cloud Platform
This syllabus is not final and can be customized as per needs/updates
 
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Google Cloud Platform Jobs in Tampines

Enjoy the demand

Find jobs related to Google Cloud Platform in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Tampines, chennai and europe countries. You can find many jobs for freshers related to the job positions in Tampines.

  • Google Cloud Engineer
  • Product Manager -GCP service
  • GCP Engineer
  • Cloud Computing Trainee
  • Engagement Manager
  • Customer Engineer
  • Hybrid Cloud Specialist
  • SAP Sales Lead
  • Cloud Cybersecurity Engineer
  • Cloud Devops Architect

Google Cloud Platform Internship/Course Details

Google Cloud Platform internship jobs in Tampines
Google Cloud Platform This allows Google developers to tackle issues such as patches, software upgrades, and hardware repairs without having to shut down the system. Google's cloud administrations are open source, which aids with interoperability and conduct capability, both of which are critical to future-proofing engineering. js, Python, Java, Net, and Go programming. Google Cloud provides serverless analytics, allowing customers to concentrate solely on analytics. 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. Virtual machine migration is an integral aspect of any Cloud solution's upkeep. Google adheres to several international security standards to ensure that your data remains your data and that no one else may access it under any circumstances. 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. Security scanners, administration and command centers, threat detection tools, binary authorization settings, and information loss prevention instruments are all part of the architecture. The structure of Google's VMs allows them to be transferred without halting.

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