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Agenda
 Need of Cloud Computing
 What is Cloud Computing
 Cloud Services and Providers
 Why GCP
 What is GCP
 GCP Services
 GCP region and zones
 Advantage and disadvantage
 Use case
Traditional Method
• Concept of physical data centers
and the dependence of the
businesses that use these data
centers for the sake of storing their
digital assets and running a
complete networking system for
their day to day operations.
Problems Faced
Database & Security Managing Servers
Increasing Cost Fast & Fault Tolerant
Scalability Issue
Solution
CLOUD
COMPUTING
Database &
Security
Dynamically
Scalable Servers
Remote Access to
Devices Fast Computation
Reduced Cost & Overhead
 Cloud computing is the on-demand delivery of
compute power, database storage, applications,
and other IT resources through a cloud services
platform via the internet with pay-as-you-go pricing.
 It is the use of remote servers on the internet to
store, manage and process data rather than a local
server or your personal computer.
Cloud Computing
On-Premise
Cloud Services
Applications
Data
Runtime
Middleware
O/S
Virtualization
Servers
Storage
Networking
Infrastructure as a
Service (IaaS)
Applications
Data
Runtime
Middleware
O/S
Virtualization
Servers
Storage
Networking
Platform as a Service
(PaaS)
Applications
Data
Runtime
Middleware
O/S
Virtualization
Servers
Storage
Networking
Software as a Service
(SaaS)
Applications
Data
Runtime
Middleware
O/S
Virtualization
Servers
Storage
Networking
Managed by Customer Managed by Provider
Cloud Providers
Why GCP?
Google Cloud Platform, is a suite of cloud computing services that runs on the same
infrastructure that Google uses internally for its end-user products, such as Google
Google Search, Gmail, Google Photos and YouTube.
Why GCP?
Cost Effective Serverless
Highly Scalable
Custom Machine
Types
Big Data
Analytics
Cloud AI
Internet of Things API Platform and Ecosystem
What is GCP?
Google Cloud Platform, is a suite of cloud computing services and management tools offered by
Google alongside a set of management tools, it provides a series of modular cloud services including
computing, data storage, data analytics and machine learning.
Google Cloud Platform Services
Compute Storage & Database Networking Big Data Developer Tools
Identity & Security Internet of Things Cloud AI Management Tools Data Transfer
Google Cloud Platform Options
Google Service Google Service Description Features
Compute Engine Host your virtual machine in
Google’s IaaS
• Handles large scale.
• Easy and fast.
• Balances loads for optimum
performance.
App Engine Provides a PaaS model that
includes tools for building and
deploying in the cloud. It’s set
up to work with containerized
applications and includes SDKs
to get started.
• Variety of development tools.
• Built-in services.
• Options for storage.
• Supports popular services
and languages.
Container Engine Orchestrate Docker containerized
applications using Kubernetes.
This service offers single-click
clusters and integrated
monitoring.
• Leverage multi-zone and
regional clusters.
• Auto-updates.
• Integrates with monitoring
solutions.
Cloud Storage Store objects and files. • Simple API provided.
• Safe and secure.
• Cloud SQL
• Cloud Datastore.
GCP Regions and Zones
Advantage of GCP
 High productivity
 Quick collaboration
 Pricing
 Live Migration
 Highly Scalable
 Strong security
 Reliability
Disadvantage of GCP
 Very few customization
 Limited choice of programming languages
 Fewer global data centers
 Complex transition away from the platform to another vendor.
Use Case of GCP
If you’re a large organization that needs to set a lot of permissions while
working on projects, Google has an excellent organizational hierarchy that
allows you to set policy at the top level and forget it. This enables
departments to move fast yet remain bound to organizational constraint.
Another ideal use case for using GCP is for organizations that need the
benefits of advanced Big Data, machine learning and analytics
GCP.pptx

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GCP.pptx

  • 1.
  • 2. Agenda  Need of Cloud Computing  What is Cloud Computing  Cloud Services and Providers  Why GCP  What is GCP  GCP Services  GCP region and zones  Advantage and disadvantage  Use case
  • 3. Traditional Method • Concept of physical data centers and the dependence of the businesses that use these data centers for the sake of storing their digital assets and running a complete networking system for their day to day operations.
  • 4. Problems Faced Database & Security Managing Servers Increasing Cost Fast & Fault Tolerant Scalability Issue
  • 5. Solution CLOUD COMPUTING Database & Security Dynamically Scalable Servers Remote Access to Devices Fast Computation Reduced Cost & Overhead
  • 6.  Cloud computing is the on-demand delivery of compute power, database storage, applications, and other IT resources through a cloud services platform via the internet with pay-as-you-go pricing.  It is the use of remote servers on the internet to store, manage and process data rather than a local server or your personal computer. Cloud Computing
  • 7. On-Premise Cloud Services Applications Data Runtime Middleware O/S Virtualization Servers Storage Networking Infrastructure as a Service (IaaS) Applications Data Runtime Middleware O/S Virtualization Servers Storage Networking Platform as a Service (PaaS) Applications Data Runtime Middleware O/S Virtualization Servers Storage Networking Software as a Service (SaaS) Applications Data Runtime Middleware O/S Virtualization Servers Storage Networking Managed by Customer Managed by Provider
  • 9. Why GCP? Google Cloud Platform, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Google Search, Gmail, Google Photos and YouTube.
  • 10. Why GCP? Cost Effective Serverless Highly Scalable Custom Machine Types Big Data Analytics Cloud AI Internet of Things API Platform and Ecosystem
  • 11. What is GCP? Google Cloud Platform, is a suite of cloud computing services and management tools offered by Google alongside a set of management tools, it provides a series of modular cloud services including computing, data storage, data analytics and machine learning.
  • 12. Google Cloud Platform Services Compute Storage & Database Networking Big Data Developer Tools Identity & Security Internet of Things Cloud AI Management Tools Data Transfer
  • 13. Google Cloud Platform Options Google Service Google Service Description Features Compute Engine Host your virtual machine in Google’s IaaS • Handles large scale. • Easy and fast. • Balances loads for optimum performance. App Engine Provides a PaaS model that includes tools for building and deploying in the cloud. It’s set up to work with containerized applications and includes SDKs to get started. • Variety of development tools. • Built-in services. • Options for storage. • Supports popular services and languages.
  • 14. Container Engine Orchestrate Docker containerized applications using Kubernetes. This service offers single-click clusters and integrated monitoring. • Leverage multi-zone and regional clusters. • Auto-updates. • Integrates with monitoring solutions. Cloud Storage Store objects and files. • Simple API provided. • Safe and secure. • Cloud SQL • Cloud Datastore.
  • 16. Advantage of GCP  High productivity  Quick collaboration  Pricing  Live Migration  Highly Scalable  Strong security  Reliability
  • 17. Disadvantage of GCP  Very few customization  Limited choice of programming languages  Fewer global data centers  Complex transition away from the platform to another vendor.
  • 18. Use Case of GCP If you’re a large organization that needs to set a lot of permissions while working on projects, Google has an excellent organizational hierarchy that allows you to set policy at the top level and forget it. This enables departments to move fast yet remain bound to organizational constraint. Another ideal use case for using GCP is for organizations that need the benefits of advanced Big Data, machine learning and analytics

Editor's Notes

  1. Google Cloud Platform, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search, Gmail, Google Photos and YouTube
  2. Cost Effective : Pay per use Scalability : Highly Scalable (Auto Scalability) Customized: Custom Machine Types : Big Data Analytics : Fully managed data warehousing, batch and stream processing, data exploration, Hadoop/Spark, and reliable messaging API Platform and Ecosystem: Cross-cloud API platform enabling businesses to unlock the value of data, deliver modern applications, and power ecosystems. Internet Of Things: Intelligent IoT platform that unlocks business insights from your global device network Cloud AI: Fast, large scale and easy to use AI services. neural net-based ML service has better training performance andincreased accuracy compared to other large scale deep learning systems. Serverless : No upfront provisioning - Just provide your code and data, and Google dynamically provisions resources as needed. No management of servers. Applications with rapid time-to-market and unpredictable scale requirements benefit the most from Serverless