Cloud platforms allow accessing of computing resources over a network. Services are divided into Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Popular cloud providers include Amazon Web Services, Microsoft Azure, Google App Engine, and Hadoop. Amazon EC2 offers IaaS through virtual machines created from Amazon Machine Images and configured with varying resources. Amazon S3 provides scalable object storage through a hierarchical bucket and object model. Hadoop is an open-source software platform that allows processing vast amounts of data across a distributed cluster in a reliable and scalable manner.

1. Cloud Platforms in
Industry

2. Cloud Computing
 Allow use of computing resources
 Services are delivered over the network
 Services are divided into:
 Infrastructure-as-a-Service (IaaS)
 Platform-as-a-Service (PaaS)
 Software-as-a-Service (SaaS)

3. Defining a Cloud
 no physical object
 an electronic structure
 server behave as
 one large storage space and processor
 server clusters can provide a cloud setup

4. Benefits of Cloud Hosting
 Elasticity
 Pay by use
 Self Service

5. Popular Providers
 Amazon Web Services
 Salesforce.com
 Microsoft Azure
 Google App Engine
 Hadoop
 Manjrasoft Aneka

6. Amazon Web Services(AWS)
 AWS is collection of Web services providing
 Compute power
 Storage
 Content delivery
 Services available in AWS ecosystem are:
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Compute service
Storage service
Communication service
Additional services

7. Amazon EC2
 Offers compute service and delivers IaaS
 EC2 deploy servers as virtual machines
 Signature features:
 Amazon Machine Image (AMI)
 EC2 instance and environment
 AWS CloudFormation
 AWS Elastic Beanstalk

8. Amazon Machine Image (AMI)
 Templates to create virtual machine
 Contains
 Physical file system layout : Amazon Ramdisk Image
 Predefined OS installed : Amazon Kernel Image
 AMI created stored in S3 bucket
 Product code can be associated for revenue

9. EC2 Instance
 Represent virtual machines
 Created by selecting
 No. of cores
 Computing power
 Installed memory
 Currently available configurations
 Standard instances
 Micro instances
 Cluster GPU instances
 EC2 instances can run by using
 Command line tools
 AWS console

10. EC2 Environment
 EC2 instances are executed in virtual environment
 EC2 environment is in charge of
 Allocating addresses
 Attaching storage volumes
 Configuring security

11. Amazon S3
 Amazon Simple Storage Service(S3) is distributed object
store.
 S3 provides services for data storage and information
management
 The components are:
 Buckets
 Objects

12. Amazon S3 Vs Distributed File System
 Storage is hierarchical
 Objects cannot be manipulated like standard files
 Content is not immediately available to users
 Request will occasionally fail

13. Features of S3
 Resource Naming
 Buckets
 Objects and meta data
 Access control and Security
 Advanced features

14. Google App Engine
Paas implementation
Distributed and scalable runtime environment
Usage can be metered

15. Components
Platform
Google AppEngine
Google App
Engine
Runtime
Environment
Set of Scalable
Services
Google Storage
Google’s Infrastructure

16. Runtime Environment
 Sand Boxing
 Supported runtimes

17. Distributed Meme: Divide & Conquer
Specialized services
Memcache
URL Fetch
Mail
XMPP
Task Queue
Images
1
7
Datastore
Cron jobs
User Service

18. Hadoop
 Software platform that lets one easily write and run
applications that process vast amounts of data.
 It includes:
– MapReduce – offline computing engine
– HDFS – Hadoop distributed file system

19. What does it do?
 Implements Google’s MapReduce, using HDFS
 MapReduce divides applications into many small blocks
of work
 HDFS creates multiple replicas of data blocks for reliability,
placing them on compute nodes around the cluster
 MapReduce can then process the data where it is
located
 Hadoop ‘s target is to run on clusters of the order of
10,000-nodes

20. What Hadoop provides:
 Ability to read and write data in parallel to or from multiple
disks
 Enables applications to work with thousands of nodes and
petabytes of data
 A reliable shared storage and analysis system (HDFS and
MapReduce)
 Advantages :
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Scalable
Economical
Efficient
Reliable

21. Who uses Hadoop?

22. Presented By:
Aditi Rai
Annapurna Tiwari