An Introduction to Cloud Computing

Seattle UniversityCourse-Computing SystemProfessor-Dr. Yingwu Zhu

By Navsimrat KaurPooja SinghalSangeetha Codla Diwakar

Outline

Introduction Key Characteristics and Benefits of Cloud Different Cloud Service Models Case Study A: Amazon EC2 - Pooja Case Study B: Google App Engine - Navi Case Study C: Microsoft Azure - Sangeetha Current Issues and Limitations of Cloud Summary References

What is Cloud Computing

Cloud computing is a technology that uses the internet and central remote servers to maintain data and applications.

It provides on demand resources and services over the internet with the power of scalability and reliability.

Key Characteristics and Benefits

Economy: The most frequent reason cited was that the cloud wins in cost. Zero Upfront Infrastructure Cost Pay as per Use

Time: Just in time Infrastructure

Elasticity : Scale up, scale down, on-demand – Improved Testability, Experimentation

Better Resource Utilization

Potential for shrinking the Processing Time

Overflow the traffic to Cloud

http://www.dotcominfoway.com/technology/cloud-computing

Different Cloud Service Models

http://hrushikeshzadgaonkar.wordpress.com/

3 Building Blocks

SaaS: on-demand software delivery model in which software and its associated data are hosted centrally on a cloud and are typically accessed by users using a client, normally using a web browser over the Internet.

*Allows users to run existing online applications

PaaS: This includes hardware (servers, networks, load balancers etc) and software (operating systems, databases, application servers etc). There are a number of PaaS providers including Google App Engine, Microsoft Azure and Salesforce.com’s Force.com.

*Allows User to create their own cloud applications using supplier specific tools and languages.

IaaS: This includes hardware (servers, networks, load balancers etc) and software (operating systems, databases, application servers etc).

*Allows Users to run any application they please on cloud hardware of their choice

Case Study C

CASE STUDY 1 – Amazon EC2

Amazon EC2

EC2: Amazon Elastic Compute Cloud is a web service that provides resizable compute capacity in the cloud. It is designed to make web scale computing easier for developers.

Gives a virtual instance of the machine on the cloud to host and run applications on the virtual instance.

Uses XEN Para-Virtualization Architecture

XEN Para-Virtualization Architecture

http://tr.opensuse.org/An_Introduction_to_Virtualization

Amazon Machine Images: Contains all the information necessary to boot instances of user’s software. It is also possible to use templated images that are already available for usage and allow instance usage of EC2

Amazon EC2 Instance: The running system based on AMI is referred to as an instance.

Amazon Elastic Block Store: offers persistent storage for EC2 Instances. Designed to protect data by automatically creating replicas. EC2 instances can be stopped and restarted.

Elastic Load Balancing: Automatically distributes incoming application traffic across multiple Amazon EC2 instances.

Auto Scaling: Automatic Scaling up/down of EC2 Instances, provided by Amazon Cloud Watch.

Amazon EC2 Core Features

Amazon EC2 Functionality

Select a pre-configured, templated image to get up and running immediately. (Or Configure a new AMI)

Configure security and network access on Amazon EC2 instance. Choose instance type(s) and operating system. Start, terminate, and monitor instances of AMI as per need Determine whether want to run in multiple locations, utilize static IP

endpoints, or attach persistent block storage to your instances. Pay only for the resources that are actually consumed

Amazon EC2 Demo

Amazon EC2 Failure: Analysis

On April 21st 2011, an Amazon’s Data Center failure in Northern Virginia caused dozens of popular websites to be out of service for a considerable amount of time.

Affected: Foursquare , Reddit, Hootsuite, Quora, many other companies Unaffected: Netflix, SimpleGeo, SmugMug

What really happened? Amazon Engineers were attempting to upgrade primary EBS networks,

accidentally routed some traffic to a backup network with insufficient capacity A large number of EBS nodes lost their connection to the replicas they had

created, causing them immediately look for somewhere to make their replicas. Instances which were trying to read/write these volumes also get stuck. In order to stabilize and restore EBS cluster, all control APIs were disabled in the

affected Availability zone giving rise to unavailability of service. Amazon team took 12 hours to control Replication Storm Took much more then that to recover Customer’s data, 0.07% EBS volumes

were unrecoverable.

Amazon EC2 Failure:

Lessons Learned Better Communication with Clients in Crisis:

Amazon Harshest Criticism : Lack of any response for more than 40 minutes

Incident showed weaknesses of a cloud, also highlights liabilities in those who have become totally dependent upon Clouds.

Cloud is still maturing and evolving. Don’t store data on Instance or if store then back it up frequently. Also make

an AMI of your instance for easy recreation or cloning. Design your systems keeping Cloud in mind: Each component (EC2

Instance) should be able to die without affecting the whole system. Netflix uses Chaos Monkey (set of Scripts) that runs through AWS

processes and occasionally shuts them down to ensure that rest of the system is able to keep running. Also, uses Amazon’s Cloud Redundant Backup Infrastructure.

Pay Model: Free Tier

Pay Model: On Demand Instances

Pay Model: Reserved Instances

SO What’s SO Amazing in Amazon EC2?

Elastic Completely Controlled Flexible Reliable Secure Designed to use with other Web Services Inexpensive

Case Study C

CASE STUDY 2 – Google App Engine

Overview Run your application on Google infrastructure. Build your app using

JVM bases interpreter or compiler. Python Go

Applications build on Google infrastructure are Easy to build, maintain and scale.

User has a choice either the app to be served by free domain appspot.com or he can his own domain name.

Starting package is free 10 applications 500 mb storage 5 million page views per month

High Level Architecture

http://www.byteonic.com/2009/why-java-is-a-better-choice-than-using-python-on-google-app-engine/

How does it work?

Dynamic web serving Persistent storage Automatic scaling and load balancing APIs for user authentications and sending emails. Fully featured local development environment. Task queues Scheduled tasks Secure Environment

Sandbox Sandbox isolates the application from operating system, hardware and physical

location of the server in very secure and reliable way. This makes load balancing easy

DataStore

A powerful distributed data storage service. Grows with the amount of traffic.

Stores data objects as entities. An entity can have more than one property of different types. Create, update or delete happens in a transaction.

Entity can belong to entity groups also which are defined as hierarchy of relationships between entities.

Uses optimistic concurrency

Types of Datastore

High Replication datastore Synchronous Highly available and reliable Available for reads and writes during planned downtime also Data replicated using Paxos algorithm. 3 times expensive than Master/Slave

Master/Slave datastore Asynchronous One datacenter is master at any given time for write queries. Therefore

offers strong consistency.

.

Services

Memcache When to use?

Speed up common datastore queries Session data, user preferences and frequently performed queries

When not to use? Values can expire unexpectedly from cache. Make sure that your

application runs normally if the value is suddenly not available. Quota

URL Fetch Communicate with other hosts using http or https requests. URL to be fetched can use any port in the range : 80-90,440-450 and 1024-

65535. Fetch can use any of GET,POST,PUT, HEAD and DELETE. A request handler cannot call its own URL. Default deadline for response for URL fetch is 5 seconds and maximum is

10 seconds for online and 10 minutes for offline. Supports both synchronous and asynchronous requests. Quota

Mail Sending emails

The message to be sent is queued and call returns immediately. Mail service contact each recipient’s mail server, delivers the message

and retries if the server was unavailable. If mail service fails in sending message, then error message is sent to

the address of the sender of the message. Receiving emails

Receive emails of the form string@appid.appspotmail.com Received as HTTP requests

Quota

BlobStore

Allows the app to serve data objects that can be upto 2 gigabytes in size. Useful for serving large files , e.g., Videos or image files or allowing users to

upload large files.

Cannot be modified once they are created. Quota

Capabilities & Images

Capabilities Detect outages and scheduled downtime.

Reduce downtime by detecting if capability is available or not.

Images Manipulate images(rotate, crop, resize) using Image service

Support JPEG, PNG,GIF,BMP,TIFF and ICO formats.

Channel

Creates a persistent API between application and Google servers.

http://code.google.com/appengine/docs/java/channel/overview.html

Channel Quota

OAuth

Protocol that allows a user to grant third party limited permission without the user to give his/her username or password to the third party.

Various steps between user and the service provider Consumer calls a web service to get request token for app. Redirection of user browser to authentication URL, user signs in and

tells Google accounts that consumer is authorized to access service on user’s behalf.

Consumer calls web service to get access token Consumer is authorized to call the service now.

Task Queues Apps perform tasks other than from the user requests, e.g., for some

background work. Efficient and powerful tool for background processing Push Queues

Configure a queue and add tasks to it. App engine takes care of rest.

Easy to implement but restricted to use within app engine. Pull Queues

Best choice if using a different system to consume tasks. Task consumer leases specific number of tasks from the queue and

is responsible for deleting it afterwards. Gives more flexibility and control over when and where tasks will be

processed. Quota

Users, Multitenancy and XMPP

Authenticate users Google accounts Google Apps domain OpenId()

One instance of an application servers many clients. XMPP: Send and receive messages to and from any XMPP compatible

chatting service , e.g. Google talk XMPP quota

Billing Model

http://code.google.com/appengine/docs/billing.html

CASE STUDY 3 – Microsoft Azure

Microsoft Azure Platform

The Windows Azure platform is a simple, reliable, and powerful Microsoft platform for creating cloud applications, online services, and websites.

Core products: Windows Azure SQL Azure Windows Azure Platform AppFabric

Windows Azure is the operating system that helps developers build, host and scale applications through Microsoft datacenters

Applications are run through internet accessible data centers.

Data stored on machines in a internet accessible data center.

Windows Azure

Windows Azure apps run in data centers accessed via internet

White Paper: Introducing windows azure

Main Components of Windows Azure

White Paper: Introducing windows azure

Compute: runs apps in the cloud. Storage: Stores data in the cloud.(Blobs, tables, queues) Fabric Controller: Deploys , monitors and manages the

apps in the cloud. Content Delivery Network: For faster access to the data

storage by maintaining cached copies of data. Connect: allows connection between on-premises

computers and applications.

Windows Azure Components

An application can have one or more instances of each of these roles.Web Roles – This makes it easy for web based applications. It has IIS configured within it. This is like front end.

So creating WCF, ASP.NET apps is easy.Worker Roles – For windows based code. This does not have IIS configured. Handles all processing like user interactions, video processing etc.

When user submits request for some task. That task can involve front end and back end tasks. Web role takes care of the front end tasks and it hands over the processing tasks to the Worker role.

VM Roles- Helps moving windows server apps to windows azure.

Application Roles

Submitting App to Azure

Submits App Config- tells platform how many instances of each

role (web, worker)to run. Fabric Controller – based on the config file info, creates

a VM for each instance.

Setting up a simple Azure Application

http://www.microsoft.com/windowsazure/getstarted/

Browser Output

Sample Application to store file data to Azure

Create a simple text file “myfile.txt” Create a console application in VS2010 Reference Microsoft Azure storage DLL. Create a blob (These are used for storage. They can

interact with storage as if they were a local system file). Set file reference to the blob. Upload file from local to blob. Get the URI of the blob. Now we can access data through this URI.

Current Problems/Limitations of Cloud

EC2 Limitations Not easy to recover if something goes wrong after creating instance. Random Loss of Instances Server Configuration Woes : Configuring, Running and Monitoring EC2 Instances

Azure Limitations Azure provides application level cloud computing not infrastructural cloud computing

like amazon. Can only select applications, no choice of OS. Security concerns: We can not be sure who has access to data. Learning curve: working with storage like blobs, tables, queues needs some

experience. Poor debugging and logging support for deployed applications Untested compared to Google and Amazon’s offerings.

App Engine Limitations Returns stale results in case of non ancestoral queries in High Replication Datastore. Data may be unavailable during planned downtime or failures in case of Master/Slave

data store.

Summary Cloud Computing Introduction, Benefits, Cloud Service Models Case study 1: Amazon EC2

EC2 Architecture EC2 Core Features and Functionality Demo of Launching an EC2 Instance April 2011 Failure Analysis and Lessons Learned Different Pay Models Highlights

Case study 2:Google AppEngine Overview High Level Architecture Data Stores

High Reliable Master/Slave

Services and Quotas Billing Model

Summary

Case study 3: Microsoft Azure Windows Azure Definition Main Components Roles

Web Roles Worker Roles VM Roles

Sample Applications: Hello World! Accessing file data.

Limitations

References

Google http://www.microsoft.com/windowsazure http://www.jackofallclouds.com/ http://aws.amazon.com/ec2/ http://cloud-computing.learningtree.com/tag/amazon-ec2/ White Paper on AWS Cloud Best Practices, 2010 By Jinesh Varia White Paper on Amazon EC2 on Red Hat Enterprise Linuxhttp://www.microsoft.com/en-us/cloud/developer/http://www.microsoft.com/en-us/cloud/developer/resource.aspx?resourceId=introducing-windows-azure&fbid=kRj7B2TdjLBhttp://www.microsoft.com/windowsazure/getstarted/http://www.microsoft.com/windowsazure/sdk/ http://kasunpanorama.blogspot.com/2010/07/understanding-cloud-computing-feel-easy.htmlhttp://code.google.com/appengine/docs/Google App engine paper by Alexander Zahariev Helsinki University of Technology

Team members contributions

Pooja – Amazon EC2 Navi – Google App Engine Sangeetha – Microsoft Azure