Fault%20Tolerance%20Design%20Techniques

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An Introduction to Cloud Computing
Seattle UniversityCourse-Computing
SystemProfessor-Dr. Yingwu ZhuBy Navsimrat
KaurPooja SinghalSangeetha Codla Diwakar
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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

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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.

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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

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http//www.dotcominfoway.com/technology/cloud-comp
uting
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Different Cloud Service Models
http//hrushikeshzadgaonkar.wordpress.com/
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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.coms 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

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Case Study C
CASE STUDY 1 Amazon EC2
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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

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XEN Para-Virtualization Architecture
http//tr.opensuse.org/An_Introduction_to_Virtuali
zation
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Amazon EC2 Core Features

• Amazon Machine Images Contains all the
  information necessary to boot instances of users
  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.

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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

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Amazon EC2 Demo
Lets Launch an EC2 Instance
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Amazon EC2 Failure Analysis

• On April 21st 2011, an Amazons 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 Customers
  data, 0.07 EBS volumes were unrecoverable.

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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.
• Dont 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 Amazons Cloud
  Redundant Backup Infrastructure.

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Pay Model Free Tier
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Pay Model On Demand Instances
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Pay Model Reserved Instances
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SO Whats SO Amazing in Amazon EC2?

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

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Case Study C
CASE STUDY 2 Google App Engine
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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

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

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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

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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.
• .

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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

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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

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Mail

• Sending emails
• The message to be sent is queued and call
  returns immediately.
• Mail service contact each recipients 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_at_appid.appspotmai
  l.com
• Received as HTTP requests
• Quota

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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

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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.

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Channel

• Creates a persistent API between application and
  Google servers.

http//code.google.com/appengine/docs/java/channel
/overview.html
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Channel Quota
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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
  users behalf.
• Consumer calls web service to get access token
• Consumer is authorized to call the service now.

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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

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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

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Billing Model
http//code.google.com/appengine/docs/billing.html
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CASE STUDY 3 Microsoft Azure
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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

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Windows Azure

• 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.

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Windows Azure apps run in data centers accessed
via internet
White Paper Introducing windows azure
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Main Components of Windows Azure
White Paper Introducing windows azure
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Windows Azure Components

• 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.

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Application Roles

• 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.

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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.

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Setting up a simple Azure Application

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

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Browser Output
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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.

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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 Amazons
  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.

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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 2Google AppEngine
• Overview
• High Level Architecture
• Data Stores
• High Reliable
• Master/Slave
• Services and Quotas
• Billing Model

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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

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References

• Google ?
• http//www.microsoft.com/windowsazure
• http//www.jackofallclouds.com/
• http//aws.amazon.com/ec2/
• http//cloud-computing.learningtree.com/tag/amazo
  n-ec2/
• White Paper on AWS Cloud Best Practices, 2010 By
  Jinesh Varia
• White Paper on Amazon EC2 on Red Hat Enterprise
  Linux
• http//www.microsoft.com/en-us/cloud/developer/
• http//www.microsoft.com/en-us/cloud/developer/res
  ource.aspx?resourceIdintroducing-windows-azurefb
  idkRj7B2TdjLB
• http//www.microsoft.com/windowsazure/getstarted/
• http//www.microsoft.com/windowsazure/sdk/
• http//kasunpanorama.blogspot.com/2010/07/underst
  anding-cloud-computing-feel-easy.html
• http//code.google.com/appengine/docs/
• Google App engine paper by Alexander Zahariev
  Helsinki University of Technology

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Team members contributions

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

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Thanks