Cloud Computing

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Cloud Computing
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Definition

• Cloud computing is a pay-per-use model for
  enabling available, convenient, on-demand network
  access to a shared pool of configurable computing
  resources (e.g., networks, servers, storage,
  applications, services) that can be rapidly
  provisioned and released with minimal management
  effort or service provider interaction. This
  cloud model promotes availability.

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What is cloud computing?

• I dont understand what we would do differently
  in the light of Cloud Computing other than change
  the wordings of some of our ads
• Larry Ellision, Oracles CEO
• I have not heard two people say the same thing
  about it cloud. There are multiple definitions
  out there of the cloud
• Andy Isherwood, HPs Vice President of European
  Software Sales
• Its stupidity. Its worse than stupidity its a
  marketing hype campaign.
• Richard Stallman, Free Software Foundation founder

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Business attributes

• Access resources from cloud of available
  computing resources
• Is always available and scales automatically to
  meet demand
• Is pay per use Based on resources consumed
• Enables full customer self-service
• Note Can be provided by 3rd party (e.g. Amazon)
  or on own network for v. large organisations
  (a.k.a private cloud)
• Acquire resources on demand
• Release resources when no longer needed
• Turns capital investment/fixed cost into
  operating costs/variable costs
• Reduced cost take advantage of economies of
  scale across users of cloud

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Technology attributes

• Access computing resources via Internet protocols
  from any computer
• Reduced system administration overhead automated
  provisioning
• Increased/matched reliability and security
• Acquire resources on demand
• Increased utilisation through sharing of
  resources through virtualisation or multi-tenancy
• To minimise the cost to the provider, clouds rely
  on a large number of commodity processors.
  These are cheaper to purchase and consumer less
  power per unit of processing when compared to
  high power processors
• No longer design deployment environment to meet
  maximum load

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The NIST Cloud Definition Framework
Deployment Models
Service Models
Essential Characteristics
Massive Scale
Resilient Computing
Homogeneity
Geographic Distribution
Common Characteristics
Based upon original chart created by Alex Dowbor
- http//ornot.wordpress.com
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The NIST Cloud Definition Framework

• OS Virtualisation leads directly to resilient
  computing, rapid elasticity and advanced security
• In case of VM based cloud, facilitates measured
  service as hypervisor tracks usage
• Multi-tenancy provides rapid elasticity

On Demand Self-Service
Essential Characteristics
Broad Network Access
Rapid Elasticity
Resource Pooling
Measured Service
Massive Scale
Resilient Computing
Homogeneity
Geographic Distribution
Common Characteristics
Virtualization
Service Orientation
Low Cost Software
Advanced Security
Based upon original chart created by Alex Dowbor
- http//ornot.wordpress.com
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The NIST Cloud Definition Framework

• A number of other attributes rely on the scale of
  investment undertaken by cloud providers
• Early cloud promoters (e.g. Amazon Google) had
  to build massive scale for their main businesses
• Use of open source software and commodity
  hardware reduces overall cost to cloud provider

On Demand Self-Service
Essential Characteristics
Broad Network Access
Rapid Elasticity
Resource Pooling
Measured Service
Massive Scale
Resilient Computing
Homogeneity
Geographic Distribution
Common Characteristics
Virtualization
Service Orientation
Low Cost Software
Advanced Security
Based upon original chart created by Alex Dowbor
- http//ornot.wordpress.com
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4 Cloud Deployment Models

• Private cloud
• Cloud infrastructure is operated solely for an
  organization. It may be managed by the
  organization or a third party and may exist on
  premise or off premise
• Typically only large organisations
• Public cloud
• Cloud infrastructure is made available to the 3rd
  parties but is owned by an organization selling
  cloud services
• Cloud services designed to be generic and
  suitable to all customers
• E.g. Amazon, Google, Microsoft, BM etc

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4 Cloud Deployment Models

• Community cloud
• Cloud infrastructure is shared by several
  organizations and supports a specific community
  that has shared concerns (e.g., mission, security
  requirements, policy, and compliance
  considerations)
• May be managed by the organizations or a third
  party and may exist on premise or off premise
• Hybrid cloud
• composition of two or more clouds that remain
  unique and separate entities but are bound
  together by standardized or proprietary
  technology that enables data and application
  portability
• Cloud bursting is the term used to describe the
  process where an organisation extend from a
  private to public cloud

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Client access architecture

• Client access via browser of Web Services
• Independent of type of cloud computing

VM
Platform
App 1
App server
Or
Clients
Access via Browser Or web-service (SOAP or REST)
DB
OS
Network
Storage
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Service model architecture
Software As A Service (SaaS)
Datastore as a service
Platform As A Service (PaaS)
Infrastructure As A Service (IaaS)

• Four main service model architectures
• Datastore as a service is not always included
  although currently the most popular use of cloud
• Significant differences in the technical and
  commercial architectures

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Service model architecture Datastorage as a
servce
Software As A Service (SaaS)
Datastore as a service
Platform As A Service (PaaS)
Infrastructure As A Service (IaaS)

• Functional Data storage interfaces can be used
  by any of the other types or accessed directly
• Examples of direct usage Amazons really simple
  storage
• Commercial Charged on basis of amount of
  storage used

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Characteristics of cloud datastore

• Cloud based datastore is massively distributed
  and scalable
• Utilises large number of commodity servers
  (a.k.a. nodes)
• This implies that the chance of system failure
  across a large number of nodes is high
• Therefore, cloud datastore must cope with node
  failure
• Cloud datastores are typically non-relational
• Distribution across a large number of nodes not a
  good fit to the relational model of databases.
  Relational databases support joins which are
  hard to implement in a massively distributed way
• To address requirement for relational database
  capabilities
• Either provide relational interfaces to
  non-relational infrastructure
• Allow relational databases to run on a small
  number of nodes as part of the virtualisation

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Characteristics of cloud datastore

• Cloud datastores are optimised for large scale
  data search
• E.g. Googles MapReduce (and hadoop an open
  source implementation) which divide the
  processing into multiple blocks (Map) and then
  process each block on one or more nodes (reduce)
• Cloud datastores are also appropriate to business
  intelligence applications which require column
  based processing
• E.g. Summing sales in a particular region
• In contrast, relational databases are efficient
  for record/row level read/write

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Service model architecture IaaS
Software As A Service (SaaS)
Datastore as a service
Platform As A Service (PaaS)
Infrastructure As A Service (IaaS)

• Functional Virtual server instances available
  for provisioning
• Examples Amazons EC2,
• Commercial Charged on basis of number /scale of
  instances as well as usage profile

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Example Amazon EC2

• Amazon provides a range of general purpose
  support services accessible via VMs
• Examples of these services include
• Simple Queue Service Limited messaging system
  for communications between VMs
• S3 Cloud storage service

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Example Amazon EC2

• Other examples of these services (cont)
• SimpleDB Non-relational database
• Elastic MapReduce large scale search and text
  processing infrastructure
• Flexible payment service enabling website
  payments
• Mechanical Turk outsourcing marketplace

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Amazon EC2 options and pricing

• Aws.amazon.com/ec2

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Service model architecture PaaS
Software As A Service (SaaS)
Datastore as a service
Platform As A Service (PaaS)
Infrastructure As A Service (IaaS)

• Functional Application development and
  deployment environment
• Provides programming APIs as well as underlying
  infrastructure
• Commercial Metering and billing based on
  application usage typically CPU
  consumption/datastore consumption

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Example Google AppEngine

• Platform uses multiple tenancy on the single
  infrastructure
• Benefit of charging only on usage and not on
  number of instance (as with IaaS)
• Provides general purpose support services
• Includes infrastructure services such as database
• Also includes application level interfaces such
  as video conferencing
• Provides both server and client side APIs to
  develop Google AppEngine applications
• Provides a platform which is proprietary

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Example Microsoft Azure Services

• Access to the Microsoft platform as a cloud based
  platform
• Provides a platform which is proprietary

Source Microsoft Presentation, A Lap Around
Windows Azure, Manuvir Das
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Service model architecture SaaS
Software As A Service (SaaS)
Datastore as a service
Platform As A Service (PaaS)
Infrastructure As A Service (IaaS)

• Functional End user interaction with the
  Applications function
• Allows for customisation of UI and workflows
• Often uses mult-tenancy databases
• Commercial typically billing based on number of
  users

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Example Salesforce.com

• Provides complete application accessible from the
  cloud
• Infrastructure is hidden from the user
• Software can be configured to support customer
  specific requirements
• Supports customisation through configuration
  driven language
• Scope for customisation is limited
• Uses multi-tenancy architecture
• Essential a platform for a specific class of
  application
• Configuration results in a change to both UI and
  underlying database schema for that customer

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Examples of configuration

• UI actions (such as entering an email address)
  can have customised scripts associated with them
  which perform workflow or validation logic
• Workflow defines the sequence of steps through
  the UI screens
• Validation logic enforces rules about information
  entered based on customer specific standards or
  context specific restraints (i.e. What can be
  entered given the current workflow)
• These may not effect the database schema
  definition and therefore can be deployed only to
  that customers UI

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Examples of configuration

• UI definitions (or associated workflows) may also
  require modifications/extensions to the database
  schema
• Through multi-tenancy/multi-schema approach, the
  metadata defining the schemas specific to that
  customer is modified without impacting on the
  baseschema or the other customers deployed
  schemas

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Different types of SaaS

• Type 1 Ad-Hoc/Custom
• Type 2 Configurable
• Type 3 Configurable, Multi-Tenant-Efficient
• Type 4 Scalable, Configurable,
  Multi-Tenant-Efficient

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Source Microsoft MSDN Architecture Center
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Different types of SaaS

• Type 1 Ad-Hoc/Custom
• Each customer (or tenant) has there own instance
  of the application which can be customised on an
  individual basis
• Level 1 SaaS is equivalent to application hosting

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Different types of SaaS

• Type 2 Configurable
• A single application base is customised for each
  customer/tenant
• Customisation is deployed within each instance of
  the application
• Deployment of upgrades across the instance will
  require roll-out to each instance

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Different types of SaaS

• Type 3 Configurable, Multi-Tenant-Efficient
• A single application base and instance is
  customised for each customer/tenant
• Customisation is deployed at run-time within each
  instance of the application
• Single instance is more resource efficient than
  multiple instances
• Deployment of upgrades made to a single instance

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Different types of SaaS

• Type 4 Scalable, Configurable,
  Multi-Tenant-Efficient
• Uses a tenant load balancer to balance load
  between multiple instances
• Similar to a hypervisor
• Should provide superior scalability and
  efficiency
• Requires deployment of upgrades to made to
  multiple instances

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Conclusions Understanding the different service
model architectures

• Different levels of abstraction
• OS Amazon EC2
• Application development framework Google
  AppEngine
• Applicaton customisation Salesforce
• Similar to languages
• Higher level abstractions can be built on top of
  lower ones

Lower-level, More flexibility, More
management Scalability through configuration
Higher-level, Less flexibility, Less
management Automatically scalable
Salesforce.com
EC2
Azure
AppEngine
IAAS
PAAS
SAAS
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Cloud and security
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General Security Challenges

• Security/data control is the most often cited
  issue with migration to the cloud
• Issues include
• Trusting vendors security model
• Customer inability to respond to audit findings
  (dependent on service provider to modify service)
• Obtaining support for investigations
• Indirect administrator accountability
• Proprietary implementations cant be examined
• Loss of physical control

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Cloud Security Challenges Part 1

• Data dispersal and international privacy laws
• EU Data Protection Directive and U.S. Safe Harbor
  program
• Exposure of data to foreign government and data
  subpoenas
• Data retention issues
• Mostly addressed by cloud vendor providing
  geographic specific services
• Clear data ownership
• Quality of service guarantees
• Reliability of cloud service providers service
  in the context of enterprise level quality of
  service commitments (typically with required
  recovery times in seconds or minutes)
• Potential for massive outages

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Cloud Security Challenges Part 2

• Dependence on secure hypervisors (for IaaS) or
  Multi-tenancy (in both PaaS and SaaS)
• Attraction to hackers (high value target)
• Security of virtual OSs in the cloud
• Encryption needs for cloud computing
• Encrypting access to the cloud resource control
  interface
• Encrypting administrative access to OS instances
• Encrypting access to applications
• Encrypting application data at rest
• Lack of public PaaS/SaaS version control
• Changes to the service may occur with out
  explicit agreement from the customer unlike
  tightly controlled lifecycle management within an
  enterprise