Title: Cloud Computing
1Cloud Computing
2Definition
- 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.
3What 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
4The Big Switch (N. Carr)
- Thesis IT will follow the same evolution as
electricity - Initially businesses had their own generators but
this consolidated towards centralised providers
of generation/distribution - Is the cloud the end of high-end PC? IT business
network? - Why build your own network if you can use a cloud
based network
5Business 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
6Technology 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
7The 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
8The 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
9The 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
104 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
114 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
12Client 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
13Service 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
14Service 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
15Characteristics 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
16Characteristics 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
17Service 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
18Example 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
19Example 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
20Amazon EC2 options and pricing
21Service 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
22Example 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
23Example 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
24Service 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
25Example 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
26Examples 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
27Examples 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
28Different types of SaaS
- Type 1 Ad-Hoc/Custom
- Type 2 Configurable
- Type 3 Configurable, Multi-Tenant-Efficient
- Type 4 Scalable, Configurable,
Multi-Tenant-Efficient
28
Source Microsoft MSDN Architecture Center
29Different 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
29
30Different 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
30
31Different 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
31
32Different 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
32
33Conclusions 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
34Cloud and security
35General 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
36Cloud 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
37Cloud 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 SaaS version control
- Changes to the service may occur with out
explicit agreement from the customer unlike
tightly controlled lifecycle management within an
enterprise