Cloud Computing

1. Cloud Computing

2. 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.”

3. What is cloud computing? I don’t understand what we would do differently in the light of Cloud Computing other than change the wordings of some of our ads Larry Ellision, Oracle’s 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, HP’s Vice President of European Software Sales It’s stupidity. It’s worse than stupidity: it’s a marketing hype campaign. Richard Stallman, Free Software Foundation founder

4. The 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

5. 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

6. 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

7. The NIST Cloud Definition Framework Deployment Models Hybrid Clouds Service Models Community Cloud Public Cloud Private Cloud Essential Characteristics Software as a Service (SaaS) Platform as a Service (PaaS) Infrastructure as a Service (IaaS) Massive Scale Resilient Computing On Demand Self-Service Homogeneity Geographic Distribution Common Characteristics Broad Network Access Rapid Elasticity Virtualization Service Orientation Resource Pooling Measured Service Low Cost Software Advanced Security Based upon original chart created by Alex Dowbor - http://ornot.wordpress.com

8. 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

9. 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

10. 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

11. 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

12. Client access architecture • Client access via browser of Web Services • Independent of type of cloud computing VM Platform App 1 App 1 App Server App server Or Database Clients OS Access via Browser Or web-service (SOAP or REST) Server DB Storage Network OS Network Storage

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

14. Service model architecture: Datastorage as a servce Software As A Service (SaaS) • Functional: Data storage interfaces can be used by any of the other types or accessed directly • Examples of direct usage: Amazon’s really simple storage • Commercial: Charged on basis of amount of storage used Datastore as a service Platform As A Service (PaaS) Infrastructure As A Service (IaaS)

15. 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

16. Characteristics of cloud datastore • Cloud datastores are optimised for large scale data search • E.g. Google’s 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

17. Service model architecture: IaaS Software As A Service (SaaS) • Functional: Virtual server instances available for provisioning • Examples: Amazon’s EC2, • Commercial: Charged on basis of number /scale of instances as well as usage profile Datastore as a service Platform As A Service (PaaS) Infrastructure As A Service (IaaS)

18. 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

19. 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

20. Amazon EC2 options and pricing • Aws.amazon.com/ec2

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

22. 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

23. 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

24. Service model architecture: SaaS Software As A Service (SaaS) • Functional: End user interaction with the Application’s function • Allows for customisation of UI and workflows • Often uses mult-tenancy databases • Commercial: typically billing based on number of users Datastore as a service Platform As A Service (PaaS) Infrastructure As A Service (IaaS)

25. 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

26. 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

27. 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 ‘base’schema or the other customers’ deployed schemas

28. 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 28 Source: Microsoft MSDN Architecture Center

29. 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 29

30. 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 30

31. 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 31

32. 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 32

33. Conclusions: Understanding the different service model architectures Lower-level, More flexibility, More management Scalability through configuration Higher-level, Less flexibility, Less management Automatically scalable Salesforce.com EC2 Azure AppEngine • 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 IAAS PAAS SAAS

34. Cloud and security

35. General Security Challenges • Security/data control is the most often cited issue with migration to the cloud Issues include: • Trusting vendor’s 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 can’t be examined • Loss of physical control

36. 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

37. 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 SaaS version control • Changes to the service may occur with out explicit agreement from the customer – unlike tightly controlled lifecycle management within an enterprise