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Cloud deployment models
The document discusses different cloud deployment models including private cloud, public cloud, and hybrid cloud. Private cloud is owned and operated solely by a single organization, public cloud is owned by third-party providers and accessible to the general public, and hybrid cloud combines both private and public clouds. Each deployment model offers different benefits related to cost, control, security, and flexibility that organizations can leverage to meet their unique needs.
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Cloud deployment models
- 1. Cloud Deployment Models Dr.K.Ashokkumar School of Computing Sathyabama University, Chennai, India
- 3. 3 Enterprise Data Center There isa spectrum of deployment options for cloud computing 1) Private Cloud 2) Managed Private Cloud 3) Hosted Private Cloud 4) Community Cloud Services 5) Public Cloud Services Enterprise Data Center 3rd party operated Enterprise 3rd party hosted & operated Private Cloud Managed Private Cloud Hosted Private Cloud Enterprise A Enterprise B Enterprise C User 1 User 2 User 4 User 3 Private PublicHybrid Key features •Scalability •Automatic/rapid provisioning •Chargeback ability •Widespread virtualization •Security Key features •Scalability •Automatic/rapid provisioning •Standardized offerings •Consumption-based pricing. •Multi-tenancy Key features • Internal & external services integrated • Functions allocated to based on requirements, business needs, architecture etc Shared Cloud Services Public Cloud Services
- 4. Customers are choosinga variety of cloud models to meet their unique needs and priorities. Private Cloud On or off premises cloud infrastructure operated solely for an organization and managed by the organization or a third party Public Cloud Available to the general public or a large industry group and owned by an organization selling cloud services Hybrid Cloud Traditional IT and clouds (public and private) that remain separate but are bound together by technology that enables data and application portability Traditional IT Appliances, pre-integrated systems and standard hardware, software, and networking Cloud delivery models
- 5. FlexibilityFlexibility Different delivery models Off-PremiseDedicated On-Premise Traditiona lIT Hybrid Description Cost Model Service Private/Public Dedicated systems in customers data centre. Bespoke and highly customised to application needs. $$$$ Customer owned. Customer operated. High Capex/ High Opex. Long term commitment. High SLAs. 99.999 availability. Custom security. Behind customer firewall. Always private Dedicated cloud in customers data centre. Highly automated, pattern based, tuned for workloads. $$$ Customer owned. Customer operated. High Capex/Medium Opex. Mid term commitment. High SLAs. 99.999 availability. Standardised security. Behind customer firewall. Always Private Combined on-premise and off- premise cloud systems. Includes off-premise private Cloud. Highly standardised build, some parts run by service provider. $$ Partial customer ownership. Mostly service provider operated. Med Capex/Medium Opex. Short term commitment. High SLAs. 99+ availability. Standardised security. Requires good network and security. Can be private or public Public cloud infrastructure run off premise by service provider. Commodity resources defined by the service provider. Catalog based services. $ Provider owned. Provider operated. Full Opex model. No/short term commitment. PAYG. Medium SLAs. 98+ availability. Relies upon provider security and trust. Likely to be public, but can have dedicated private cloud at off-premise service provider.
- 6. Private Cloud • Aprivate cloud is owned by a single organization. • Private clouds enable an organization to use cloud computing technology as a means of centralizing access to IT resources by different parts, locations, or departments of the organization. • When a private cloud exists as a controlled environment, the problems described in the Risks and Challenges section do not tend to apply.
- 7. • Cloud infrastructurebuilt in house • Retains control of resources • More security & privacy • Can conform to regulatory requirement • Needs capital investment • Needs expertise to build and maintain Private CloudPrivate Cloud
- 9. Public Cloud • Apublic cloud is a publicly accessible cloud environment owned by a third-party cloud provide • The IT resources on public clouds are usually provisioned via cloud delivery models . • The cloud provider is responsible for the creation and on-going maintenance of the public cloud and its IT resources.
- 10. • Available toeveryone. • Anyone can go and signup for the service. • Economies of Scale due to Size. • Some public cloud concerns – Ownership – Control – Regulatory compliance – Data/Application security – Liability for SLA breaches Public CloudPublic Cloud I n t e r n e t
- 11. • Many ofthe scenarios and architectures explored via Public cloud.
- 12. • A hybridcloud is a cloud environment comprised of two or more different cloud deployment models. • Best of Both World • Workload is deployed mostly on private cloud • Resources can be used from public cloud when there is a surge in peak load (Cloud Burst) Private CloudPrivate Cloud Public CloudPublic CloudI n t e r n e t Hybrid Clouds
- 13. Hybrid delivers benefitsbeyond only public or private cloud models Reduce costs and maximise existing IT investments. – Data centre and infrastructure reused alongside flexible public cloud. Business agility, scale quickly to respond to business events. – Move quickly increasing workloads to off-premise Clouds. Maintain control through application lifecycle. – Single point of control of IT infrastructure resources, consumption and usage Maintain visibility of important workloads. – Workloads placed based on service requirements Shared Off-Premise Dedicated On-Premise Traditiona l IT Hybrid Flexibility & Resilience Regulated Workloads Production User Data Low-cost commodity Test/Dev Anonymised Data Performance without commitment Pre- Production/Test Anonymised Data Enterprise class Regulated Workloads Production User Data
- 14. Data centre prioritisedfor high- availability production workloads with service mgmt Low priority workloads moved externally Lower investment in fixed data centre assets ITIL managed Burst at peak workload to low cost commodity provider Dev Test - SIT Dev No commitment Pay as you go - commodity Long term flexibility with external Dedicated Private Exploit unused production capacity Development SCM Build SIT UAT Prod Application Lifecycle Time Adopting hybrid lowers costs while maintaining service levels
- 15. Deployment Models -BenefitsCustomer Scenario Service Model Deployment Model Benefits Payroll Processing IaaS (VMs), cloud storage Public Cloud Processing time reduced Hardware requirements reduced Elasticity enabled for future expansion Astronomic Data Processing IaaS (VMs), cloud storage Public Cloud Hardware expense greatly reduced processing power and storage) Energy costs greatly reduced Administration simplified Central Government IaaS, PaaS Private Cloud IT expertise consolidated Hardware requirements reduced Local Government IaaS, PaaS Hybrid Cloud IT expertise consolidated Hardware requirements reduced
Editor's Notes
- #14 Typically the discussion of test/dev in the cloud does not address production. A hybrid approach can address production requirements as well as deliver benefits of public cloud for test/dev. Splitting the application lifecycle across public and private, allows the benefits of each type of cloud to be realised. However to realise these benefits, the workloads have to be easily portable between cloud environments and the fixed assets of the Dedicated On-Premise cloud have to be effectively utilised when production workload is low. Open standards and workload portability allow fixed resources to be effectively utilised and PAYG only when peak workload requires. Security and networking is simplified as production/client data only remains within client DCs.
- #15 User acceptance testing (UAT) is the formal testing with respect to user needs, requirements, and business processes conducted to determine whether or not a system satisfies the acceptance criteria and to enable the user, customers or other authorized entity to determine whether or not to accept the system. Acceptance testing is also known as end-user testing, operational acceptance testing (OAT) or field (acceptance) testing. System integration testing (SIT) is a testing process that exercises a software system's coexistence with others. With multiple integrated systems, assuming that each have already passed system testing Can also be applied to DR. Production and Pre-Production workloads shared across two data centres providing DR for production workloads. Manage costs within budget Schedule workloads and prioritisation dependant on available resources. Schedule dev/test projects based on peak workload expectation, manage costs within available budget. Burst workloads to commodity cloud under peak workload conditions. Chargeback to business units/Projects based on capacity consumption – type and utilisation. Variable income to IT dependant on business load. Execess workload backed off to public cloud to minimise investment Lower priority test workloads deferred to offsite resources Very low priority workloads deferred to pay as you go variable commodity infrastructure Resource planning for onsite verus’s offsite. – long term investment in DCs or movement to completely outsourced infrastructure Charge back of resources used Benefits from using pay as you go pricing. – variability of external resources is essential.
- #16 The payroll application used an SQL database for processing employee data. Instead of rewriting the application to use a cloud database service, a VM with a database server was deployed. The database server retrieved data from a cloud storage system and constructed relational tables from it. Because of the size of the original (in-house) database, extraction tools were used to select only the information necessary for payroll processing. That extracted information was transferred to a cloud storage service and then used by the database server. The payroll application was deployed to four VMs that run simultaneously; those four VMs work with the VM hosting the database server. The configuration of the payroll application was changed to use the VM hosting the database server; otherwise the application was not changed. ----------------------------------------------------------- Gaia8 is a mission of the European Space Agency that will conduct a survey of one billion stars in our galaxy. It will monitor each of its target stars about 70 times over a five-year period, precisely charting their positions, distances, movements, and changes in brightness. It is expected to discover hundreds of thousands of new celestial objects, such as extra-solar planets and failed stars called brown dwarfs. This mission will collect a large amount of data that must be analyzed. The ESA decided to prototype a cloud-based system to analyze the data. The goals were to determine the technical and financial aspects of using cloud computing to process massive datasets. The prototype system contains the scientific data and a whiteboard used to publish compute jobs. A framework for distributed computing (developed in house) is used for job execution and data processing. The framework is configured to run AGIS (Astrometric Global Iterative Solution). The process runs a number of iterations over the data until it converges. For processing, each working node gets a job description from the database, retrieves the data, processes it and sends the results to intermediate servers. The intermediate servers update the data for the following iteration. The prototype evaluated 5 years of data for 2 million stars, a small fraction of the total data that must be processed in the actual project. The prototype went through 24 iterations of 100 minutes each, equivalent to running a grid of 20 VMs for 40 hours. For the full billion-star project, 100 million primary stars will be analyzed along with 6 years of data, which will require running the 20 VM cluster for 16,200 hours. To evaluate the elasticity of a cloud-based solution, the prototype ran a second test with 120 high CPU extra large VMs. With each VM running 12 threads, there were 1440 processes working in parallel. A.LinkedIn: ·For discovering People You May Know and other fun facts. ·Item-Item Recommendations ·Member and Company Derived Data ·User’s network statistics ·Who Viewed My Profile? ·Abuse detection ·User’s History Service ·Relevance data ·Crawler detection ----------------------------------------------------------- The ministries of the Japanese Government have thousands of servers across their infrastructures. The central government has announced a private “Kasumigaseki” cloud environment to provide a secure, centralized infrastructure for hosting government applications. Existing back office systems, such as payroll, accounting and personnel management, will be virtualized and hosted in the private cloud. Some front office systems, such as electronic procurement, will be virtualized to a public cloud, but that is outside the scope of this project. The ultimate goal of the project is to reduce the total cost of ownership by eliminating redundant systems and the need for administrators in each ministry. ----------------------------------------------------------- There are more than 1800 local governments across Japan, each of which has its own servers and IT staff. A secondary goal of the Kasumigaseki cloud is to provide a hybrid cloud environment. In addition to the Kasumigaseki cloud, the Japanese central government has decided to group local governments at the prefecture level. Each prefecture will have a private cloud and a connection to the Kasumigaseki hybrid cloud. Internal tasks and some data will be hosted in the prefecture’s private cloud, while other data will be stored locally. Wherever possible, existing systems will be virtualized and hosted in the Kasumigaseki cloud.