Cloud Computing to Satisfy Peak Capacity Needs Case Study

Download Cloud Computing to Satisfy Peak Capacity Needs Case Study

Post on 15-Jan-2016

217 views

Category:

Documents

0 download

Embed Size (px)

TRANSCRIPT

<p>PowerPoint Presentation</p> <p>Cloud Computing to Satisfy Peak Capacity NeedsCase StudyWhat is Cloud?Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics, three service models, and four deployment models. On-Demand Self ServiceBroad Network AccessResource poolingRapid ElasticityMeasured Service</p> <p>Cloud DefinitionAccording to NISTNIST Cloud Defitition (National Institute of Standards and Technology)http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf3A consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with each service provider </p> <p>What is Cloud: On-Demand Self ServiceCapabilities are available over the network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, tablets, laptops, and workstations). What is Cloud:Broad Network AccessThe providers computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to consumer demand. What is Cloud:Resource PoolingCapabilities can be elastically provisioned and released, in some cases automatically, to scale rapidly outward and inward commensurate with demand. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be appropriated in any quantity at any time. What is Cloud:Rapid ElasticityCloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service. What is Cloud:Measured ServiceA pragmatic approach is being developed to identify business value and not force-fit Cloud as a silver bullet. MetLife Cloud Approach9External Cloud is being positioned to extend our short-term, non-core compentency service offerings.</p> <p>MetLife Cloud Approach10Internal cloud is being positioned to simplify and further automate capacity provisioning to speed time to market, enhance internal efficiencies and possibly compete with low cost, low support external offerings.MetLife Cloud Approach11By developing separately but planning for an internal/external integration, we recognize the progressive nature of Cloud today. Taking measured steps maximizes current value while stategically positioning MetLife to streamline operations and increase agility to respond quickly to market demands.</p> <p>MetLife Cloud Approach12Replace high capital spend with low operational rent where appropriateSpeed to market over traditional provisioning for rapid project start, critical events, market agility and quick product evaluation</p> <p>MetLife Cloud ApproachExternal CloudMetLife Cloud ApproachExternal Cloud</p> <p>Leverage existing resourcesHardened EnvironmentExtension of our existing environmentMetLife Cloud ApproachInternal CloudMetLife Cloud ApproachInternal Cloud</p> <p>Use Case: HPC Grid(HPC) is the ability, using a set of open standards and protocols, to gain access to applications and data, processing power, storage capacity and other computing resources. A grid is a type of parallel and distributed system that enables the sharing, selection, and aggregation of resources distributed across multiple administrative domains based on their availability, capacity, performance, cost, and expected Quality-of-Service requirements.HPC Grid</p> <p>Metlife Integrated Actuarial Modeling Environment (MIAME)2 Head Nodes2 Storage Nodes96 Compute Nodes</p> <p>HPC Grid:MIAMEUse Case: SituationMIAME Grid presented with multiple deliverables totaling 350-400 jobs in 5 days20 Compute Node / Server resources available 160 CPU Cores total</p> <p>Projected failure to meet business timelineLimited resources would require failing selected service level agreements to allow for meeting those with a higher priorityUse Case: SituationProvision 24 additional compute nodes from internal cloud environmentAdditional 48 CPU Cores </p> <p>Use Case: SolutionNet increase of 30% capacity23Additional resources provisioned and integrated within 4 hoursUsed for satisfying all deliverables within business timelineRetained for additional period to resolve additional backlogReleased and Decommissioned following useMachine images archived against future use</p> <p>Use Case: Results</p> <p>Cloud Experiences and SummaryChallenges for Internal vs ExternalIntegration with existing processes Controlling an process that is designed to be uncontrolledCloudChallenges and OpprotunitiesQuestions</p>

Recommended

View more >