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Cloud Computing to Satisfy Peak Capacity Needs Case Study.

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Presentation on theme: "Cloud Computing to Satisfy Peak Capacity Needs Case Study."— Presentation transcript:

1 Cloud Computing to Satisfy Peak Capacity Needs Case Study

2 What is Cloud?

3 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 Service  Broad Network Access  Resource pooling  Rapid Elasticity  Measured Service Cloud Definition According to NIST

4  A consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with each service provider What is Cloud: On-Demand Self Service

5  Capabilities 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 Access

6  The provider’s 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 Pooling

7  Capabilities 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 Elasticity

8  Cloud 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 Service

9  A pragmatic approach is being developed to identify business value and not force-fit Cloud as a ”silver bullet.” MetLife Cloud Approach

10  External Cloud is being positioned to extend our short-term, non-core compentency service offerings. MetLife Cloud Approach

11  Internal 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 Approach

12  By 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. MetLife Cloud Approach

13  Replace high capital spend with low operational rent where appropriate  Speed to market over traditional provisioning for rapid project start, critical events, market agility and quick product evaluation MetLife Cloud Approach External Cloud


15  Leverage existing resources  Hardened Environment  Extension of our existing environment MetLife Cloud Approach Internal Cloud


17 Use Case: HPC Grid

18 “(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


20  Metlife Integrated Actuarial Modeling Environment (MIAME)  2 Head Nodes  2 Storage Nodes  96 Compute Nodes HPC Grid: MIAME

21 Use Case: Situation

22  MIAME Grid presented with multiple deliverables totaling 350-400 jobs in 5 days  20 Compute Node / Server resources available  160 CPU Cores total  Projected failure to meet business timeline  Limited resources would require failing selected service level agreements to allow for meeting those with a higher priority Use Case: Situation

23  Provision 24 additional compute nodes from internal cloud environment  Additional 48 CPU Cores Use Case: Solution

24  Additional resources provisioned and integrated within 4 hours  Used for satisfying all deliverables within business timeline  Retained for additional period to resolve additional backlog  Released and Decommissioned following use  Machine images archived against future use Use Case: Results


26 Cloud Experiences and Summary

27  Challenges for Internal vs External  Integration with existing processes  Controlling an process that is designed to be uncontrolled Cloud Challenges and Opprotunities

28 Questions

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