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Cloud Storage and Intel Power Management Usage Oriented Reference Architecture. Enrique Castro-Leon, Ph.D. End User Platform Integration October 2009 Rev 1.0. Summary. The Cloud Computing Reference Architecture Model Historical context for Cloud Storage 2.0

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cloud storage and intel power management usage oriented reference architecture

Cloud Storage and Intel Power Management Usage Oriented Reference Architecture

Enrique Castro-Leon, Ph.D.End User Platform IntegrationOctober 2009

Rev 1.0

summary
Summary
  • The Cloud Computing Reference Architecture Model
  • Historical context for Cloud Storage 2.0
    • Cloud storage yesterday, today and tomorrow
    • The growth of the digital universe and power considerations
    • Use cases for storage services producers and consumers
  • Usage Oriented Reference Architecture for Cloud Storage
    • CPU, servers, storage devices, rack, row, whole data center
    • How it works within and across architectural building blocks
    • Data center system-level use cases: platooning
cloud applications reference architecture model
Cloud Applications Reference Architecture Model

High Level

30000’

Usage: Discovery, exploration phase, market segment analysis

Audience: C level executives

Content: High Level conceptual arch

Example:Cloud infrastructure RA

General Purpose Reference Architecture

(GPRA)

Technical

1000’

Usage: Solution architecture discussion

Audience: CTO, IT architects, IT Managers

Content: Usage specific/environment generic

Example: Cloud Storage Power Management

Usage Oriented Reference Architecture

(UORA)

Mapping to implementation technology

Deep technical

End Users & SIs

Usage: App development/prototype discussions

Audience: IT architects & engineers

Content: Usage specific/environment specific

Example:Power management for cloud application

Special Purpose Reference Architecture (SPRA)

ODMs & OEMs

Usage: Strategic planning and product dev

Audience: Platform architects and engineers

Content: Solution concept proposals

Example: Next gen. power mgt sol’n proposal

Concept &

Design

Product Roadmap

Development &

Implementation

Usage: Defining product roadmap

Audience:Prod. Dev. engineers

Content: Project dev. documentation

Example: Prod. Reqs. & impl. plan

Product Hardware, Software Architecture

cloud storage 2 0
Cloud Storage 2.0

**Source: John F. Gantzet al., “The Diverse and Exploding Digital Universe”, IDC March 2008

cloud storage use cases
Cloud Storage Use Cases

Cloud Storage

Traditionaldedicatedcorporatestorage

Storage Virtual InfrastructureServices

In the Office

Business UseCases – In-sourced vs. Out-sourced

OnlineStorage Providers

Corporatestorageservices

Application &Data Storage Services

RichInternetApplications

Digital mediacreation &distribution

DataPresenceService

FamilyMovies-2-go

Personalstore-n-sync

SocialComputing

Backup

Streaming

Other corpcloud-basedapps

Storage-basedapplications

Storage providers

Storage consumers

Consumer use cases

(individual & corporate users

challenges opportunities consumers
Challenges & Opportunities (consumers)
  • Challenges
    • Risk of data loss
      • Solve backup problem
    • Proliferation of storage media
      • Unwieldy data management
    • Data volume increasing
      • Digital media: audio, video, pictures, data
    • Media obsolescence
      • Data retrieval, migration
  • Opportunities
    • A la carte storage services
      • Data presence (Pi Corporation*), backup (Mozy*)
    • Data stewardship
      • DR, offsite storage
challenges opportunities corporate service providers
Challenges & Opportunities(corporate & service providers)
  • Challenges
    • Exponential growth of digital footprint
      • New media, Web 2.0 driving storage requirements
    • Cost of in-house data storage
    • Energy usage can’t be ignored
  • Opportunities
    • Virtualization driving storage usage/delivery
    • Service oriented IT with SLA-driven products
      • Retention, privacy, access, management, security
      • Service decoupled from underlying technology
        • Cloud based storage
        • Integrated power management for storage devices
      • Organization-wide, uniform policies
      • Advanced info capture, search, discovery, classification
intel power management technologies portfolio for hyper scale environments

Power Control Range

Hardware entity

Implementation technology

100 KW

Data Center

OEM, ISV, SI solutions

10 KW

Row

Intel® Data Center Manager(10-10,000+ nodes)

Rack

1 KW

Intel® Intelligent PowerNode Manager(single node)

Server

100 W

IPMI, Data Center Management Interface

Solid State Drives

Chipset

CPU P / T state control ACPI, low power SSDs

Mem

CPU

10 W

Legend:

3rd Party Mgmt SW

Intel

Server OEM

Intel Power Management Technologies Portfolio for Hyper-scale Environments

Power control through nested control loops

11

cloud storage power management usage framework
Cloud Storage Power Management Usage Framework

Data Center Management Systems

Rack Optimization

Maximize server rack capacity in power constrained racks

Branch CircuitOptimization

Optimize DC pwrinfrastructReduce stranded power

Platooning & workload rebalancing

Optimize workload ramp-up,

energy usage in virtualized environments

Chargeback

Fine grained reporting, billing, auditing

P/T Monitoring

Control power consumption against forecast targets

Power control algorithms

Power feedback loops & state estimation physical models

Node level

power management

Management S/W (multi-level)

Other P/T sensors, controls & algorithms

ACPI P-state control

Recursive composition

Intel Confidential

cloud storage systems integration framework
Cloud Storage Systems Integration Framework

Building Management System

1

Global policy: Appliance power not to exceed 5 KW

Cloud storage application

Cloud storage powerpolicy engine budgets storage and node power to meet 5KW objective

Row Power Manager

Rack PolicyEngine

3

Cloud storage policy engine manages storagepower throughselective spin-downs

Storagecontrol

Nodecontrol

Cloud storage policy engine sets power targetfor compute & storagesubsystems

Intel DCM technologycloud plug-in

5

Actual Powerconsumed

Per node actual

Powerconsumed

2

4

Storage subsystem set power

7

Compute subsystem set power

DCM

Disk ArrayEnclosure

Reduce baselinepower in storage subsystem throughuse of SSDs

Group Policies

Node Manager performs voltage & frequency scaling to keep server power within assigned node power target

PSMI

PMBus

PMBus

PMBus

Actual Powerconsumed

Actual Powerconsumed

Disk ArrayEnclosure

NM

IntelligentPDU

S

S

CPU

S

Power tostorage subsystem

DCM assigns power targets inindividual nodes dynamicallysubject to compute subsystem power constraints

6

Disk ArrayEnclosure

cloud storage power management reference architecture
Cloud Storage Power Management Reference Architecture

Data Center MgtBuilding Mgt System

StorageApplication

Presentation subsystem

(consoles, dashboards, GUIs)

Planning & Management

CMDB

Apache

DCM Console

REST

SOAP

DC Control

Event Mgr

CMS Core

Operational Control

Native clientaccess API

Policies

Engine

Resource monitoring & Mgmt

Power Mgmt

Discovery & provisioning

Power control

Policy Resolution

Aggregator

Policy Data

Trending/ Query Data

Node Adapter Service (plug-in framework)

Monitoring & Automation

Powercontrol

Compute

Subsystemset pwr &pwr readout(REST)

Java in-process

Info collection

DCM Node control

Intel® Data Center Manager

Storage

service

Node Adapter Interface (pre-defined)

Set power (IPMI)

Power metadata (IPMI)

Blade

IB

3rd-party

NM

DCMI

iPDU

iDRAC

Set power & power metadata (REST)

Set power & power metadata (REST)

DCM Network Communication Lib

CPU power control

Powerreadout

Tempsensor

NPTM policyengine

Monitors

Power change

Power

PDU

MetadataService

Temp Mon

PMBusP/S

NM firmware

Other environmental sensors (temp, airflow, humidity)

PMBus interface

CPU power control

PSU Mon

BIOS ACPIpower & thermal state controlinterface

Power

Datastorage

Metadatastorage

Power control

Actual powerconsumed

Actual P-state

Set P-state

Operating systemor virtualization hypervisor

P-state table

KVM subsystem

Cloud Storage Application

Appliance Group Manager

Node power control

CPU

cloud storage appliance level replication
Cloud Storage Appliance-Level Replication

Rack level power and environmental sensor data (SOAP)

Cloudstorageapplication

Cloudstorageapplication

Cloudstorageapplication

Cloudstorageapplication

Rack PolicyEngine

Rack PolicyEngine

Rack PolicyEngine

Rack PolicyEngine

Storagecontrol

Storagecontrol

Storagecontrol

Storagecontrol

Nodecontrol

Nodecontrol

Nodecontrol

Nodecontrol

Row Power Manager

Application powerpolicy (SOAP)

Branch circuit and per appliance power allocation

The Row Power Manager can control multiple appliances

energy management use cases power vs energy management
Energy Management Use CasesPower vs. Energy Management

Powersaved at time t

Energy savedbetween t1 and t2is the area betweenthe two curves

t

t1

t2

integrated power management
Integrated Power Management
  • Power Mgt mechanisms have operational restrictions
    • Node Manager: high workload
    • DBS: low workload
    • NHM power proportional computing: Pbaseline limited to about 50%
  • Pooled virtualized environment
    • Combine mechanisms
      • Extend operational envelope
      • Lower Pbaseline
  • Example: Server platooning
advanced use case server platooning
Advanced Use Case: Server Platooning

2% - 25%

Takes 1 to 5 minto bring node online

Power

consumption

70%

50%

100%

Transitions forincreasing workload

Transitions fordecreasing workload

Active workloads

Power capped

Asleep

(ACPI S3, S4 or S5)

Active, high priorityworkloads

Unconstrained power

Idle

Platooning state

PMBus

PSMI

PMBus

PSMI

PMBus

PMBus

PMBus

PMBus

PMBus

PMBus

PMBus

PSMI

PSMI

PMBus

PMBus

PMBus

NM

NM

NM

NM

S

S

CPU

S

CPU

S

S

S

S

S

S

S

CPU

CPU

S

S

conclusions
Conclusions
  • Digital universe growing exponentially
    • Data spilling from the corporate data center into the cloud
    • Power usage growth slower but still unsustainable
  • Usage drives power management architecture
  • Paradigm of arbitrarily scalable systems
    • Composition & replication
    • Spans CPU to whole data center
    • Power control range from watts to hundreds of kilowatts
  • Power vs. energy management