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Academic Compute Cloud Provisioning and
UsageProject
Peter KunsztETH/SystemsX.ch
2012, November 19 Bern
MotivationResearchers often only want services, not products.Services rely on •Infrastructure•Middleware•Application Software•Research Informatics ‘Glue’
We ‘the supporters’ want to offer ‘Apps’•Maintainable services
•Published, usable tools and software•Browsable published research data
19 Nov. 2012 SDCD Bern
Motivation: SystemsX.chSCHWEIZERISCHE EIDGENOSSENSCHAFTCONFÉDÉRATION SUISSECONFEDERAZIONE SVIZZERACONFEDERAZIUN SVIZRA
Largest Swiss national research effort to dateLargest Swiss national research effort to date
19 Nov. 2012 SDCD Bern
Some numbers..• Funded by the Swiss
government with CHF 25Million/year for 2008-2011, 2012, 2013-2016
• 12 Swiss Universities and Research Institutions invest a matching 25 Million/y
• Projects approved by the SNSF
• 14 large research projects (4-7MCHF) until 2012, 10 new starting 2013 (3MCHF)
• 50+ PhD projects
• 20+ interdisciplinary pilot projects
• 1 strategic support project: SyBIT 2MCHF/y average
SDCD Bern19 Nov. 2012
SyBIT Project Motivation
SystemsX.ch will produce and analyze a large large amount of dataamount of dataStrong need for coordinationcoordination among data providersStrong need for commoncommon semanticssemantics and compatiblecompatible service offeringsIncreased need for professionally supportedsupported tools and services
19 Nov. 2012 SDCD Bern
BioinformaticsBioinformatics
IT InfrastructureIT Infrastructure
PlatformsPlatforms
PhosphoNetXLipidX
MetaNetXPlantGrowthCellPlasticity
LiverXCycliX
NeurochoiceWingXYeastX
DynamiXCINA
BattleXInfectX
PhosphoNetXLipidX
MetaNetXPlantGrowthCellPlasticity
LiverXCycliX
NeurochoiceWingXYeastX
DynamiXCINA
BattleXInfectX
SyB
ITS
yBIT
IPPIPP
IPHDIPHD
Service Providers
SyBIT provides support
19 Nov. 2012 SDCD Bern
BioinformaticsBioinformatics
IT InfrastructureIT Infrastructure
PlatformsPlatforms
PhosphoNetXLipidX
MetaNetXPlantGrowthCellPlasticity
LiverXCycliX
NeurochoiceWingXYeastX
DynamiXCINA
BattleXInfectX
PhosphoNetXLipidX
MetaNetXPlantGrowthCellPlasticity
LiverXCycliX
NeurochoiceWingXYeastX
DynamiXCINA
BattleXInfectX
SyB
ITS
yBIT
IPPIPP
IPHDIPHD
Service Providers
SyBIT gives feedback
19 Nov. 2012 SDCD Bern
MotivationResearchers often only want services, not products.Services rely on •Infrastructure•Middleware•Application Software•Research Informatics ‘Glue’
We ‘the supporters’ want to offer ‘Apps’•Maintainable services
•Published, usable tools and software•Browsable published research data
19 Nov. 2012 SDCD Bern
Project Goals• How to extend current cluster services using cloud
technology? • Support new application models (MapReduce, specialized
servers).• Test real applications.• Understand performance implications.
1. Define Service Models: How to move to cloud-like service orientation models.
2. Define Business Models: How to accommodate pay-per-use, OpEx vs. CapEx, how to plan an academic private cloud, and how to use and offer public clouds
3. Run real applications: Run a regular, a compute-intensive and a data-intensive application on the cloud.
19 Nov. 2012 SDCD Bern
19 Nov. 2012 SDCD Bern
Project Goals• How to extend current cluster services using cloud
technology? • Support new application models (MapReduce, specialized
servers).• Test real applications.• Understand performance implications.
1. Define Service Models: How to move to cloud-like service orientation models.
2. Define Business Models: How to accommodate pay-per-use, OpEx vs. CapEx, how to plan an academic private cloud, and how to use and offer public clouds
3. Run real applications: Run a regular, a compute-intensive and a data-intensive application on the cloud.
Provide input to the mid- and long-term strategy for cluster and cloud
infrastructure at ETH and UZH.
Provide input to the mid- and long-term strategy for cluster and cloud
infrastructure at ETH and UZH.
Disseminate results in Switzerland broadly in academia and to
interested parties (Workshop at project end)
Disseminate results in Switzerland broadly in academia and to
interested parties (Workshop at project end)
Cloud Attributes: When do we talk about a cloud
• Self-service, On-demand, Cost transparency– Access to immediately available resources, paying
for usage only. No long-term commitments. No up-front investments needed. Operational expenses only.
• Elasticity, Multi-tenancy, Scalability– Grow and shrink size of resource on request.
Sharing with other users without impacting each other. Economies of scale.
DEFINITION
19 Nov. 2012 SDCD Bern
Definitions• Self-service: A consumer can unilaterally provision
computing capabilities, such as server time and network storage, without requiring human interaction.
• On-demand: As needed, at the time when needed, automatic provisioning.
• Cost Transparency: Accounting of actual usage transparent to user and service provider both, measured in corresponding terms (Hours CPU time, GB per Month, MB Transfer, etc)
19 Nov. 2012 SDCD Bern
Definitions• Elastic: Capabilities can be elastically provisioned and
released, in some cases automatically, to scale rapidly outward and inward commensurate with demand.
• Multi-tenant: The provider’s computing resources are pooled to serve multiple consumers, with resources dynamically assigned and reassigned according to consumer demand.
• Scalable: To the consumer, the capabilities available for provisioning often appear to be unlimited and can be appropriated in any quantity at any time.
http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf
Relation to Cloud: As User (extension)
Number of users
Com
pu
tin
g n
eed
s CSCS
CloudCloudBurstUse
19 Nov. 2012 SDCD Bern
Today, University Clusters do not make use of the Cloud:
• Technical details to be investigated: – Bursting the cluster into the cloud
• Networking?• User Management?• File System?
• Cloud-compatible licenses for commercial products are often not available
• No billing mechanism to bill users of cluster for pay-per-use services
19 Nov. 2012 SDCD Bern
Relation to Cloud: As Provider
Number of users
Com
pu
tin
g n
eed
s CSCS
CloudCloud
Account / charge usage
Expose to
19 Nov. 2012 SDCD Bern
Not clear how to be a Cloud Provider with a University Cluster
• Univ. cluster is not self-service• Capital expenses, not just pay-per-use• Long-term commitment• Not extensible on-demand, not elastic• Sharing with others only according to policies• More stringent terms of use, needs account
• We have examples to look at:– SDSC, Cornell, Oslo
SDCD Bern
Infrastructure and Platform as a Service
From www.cloudadoption.org
Classic Approach Today
IaaS .
SoftwareSoftware Infrastructure Infrastructure PlatformPlatform
SaaS
PaaS
START FINISH
95%time savings
Cloud Stack
SoftwareSoftware
PlatformPlatform
InfrastructureInfrastructure
User Interface
MachineInterface
Components Services
Compute
Network
Storage
CLIENTSCLIENTS
HARDWAREHARDWARE
Users or Portals. Can directly use each stack. Users or Portals. Can directly use each stack.
Any kind of infrastructure for any of the stacks.Any kind of infrastructure for any of the stacks.
DEFINITION
Who can makes use of what
IaaSIaaS
PaaSPaaS
SaaSSaaS
User PortalUser Portal
HardwareHardware
• Users may use any service
• Portals may use any service
• SaaS may or may not be built on top of PaaS or IaaS
• PaaS may or may not be built on top of IaaS
19 Nov. 2012 SDCD Bern
Hybrid CloudHybrid Cloud
Public, Private, Hybrid CloudsDEFINITION
Public CloudPublic Cloud
• Offered by partner organizations or cloud providers
• Only operational expenses
• No control on cloud stack, dependency on external partner
• Private Cloud connected to Public Cloud
• Remote cloud resources on-demand
• Constraints on own cloud stack: needs to interoperate with public cloud
Private CloudPrivate Cloud
• Own infrastructure only
• In-house or hosted
• Internal use or for sale
• Full control on cloud stack, accounting, etc
ConnectConnect
Institutional boundary19 Nov. 2012 SDCD Bern
How to evolve the HPC Service..
• ..to be able to offer a Platform as a Service.
• ..to be able to make use of public clouds seamlessly (Hybrid model, CloudBursting)
19 Nov. 2012 SDCD Bern
Information Gathering
• We collected a lot of information and conducted a survey on existing solutions (mandate to CloudBroker)
19 Nov. 2012 SDCD Bern
Lots of Interactions
• With Cloud providers– IBM, Amazon, CloudSigma, HP, Google
• Software providers– VMWare, HP, Dell, OpenStack flavors (Piston, ..)
• Universities– SWITCH, ZHAW, SDSC, Cornell, Imperial College, U
Oslo, Zaragoza
19 Nov. 2012 SDCD Bern
Choices
• Commercial Cloud Appliance– Evaluate HP CloudSystem Matrix– Integrated hardware: HP blades and 3PAR storage– Runs with VMWare or Hyper-V– Complete management and end-user interfaces
• Build our own– 2 different systems (Dell based)– OpenStack: Several distributions to test– Special software: ScaleMP, cloud FS
19 Nov. 2012 SDCD Bern
Infrastructure 1
• ETH: HP CloudSystem Matrix Testbed– Operational as of THIS WEEK
• 8 Intel, 8 AMD blades • 128GB memory per blade• 10TB storage 3PAR
• HP Matrix cloud software is fixed• This is on RENT we have to give it back
Infrastructure 2• ETH: Build our own from new components.
– Standard cluster nodes x16, diskless– 128GB RAM on each node– Very fast storage (SSD based) for VM images
• Attach standard storage NAS from ETH• Cloud Stack:
– OpenStack – VMWare
• Being installed next monday• This remains at ETH after the project
Infrastructure 3
• University of Zurich: Recycle existing components.– Set of old cluster nodes, heterogeneous– Cloud filesystem using local node storage
(technologies will be evaluated)• GlusterFS• Ceph
19 Nov. 2012 SDCD Bern
HPC + Cloud: On the same HW
…….
Com
pute
Nod
esSt
orag
e
HPC CLUSTER CLOUD HW
Classic CLUSTER – Not Virtualized•Can be heterogeneous HW•OS controlled by Admins•Scheduler for job submission•Applications compiled and installed•Shared FS
CLOUD – Virtualized•Hypervisor and Cloud Stack controlled by Admins•Template ‘Apps’•Users can create new•Different kinds of storage•Different setups possible•Virtual SMP
19 Nov. 2012 SDCD Bern
Storage• Ceph, Gluster• Mount REAL=non-virtual cluster FS (Lustre, GPFS)• Mount NFS• Object stores, e.g. SWIFT• Different HW
– Local Disks– iSCSI– Very fast SSD-based appliance over 10Gb or FC or IB
(deduplication, compression) – for VMs and fast disk
19 Nov. 2012 SDCD Bern
Cloud HPC Use Cases to Test 1• Extending the regular cluster into the cloud
– Just run cluster node instances– Register back with cluster scheduler– Jobs can request these nodes explicitly– ALREADY tested using Amazon
• Building a full virtualized cluster in our Cloud– Everything virtual: Cluster nodes, headnodes– Cluster FS : several options (see storage)– What do we learn? Reality check: HPC performance
19 Nov. 2012 SDCD Bern
Test Case 1 Software• Use regular cluster workloads, NOT data intensive• Rosetta: structural biology• GAMESS: molecular chemistry simulation• SMSCG workloads (if we get there)
19 Nov. 2012 SDCD Bern
• Hadoop cluster– Build the virtual cluster dedicated to Hadoop– HFS or Swift
• Commercial tool cluster: Matlab– Matlab ‘cluster’: allocate a few ‘fat’ VMs to
Matlab– Let it run its internal clustering, expose to user
Cloud HPC Use Cases to Test 2
19 Nov. 2012 SDCD Bern
Test Case 2 Software• A bit more data intensive• Hadoop use cases
– Proteomics: analysis of selected reaction monitoring data– Genomics: bowtie over hadoop (Crossbow)
• Matlab and R– Set up cluster matlab on regular cluster– On SMP’d nodes
19 Nov. 2012 SDCD Bern
• Data intensive workflow– InfectX pipeline: Image analysis – several TB of small files– Many kinds of scripts, mostly Matlab– Same workflow can be submitted many times– Error prone!
• OpenBIS on-demand workflow– Extend metadata catalog with some basic processing
capabilities using remote resources– Streaming of data to perform some processing in the cloud
Cloud HPC Use Cases to Test 3
Business Models
• Cannot charge at full cost if we want to be the service provider (competitive advantage)• Internal and external views
• Efficient, fair, feasible and generally accepted funding and charging model
• New opportunities should not require to change existing business procedures for existing infrastructure (evolution not revolution)
• Transparent Financial Accounting mechanism
19 Nov. 2012 SDCD Bern
Business Models
• Several models are being worked out– Shareholder model – one-time fee for TFLOPS or TB– Subscription model – yearly fee– Pay-per-use model
• Self service options– Very detailed like Amazon– High-level ‘virtual cluster’ or PaaS– Top-level SaaS user gateways
19 Nov. 2012 SDCD Bern
TimelineApr‘12
ETHProject Start
Jul‘12
SWITCH AAAProject Start
SWITCH AAAProject End
Oct‘12 Jan‘13 Apr‘13
Information Gathering
Refinement of Targets
HP CloudSystem on lease
Business Model
Application Definition
delivered ready
ETH Self-built system
call decision delivery
today
UZH Self-built systemassemblyfrom existing stuff
ready
ready
return to HP
Application testing
Output• Workshop in April’13 to show results of project
– To all Swiss research community – See you there!
• Input to ETH, UZH strategies for research infrastructure– Drive next procurement processes– Drive strategies for cooperation/outsourcing models– Drive new policy models for funding and
sustainability
19 Nov. 2012 SDCD Bern