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1 Commodity Reliability And Practices Commodity Reliability And Practices or or Building Reliable Systems with CRAP Building Reliable Systems with CRAP Thomas M. Ruwart Thomas M. Ruwart Chief Scientist Chief Scientist [email protected] [email protected] University of Minnesota Digital Technology Center Minneapolis, MN October 8, 2007

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Page 1: Commodity Reliability And Practices or Building Reliable ...cse820/lectures/lecturesS08/ruwartDisk.pdf · Commodity Reliability And Practices or Building Reliable Systems with CRAP

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Commodity Reliability And PracticesCommodity Reliability And Practicesoror

Building Reliable Systems with CRAPBuilding Reliable Systems with CRAP

Thomas M. RuwartThomas M. RuwartChief ScientistChief Scientist

[email protected]@sherwoodinfo.com

University of Minnesota

Digital Technology Center

Minneapolis, MN

October 8, 2007

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Why you are hereWhy you are here

• To learn about a relatively new conceptin the storage industry

• Concepts behind CRAP• Related issues and problems• Addressing those issues and

problems

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OrientationOrientation

• A bit of history• How did we get to this point?• Design requirements for enterprise-class storage• Design requirements for consumer-class storage• Principles of Commodity Reliability And

Practices• Why we need CRAP• Conclusions

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A bit of HistoryA bit of History

• What disk drives were like in the “oldendays”

• 1967-2007 in 10-year increments – theview from someone who lived through it

• Future history – were are we headed

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19671967

• Disk drive platters were 30-inches in diameter• Disk drives were the size of a large clothes

washing machine• A Million dollars per disk drive that held only a

few MegaBytes• Disk drives required daily maintenance of

cleaning heads and platters• Several people were crushed under the weight

of their iPods which held only one song at atime

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IBM 305 RAMAC

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19771977

• Disk drive platters are now 14-inches in diameter• Disk drive capacity up to about 315MB in a small

washing-machine sized box• Disk drives are still only used in computer centers• Disk drives were just beginning to be sealed so that

no physical maintenance was required for the headsor media

• Media maintenance for dealing with bad spots wasrequired on a monthly basis

• iPods now carried by pack mules and elephants andas such, never caught on in the US

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19871987• The 8-inch disk drive form factor is the standard for “enterprise-

class” disk drives and uses the SMD or emerging IPI interface• The PC revolution gives rise to “consumer-class” hard disk

drives• Consumer-class disk drives start with the small form factor 5.25-

inch full height• ST506, ATA/IDE, SCSI, and ESDI are the new interfaces hard disk

drives for consumer use• Maintenance required to manage bad sectors but no other

physical maintenance required• RAID is just being invented… again• iPods become practical to the extent that they are smaller but

battery life is about 3 seconds so the Walkman wins

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19971997• The 8-inch and 5.25-inch hard disk drive form factors give way to the 3.5-

inch form factor (half-height)• 3.5-inch form factor is dominant in both enterprise-class and consumer-

class disk drives• Parallel SCSI and Fibre Channel SCSI replace all other interfaces for

enterprise-class disk drives• IDE and EIDE are the standard consumer-class disk drive interface• Capacities/Densities on both enterprise-class and consumer-class disk

drives are equivalent• No maintenance required – bad sector management an integral part of

each disk drive• Zone-bit recording significantly increases disk drive capacities• RAID Arrays are in wide use to increase data integrity and disk storage

reliability as well as performance with minimal tradeoff in capacity• iPods are deemed a waste of time because everything will be on

miniDISC or DAT

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20072007• The 3.5-inch, low profile (1-inch high) form factor is dominant in both

enterprise-class and consumer-class storage• The 2.5-inch form factor starting to make an appearance in the data

center• 2.5-inch (laptop drive) and 1.8-inch (iPod) disk drives are dominant in

mobile devices• Sub-1.8-inch disk drives being replaced by FLASH• Consumer-class disk drives maintain a consistently higher bit density

and drive capacity than Enterprise-class disk drives• Enterprise-class disk drives maintain higher RPM and faster access

times over consumer-class disk drives and 3-4x drive cost• Enterprise-class disk drives giving way to consumer-class disk drives in

previously Enterprise-class applications• Concerns rise over use of Consumer-class storage in Enterprise-class

applications• iPods take over and begin to network themselves together to form

another, higher intelligent life-form based solely on pop music. We call it:

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20172017• The 2.5-inch and 1.8-inch form factors are dominant in

both enterprise-class and some consumer-classstorage

• Data centers beginning to give up on disk drives andwant to revert to using punch-cards

• Mobile devices are primarily FLASH-based• Sub-1.8-inch disk drives being replaced by FLASH• Consumer-class disk drives dominant in Enterprise-

class applications – distinction between Consumer-class and Enterprise-class disk drives is narrow

• Concerns rise over the US President’s demand topaint the White House purple

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77””

Where Drive Form Factors Come From.Where Drive Form Factors Come From.

5.255.25””

5.255.25””3.53.5””

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WhatWhat’’s inside a Video IPODs inside a Video IPODI knew it was too good to be true….

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LetLet’’s talk about the Lunaticss talk about the Lunatics• High-End Computing (HEC) Community

– BIG data or LOTS of data, locally and widelydistributed, high bandwidth access or hightransaction rate, relatively few users, secure,short-term and long-term retention

• High Energy Physics (HEP) – Fermilab,CERN, DESY– BIG data, locally distributed, widely available,

moderate number of users, sparse access,long-term retention

• DARPA – Interagency High ProductivityComputing Systems– Design and build a peta-scale

computer system that is usablefor the year 2010

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HEP HEP –– FermilabFermilab and CMS and CMS• The Compact Muon Solenoid (CMS -

http://cms.cern.ch )– $750M Experiment being built at CERN in Switzerland– Will be active in 2007

• The Easy Part – collecting the data– Data rate from the detectors is ~1 PB/sec– Data rate after filtering is a few GB/sec

• The Hard Part: Storing and Access– Dataset for a single experiment is ~1PB– Several experiments per year are run– Must be made available to 5000 scientists all over the planet

(Earth primarily) for the next 10-25 years– Dense dataset, sparse data access by any one scientist– Access patterns are not deterministic

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Tier 1

Tier2 Center

Online System

eventreconstruction

French RegionalCenter

GermanRegional Center

InstituteInstituteInstituteInstitute~0.25TIPS

Workstations

~100MBytes/sec

~0.6-2.5 Gbps

100 - 1000Mbits/sec

Physics data cache

~PByte/sec

~2.5 Gbits/sec

Tier2 CenterTier2 CenterTier2 Center

Tier 0 +1

Tier 3

Tier 4

Tier2 Center

LHC Data Grid HierarchyLHC Data Grid HierarchyCMS as example, Atlas is similarCMS as example, Atlas is similar

Tier 2

CERN/CMS data goes to 6-8 Tier 1 regional centers,and from each of these to 6-10 Tier 2 centers.

Physicists work on analysis “channels” at 135institutes. Each institute has ~10 physicists workingon one or more channels.2000 physicists in 31 countries are involved in this20-year experiment in which DOE is a major player.

CMS detector: 15m X 15m X 22m

12,500 tons, $700M.

human=2m

analysis

eventsimulation

Italian Center FermiLab, USARegional Center

CourtesyHarvey

Newman,CalTech and

CERN

~0.6-2.5 Gbps

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2020

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What are the DARPA requirements?What are the DARPA requirements?

• HEC Community – The High ProductivityComputing Systems (HPCS) from DARPA– 1015 computations per second – Peta-scale computing– 1-10 trillion files in a single file system– 100’s of thousands of processors– Millions of process threads all needing and generating

data– 1-100 TBytes/sec aggregate bandwidth to disk– 30,000+ file creations per second– Focus on ease of use, efficiency, and RAS

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Lots of things have to scale Lots of things have to scaleFile System Attributes

1999 2002 2005 2008Teraflops 3.9 30 100 400

Memory size (TB) 2.6 13-20 32-67 44-167

File system size (TB) 75 200 - 600 500 -2,000 20,000

Number of Client Tasks 8192 16384 32,768 65,536

Number of Users 1,000 4,000 6,000 10,000

Number of Directories 5.0*106 1.5*107 1.8*107 2*108

Metadata RatesData Rate

500/sec1 mds

3 GB/sec

2000/sec1 mds

30 GB/sec

20,000/secn mds

100 GB/sec

50,000/secn mds

400 GB/secNumber of Files 1.0*109 4.0*109 1.0*1010 2.0*1012

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What are we getting ourselves into?What are we getting ourselves into?• 1TB/sec

– 20,000 disk drives• @ 50MB/sec/disk average• @ 10ms average access time ≈ 2 million IOPS• @ 1TB/disk ≈ 20PB raw capacity• @ 25watts/disk (including cooling power) ≈ 500 KWatts

– 40,000 disk drives in an real design to includeredundancy

• Space and power/cooling increase by 2x ≈1MWatt

– And that is just the beginning….– 10TB/sec would be up to 400,000 disk drives

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What does 1TB/sec really mean?What does 1TB/sec really mean?

• To what?– 1,000 processes @ 1GB/sec each?– 100,000 processes at 10MB/sec each?– Assumes a process/processor can

absorb/generate data at that rate– Current data:instruction ratio is about 10:1

• Therefore, 1TB/sec implies 100GFlops• Thus 1PFlop implies a data rate of 100TB/sec –

opps.

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Digging ourselves in deeper?Digging ourselves in deeper?• 1 Trillion Files

– 30,000 file creations per second for 1 year = 1 trillion files– 1PB of MetaData to describe 1Trillion files– Finding any one file within 1 Trillion files– Finding anything inside of the 1 Trillion files– This is a major transactional problem not a bandwidth

problem– Traditional file systems and associated [POSIX] semantics

break down at these scales – need new/relaxed semantics– Is the concept of a “file” still valid in this context?

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The Growing Disk Drive BottleneckThe Growing Disk Drive Bottleneck Subsystem

19931

2007E1

Increase

Network I/O2

0.001

2

2000x Intel CPU

0.48

100

200x

Storage Channel I/O3

0.05

4

80x PCI

7

0.13

16

123x

Intel Front Side Processor Bus

0.53

13

24x Random Disk IOPS

5 90 150 1.7x

Random Disk IOPS per Gbyte5,6

43 4.2 -10x

Sequential Disk I/O4

0.005 0.1 20x

Sequential Disk BW/Gbyte 0.005 0.0001 -50x

Notes: 1 Speed of subsystem in GBps

2 Ethernet

3 SCSI and Fibre Channel

4 IBM 3.5 inch drives internal data rate

5 IBM 3.5 inch drives se ek + rotational latency

6 Horison/Fred Moore

7 PCI versus 16xPCIe

Source: www.ArchiveBuilders.com, "Evolution of Intel Microprocessors: 1971 to 2001”

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Need more disks, not higher capacity onesNeed more disks, not higher capacity ones• Disk drive capacity improves faster than

– Data transfer rate– Seek time– Rotational Latency

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Access DensityAccess Density

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Serious QuestionsSerious Questions

• How do you package it?• How do you maintain it?• How do you connect it all together?• How do you access/use a storage system

with 250,000 disk drives?

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How do you package this?How do you package this?

• Conservatively one hundred 3½ inch disksper rack with controllers

• 400 racks of disk drives and controllers• 8,000 square feet• 10TB/sec is 10 times this or about the size

of two football fields (~100,000 sq ft)

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How do you maintain it?How do you maintain it?

• Assume– 40,000 disk configuration– 2,000,000 hours MTBF per Enterprise-class disk– 300,000 hours MTBF per Consumer-class disk

• ~4 disk failure per week for Enterprise-classdisks

• ~20 failures per week for Consumer-class disks• Continual rebuilds in progress• 10TB/sec is 10 times this

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How do you connect it all together?How do you connect it all together?• 10Gbit/sec/channel → 1,000 channels @ 100%

efficiency• Implies a 2,000 channel non-blocking switch fabric• What about transceiver failure rates• When it breaks, how do you

find the broken transceiver?• 10TB/sec – who on earth would

want to do that? (don’t ask)

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How do you use this?How do you use this?• Current file system technology is based on

30+ year-old designs and does not scale• Disk I/O software stack is 30+ years old

and does not scale• Need lots of innovation in many areas

– Common shared file system interfaces– Data Life Cycle Management and seamless

integration into existing HEC environments– Changes to standards that offer greater

scalability without sacrificing data integrity– Streaming I/O from zillions of single nodes– Data alignment, small-block, large-block,

and RAID issues– File System Metadata

Application

OperatingSystem

Storage andTransport

Application

OperatingSystem

Storage andTransport

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Commodity Reliability And PracticesCommodity Reliability And Practices• Processors, Networks, Graphics Engines have for the

most part gone “commodity”• Disk drives are still largely “enterprise-class”• Significant pressure to move toward more use of

commodity disk drives• Requires a fundamental change in how we think about

RAS for storage – i.e. Fail-In-Place• Assumes something is always in the process of breaking• Must re-orient engineering to think about how to build

reliable systems using unreliable components• AKA – How to build reliable systems using CRAP

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What is CRAP?What is CRAP?• Successful systems are designed to be “fault-tolerant” – faults are a

normal occurrence• Until recently, systems were designed and assumed to be highly-

reliable and faults were an anomaly rather than a normal occurrence• That was possible due to the relatively “low” part count in a given

system• In order to make computations go faster, significantly more

parallelism is needed• Parallelism implies a far greater “part count”• A natural consequence of higher part count is a higher failure rate of

some part in the system as a whole• However, there is a great deal of duplication in highly parallel or

high-part-count systems• Need to take advantage of this parallelism

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So, what is CRAP?So, what is CRAP?• High part-count systems must contain a large number of

“commodity” components to be commercially viable• Commodity components are less expensive and arguably less

reliable in enterprise-class applications• Thus, Systems should be designed with Commodity Reliability in

mind• Commodity Reliability means that at any point in time, something is

in the process of failing within the system as a whole• Given that something is always in the process of breaking,

appropriate Engineering Practices must be employed to maintain:– Data Access– Data Integrity– System Performance

• Requires a broader, systemic engineering view when designing withCRAP in order to ensure that things above and below a point offailure are minimally impacted – software and hardware

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WhatWhat’’s happening now?s happening now?• Areal Density is at about 150Gigabits per square inch• 3.5-inch form factor is currently the standard• 2.5-inch form factor is emerging in the enterprise• SAS and SATA are getting significant traction• OSD has been demonstrated and is in active

development• Consumer-grade storage is cheap cheap cheap• Commodity interface speeds are up to 10Gigabits/sec• Storage and Network processing engines are available• New applications for storage are rapidly evolving• Relaxed POSIX standards• NFS V4 and Parallel NFS

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Reaching Error Detection Code LimitsReaching Error Detection Code Limits• Error Detection Codes are statistical in nature• Current codes are rated at about 1 “undetected”

error in 1015 bits transferred or about 1 bit inevery 100 TeraBytes

• As storage capacities and transfer ratesincrease, the current error “detection” codes willno longer be sufficient to guard against silentdata corruption

• Need “stronger”, non-intrusive error “detection”codes at multiple levels

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ConclusionsConclusions• Need CRAP to design the next generation of

scalable, high-performance systems• System design is highly dependent on

leveraging commodity components

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Zone Bit RecordingZone Bit Recording

• Commonly used technique to maximizeuse of media area

• More sectors recorded on the outer tracksthan inner tracks

• Bit density remains constant but the datarate changes from zone to zone

• Typically 10-100 zones on a disk – variesfrom mfg to mfg, model to model

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Example of Zones in ZBRExample of Zones in ZBR

Zone Map of the Fujitsu 60 GB 5400 RPM 2.5-inch SATA Disk

15

17

19

21

23

25

27

29

31

33

35

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95

Percent of disk from outer to inner tracks

Ban

dw

idth

in

MB

/sec

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Adaptive FormattingAdaptive Formatting

• ZBR on steroids• Each head is “tuned” to maximize the

signal-to-noise ratio of each individualtrack

• Results in different effective data rate foreach track

• Results in a variable number of sectorsper track

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Example of Example of ““zoneszones”” in AF in AFSeagate 100 GB 5400 RPM Momentus

0

5

10

15

20

25

30

35

40

0 10 20 30 40 50 60 70 80 90

Percent of disk from outer to inner tracks

Ba

nd

wid

th i

n M

B/s

ec