SlideShare a Scribd company logo
1 of 20
Download to read offline
Copyright©2014 NTT Corp. All Rights Reserved. 
Durability Simulator Design for OpenStack Swift (Interactive Durability Calculation Tools) 
Kota Tsuyuzaki [IRC: kota_] 
tsuyuzaki.kota@lab.ntt.co.jp 
NTT Software Innovation Center 
Copyright(c)2009-2014 NTT CORPORATION. All Rights Reserved.
2 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Goal & Benefits 
•How to calculate? 
•Demo 
Outline 
Etherpad: 
https://etherpad.openstack.org/p/kilo-swift-durability-simulator
3 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
Issue 
User 
I wanna build a durable object storage system by 
using OpenStack Swift. I wanna know also the durability 
to confirm it will be enough for our SLA.
4 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
Issue 
User 
Provider A 
Provider B 
Provider C 
Hey, guys. Could you tell me the 
Swift system architecture and its 
storage durability you support. 
OpenStack Providers
5 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
Issue 
User 
Provider A 
Provider B 
Provider C 
A: 7-9s durability 
with 3 copies 
B: 9-9s durability 
with 3 copies 
C: 11-9s durability 
with 3 copies 
WHAT’S HAPPEN!? 
WHICH IS CORRECT? 
OpenStack Providers
6 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Goal 
•Building durability calculation tools supported (or recommended) by Swift community 
•Enabling to get the calculation result easily from both specs of system component HWs and swift configures. (e.g. # of disks, size of each disk, # of partitions) 
•Benefits 
•Swift Administrators (almost beginners) can find their own system durability easily 
•Enable to standardize the calculation definition among Swift providers 
•Swift Users can choose the policy for their use case (Replica? EC? Which # of parities are best for you?) 
Goal & Benefits
7 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
How to calculate the durability?
8 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
For Replica Case
9 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Calculation Using Markov Model (Markov Process) 
•2 Replica -> k = 1, m = 1 
•i.e. Data Lost with 2 Fragments 
•3 Replica -> k = 1, m = 2 
•i.e. Data Lost with 3 Fragments 
•Reference: 
•[1]: "Reliability Mechanisms for Very Large Storage Systems" 
•http://www.ssrc.ucsc.edu/Papers/xin-mss03.pdf 
How to Calculate EC Durability? 
[1]
10 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Redundancy Set[1]: 
•Definition 
•A block group composed of data blocks or object and their associated replicas or parity blocks. A single redundancy set will typically contain 1MB to 1TB, though we expect that redundancy sets will be at least 1GB to minimize bookkeeping overhead and reduce the likelihood that two redundancy sets will be stored on the same set of object storage system. 
•Assuming a Reduandancy Set as a Partition 
Consideration for Swift’s Partition 
Ring 
MD5*(URL) = index 
partitions 
idx 
Copy 1 
Copy 2 
Copy 3 
0 
1 
5 
7 
… 
… 
… 
… 
8 
3 
2 
6 
Partition table from part to device id. 
From [1]
11 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Definition: 
•Absorbing State: The end state in the state transition model. 
•P: Transition Probability Matrix 
Markov Process (1) 
Absorbing State 
Temporary State 
P=푄푈 푂퐼 ퟏ−ퟐ흁ퟐ흁ퟎ 풗ퟏ−(흁+풗)흁 ퟎퟎퟏ 
Q: Transition Probability Matrix among Temporary State 
U: Probability Matrix from Temporary State into Absorbing State 
O: Zero Matrix、I: Identity Matrix 
State0 
State1 
State2
12 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Time (t) Limitation of State Transition Matrix (P) shows average # of state transition (M) from initial state to absorbing state 
•MTTDL (Time to be absorbing state) calculated from sum of each rows in MN 
Markov Process (2) 
퐥퐢퐦 풕→∞ 푷풕=ퟎ푴푼 ퟎ푰 
M = (I-Q)-1 
MTTDLrs = M ퟏ ⋮ ퟏ 
P= ퟏ−ퟐ흁ퟐ흁ퟎ 풗ퟏ−(흁+풗)흁 ퟎퟎퟏ 
ퟏ ퟐ흁 흁+풗 흁 ퟐ 풗 흁 ퟐ 
State Transition Matrix for 2 replica 
M 
MTTDLrs 
ퟏ ퟐ흁ퟐ ퟑ흁+풗 ퟐ흁+풗 
Durability = 1 – N/ MTTDLrs 
Probability for Data Lost 
Durability 
1 - 2푵흁ퟐ ퟏ ퟑ흁+풗 ퟏ ퟐ흁+풗
13 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
For EC Case
14 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Object Size(bytes): n 
•# of Sliced Raw Objects: k 
•# of Parities: m 
•Total # of Fragments: k + m 
•Fragment Size(bytes): n / k (+ checksum) 
•Total Stored Size (bytes): Fragment Size * (k + m) 
Erasure Code Definition 
object 
Data 
fragment 
Data 
fragment 
parity 
fragment 
parity 
fragment 
… 
… 
k 
m 
encode 
decode 
Terminology Reference: 
http://specs.openstack.org/openstack/ 
swift-specs/specs/swift/erasure_coding.html
15 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Basic Idea 
•Expansion of Durability Calculation for Replica Model 
•Calculation Using Markov Model (Markov Process) 
•Replica Model based on Markov Process: 
•2 Replica -> k = 1, m = 1 
•i.e. Data Lost with 2 Fragments 
•3 Replica -> k = 1, m = 2 
•i.e. Data Lost with 3 Fragments 
How to Calculate EC Durability? 
[1] 
※ Markov Process works to calculate the durability with matrix calculation. [3]
16 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
•Algorithms 
•State: Status (exists or lost) for All fragments 
•Each state is transferred by constant probability 
•μ = Disk Failure Rate, v = Fragments Repair Rate 
•Each Rate related to # of Fragments 
•E.g. RAID related to # of Devices 
•Extract States to m + 1 (i.e. data lost) 
Durability Calculation Algorithms 
0 
1 
m-1 
m 
… 
m+1 
state transitions for “m” parities EC 
D = # of Devices (RAID5) 
N = k + m (N fragments located in the system) 
-Nμ 
v 
Nμ 
-(N-1)μ-v 
(N-m)μ 
mv 
(N-(m-1))μ 
-(N-(m-1))μ-mv
17 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
Demo
18 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
Demo
19 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
Demo
20 
Copyright©2014 NTT Corp. All Rights Reserved. 
NTT Confidential 
Kota Tsuyuzaki [IRC: kota_] tsuyuzaki.kota@lab.ntt.co.jp NTT Software Innovation Center 
Questions? 
Etherpad: 
https://etherpad.openstack.org/p/kilo-swift-durability-simulator

More Related Content

What's hot

OpenContrail Implementations
OpenContrail ImplementationsOpenContrail Implementations
OpenContrail ImplementationsJakub Pavlik
 
Introduction of Okinawa Open Laboratory Testbed, OpenStack and SDN Technology...
Introduction of Okinawa Open Laboratory Testbed, OpenStack and SDN Technology...Introduction of Okinawa Open Laboratory Testbed, OpenStack and SDN Technology...
Introduction of Okinawa Open Laboratory Testbed, OpenStack and SDN Technology...Takashi Torii
 
OpenStack Ottawa Q3 Meetup September 26th 2017
OpenStack Ottawa Q3 Meetup   September 26th 2017OpenStack Ottawa Q3 Meetup   September 26th 2017
OpenStack Ottawa Q3 Meetup September 26th 2017Stacy Véronneau
 
Greenplum: Building a Postgres Fabric for Large-Scale Analytical Computation ...
Greenplum: Building a Postgres Fabric for Large-Scale Analytical Computation ...Greenplum: Building a Postgres Fabric for Large-Scale Analytical Computation ...
Greenplum: Building a Postgres Fabric for Large-Scale Analytical Computation ...VMware Tanzu
 
CERN User Story
CERN User StoryCERN User Story
CERN User StoryTim Bell
 
Containers on Baremetal and Preemptible VMs at CERN and SKA
Containers on Baremetal and Preemptible VMs at CERN and SKAContainers on Baremetal and Preemptible VMs at CERN and SKA
Containers on Baremetal and Preemptible VMs at CERN and SKABelmiro Moreira
 

What's hot (8)

OpenContrail Implementations
OpenContrail ImplementationsOpenContrail Implementations
OpenContrail Implementations
 
OpenPOWER ADG key note
OpenPOWER ADG key note OpenPOWER ADG key note
OpenPOWER ADG key note
 
Introduction of Okinawa Open Laboratory Testbed, OpenStack and SDN Technology...
Introduction of Okinawa Open Laboratory Testbed, OpenStack and SDN Technology...Introduction of Okinawa Open Laboratory Testbed, OpenStack and SDN Technology...
Introduction of Okinawa Open Laboratory Testbed, OpenStack and SDN Technology...
 
OpenStack Ottawa Q3 Meetup September 26th 2017
OpenStack Ottawa Q3 Meetup   September 26th 2017OpenStack Ottawa Q3 Meetup   September 26th 2017
OpenStack Ottawa Q3 Meetup September 26th 2017
 
Greenplum: Building a Postgres Fabric for Large-Scale Analytical Computation ...
Greenplum: Building a Postgres Fabric for Large-Scale Analytical Computation ...Greenplum: Building a Postgres Fabric for Large-Scale Analytical Computation ...
Greenplum: Building a Postgres Fabric for Large-Scale Analytical Computation ...
 
CERN User Story
CERN User StoryCERN User Story
CERN User Story
 
Collect, summarize and notify of OpenStack's log
Collect, summarize and notify of OpenStack's logCollect, summarize and notify of OpenStack's log
Collect, summarize and notify of OpenStack's log
 
Containers on Baremetal and Preemptible VMs at CERN and SKA
Containers on Baremetal and Preemptible VMs at CERN and SKAContainers on Baremetal and Preemptible VMs at CERN and SKA
Containers on Baremetal and Preemptible VMs at CERN and SKA
 

Similar to Durability Simulator Design for OpenStack Swift

Future semantic segmentation with convolutional LSTM
Future semantic segmentation with convolutional LSTMFuture semantic segmentation with convolutional LSTM
Future semantic segmentation with convolutional LSTMKyuri Kim
 
OpenStack Summit Tokyo - Know-how of Challlenging Deploy/Operation NTT DOCOMO...
OpenStack Summit Tokyo - Know-how of Challlenging Deploy/Operation NTT DOCOMO...OpenStack Summit Tokyo - Know-how of Challlenging Deploy/Operation NTT DOCOMO...
OpenStack Summit Tokyo - Know-how of Challlenging Deploy/Operation NTT DOCOMO...Masaaki Nakagawa
 
Mike Bartley - Innovations for Testing Parallel Software - EuroSTAR 2012
Mike Bartley - Innovations for Testing Parallel Software - EuroSTAR 2012Mike Bartley - Innovations for Testing Parallel Software - EuroSTAR 2012
Mike Bartley - Innovations for Testing Parallel Software - EuroSTAR 2012TEST Huddle
 
Understanding performance aspects of etcd and Raft
Understanding performance aspects of etcd and RaftUnderstanding performance aspects of etcd and Raft
Understanding performance aspects of etcd and RaftHitoshi Mitake
 
Modeling the IoT with TitanDB and Cassandra
Modeling the IoT with TitanDB and CassandraModeling the IoT with TitanDB and Cassandra
Modeling the IoT with TitanDB and Cassandratwilmes
 
HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...
HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...
HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...Yuji Kubota
 
Tsinghua University: Two Exemplary Applications in China
Tsinghua University: Two Exemplary Applications in ChinaTsinghua University: Two Exemplary Applications in China
Tsinghua University: Two Exemplary Applications in ChinaDataStax Academy
 
Crash course on data streaming (with examples using Apache Flink)
Crash course on data streaming (with examples using Apache Flink)Crash course on data streaming (with examples using Apache Flink)
Crash course on data streaming (with examples using Apache Flink)Vincenzo Gulisano
 
IRJET - Predicting the Maximum Computational Power of Microprocessors using M...
IRJET - Predicting the Maximum Computational Power of Microprocessors using M...IRJET - Predicting the Maximum Computational Power of Microprocessors using M...
IRJET - Predicting the Maximum Computational Power of Microprocessors using M...IRJET Journal
 
The Pill for Your Migration Hell
The Pill for Your Migration HellThe Pill for Your Migration Hell
The Pill for Your Migration HellDatabricks
 
Transport SDN & OpenDaylight Use Cases in Korea
Transport SDN & OpenDaylight Use Cases in KoreaTransport SDN & OpenDaylight Use Cases in Korea
Transport SDN & OpenDaylight Use Cases in KoreaJustin Park
 
Online learning for low-latency streaming
Online learning for low-latency streamingOnline learning for low-latency streaming
Online learning for low-latency streamingTheo Karagkioules
 
Globecom 2015: Adaptive Raptor Carousel for 802.11
Globecom 2015: Adaptive Raptor Carousel for 802.11Globecom 2015: Adaptive Raptor Carousel for 802.11
Globecom 2015: Adaptive Raptor Carousel for 802.11Andrew Nix
 
The Role of Inter-Controller Traffic in SDN Controllers Placement
The Role of Inter-Controller Traffic in SDN Controllers PlacementThe Role of Inter-Controller Traffic in SDN Controllers Placement
The Role of Inter-Controller Traffic in SDN Controllers PlacementPaolo Giaccone
 
OpenTelemetry For Architects
OpenTelemetry For ArchitectsOpenTelemetry For Architects
OpenTelemetry For ArchitectsKevin Brockhoff
 
Basic Tutorial for Robotic Arm
Basic Tutorial for Robotic ArmBasic Tutorial for Robotic Arm
Basic Tutorial for Robotic ArmYu Wei Chen
 
Speeding up information extraction programs: a holistic optimizer and a learn...
Speeding up information extraction programs: a holistic optimizer and a learn...Speeding up information extraction programs: a holistic optimizer and a learn...
Speeding up information extraction programs: a holistic optimizer and a learn...INRIA-OAK
 

Similar to Durability Simulator Design for OpenStack Swift (20)

Future semantic segmentation with convolutional LSTM
Future semantic segmentation with convolutional LSTMFuture semantic segmentation with convolutional LSTM
Future semantic segmentation with convolutional LSTM
 
OpenStack Summit Tokyo - Know-how of Challlenging Deploy/Operation NTT DOCOMO...
OpenStack Summit Tokyo - Know-how of Challlenging Deploy/Operation NTT DOCOMO...OpenStack Summit Tokyo - Know-how of Challlenging Deploy/Operation NTT DOCOMO...
OpenStack Summit Tokyo - Know-how of Challlenging Deploy/Operation NTT DOCOMO...
 
Mike Bartley - Innovations for Testing Parallel Software - EuroSTAR 2012
Mike Bartley - Innovations for Testing Parallel Software - EuroSTAR 2012Mike Bartley - Innovations for Testing Parallel Software - EuroSTAR 2012
Mike Bartley - Innovations for Testing Parallel Software - EuroSTAR 2012
 
BIRTE-13-Kawashima
BIRTE-13-KawashimaBIRTE-13-Kawashima
BIRTE-13-Kawashima
 
Understanding performance aspects of etcd and Raft
Understanding performance aspects of etcd and RaftUnderstanding performance aspects of etcd and Raft
Understanding performance aspects of etcd and Raft
 
Modeling the IoT with TitanDB and Cassandra
Modeling the IoT with TitanDB and CassandraModeling the IoT with TitanDB and Cassandra
Modeling the IoT with TitanDB and Cassandra
 
HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...
HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...
HeapStats: Troubleshooting with Serviceability and the New Runtime Monitoring...
 
Tsinghua University: Two Exemplary Applications in China
Tsinghua University: Two Exemplary Applications in ChinaTsinghua University: Two Exemplary Applications in China
Tsinghua University: Two Exemplary Applications in China
 
Icbai 2018 ver_1
Icbai 2018 ver_1Icbai 2018 ver_1
Icbai 2018 ver_1
 
Crash course on data streaming (with examples using Apache Flink)
Crash course on data streaming (with examples using Apache Flink)Crash course on data streaming (with examples using Apache Flink)
Crash course on data streaming (with examples using Apache Flink)
 
IRJET - Predicting the Maximum Computational Power of Microprocessors using M...
IRJET - Predicting the Maximum Computational Power of Microprocessors using M...IRJET - Predicting the Maximum Computational Power of Microprocessors using M...
IRJET - Predicting the Maximum Computational Power of Microprocessors using M...
 
The Pill for Your Migration Hell
The Pill for Your Migration HellThe Pill for Your Migration Hell
The Pill for Your Migration Hell
 
Transport SDN & OpenDaylight Use Cases in Korea
Transport SDN & OpenDaylight Use Cases in KoreaTransport SDN & OpenDaylight Use Cases in Korea
Transport SDN & OpenDaylight Use Cases in Korea
 
Online learning for low-latency streaming
Online learning for low-latency streamingOnline learning for low-latency streaming
Online learning for low-latency streaming
 
Globecom 2015: Adaptive Raptor Carousel for 802.11
Globecom 2015: Adaptive Raptor Carousel for 802.11Globecom 2015: Adaptive Raptor Carousel for 802.11
Globecom 2015: Adaptive Raptor Carousel for 802.11
 
The Role of Inter-Controller Traffic in SDN Controllers Placement
The Role of Inter-Controller Traffic in SDN Controllers PlacementThe Role of Inter-Controller Traffic in SDN Controllers Placement
The Role of Inter-Controller Traffic in SDN Controllers Placement
 
OpenTelemetry For Architects
OpenTelemetry For ArchitectsOpenTelemetry For Architects
OpenTelemetry For Architects
 
Digital_system_design_A (1).ppt
Digital_system_design_A (1).pptDigital_system_design_A (1).ppt
Digital_system_design_A (1).ppt
 
Basic Tutorial for Robotic Arm
Basic Tutorial for Robotic ArmBasic Tutorial for Robotic Arm
Basic Tutorial for Robotic Arm
 
Speeding up information extraction programs: a holistic optimizer and a learn...
Speeding up information extraction programs: a holistic optimizer and a learn...Speeding up information extraction programs: a holistic optimizer and a learn...
Speeding up information extraction programs: a holistic optimizer and a learn...
 

More from Kota Tsuyuzaki

Storlets Project Update for Train
Storlets Project Update for TrainStorlets Project Update for Train
Storlets Project Update for TrainKota Tsuyuzaki
 
Project Updates Storlets Denver 2019
Project Updates Storlets Denver 2019Project Updates Storlets Denver 2019
Project Updates Storlets Denver 2019Kota Tsuyuzaki
 
NVIDIA/deepopsを触ってみた話
NVIDIA/deepopsを触ってみた話NVIDIA/deepopsを触ってみた話
NVIDIA/deepopsを触ってみた話Kota Tsuyuzaki
 
OpenStack Swift Introduction 2019
OpenStack Swift Introduction 2019OpenStack Swift Introduction 2019
OpenStack Swift Introduction 2019Kota Tsuyuzaki
 
Case Study: Large Scale Deployment for Machine Learning with Highspeed Storage
Case Study: Large Scale Deployment for Machine Learning with Highspeed StorageCase Study: Large Scale Deployment for Machine Learning with Highspeed Storage
Case Study: Large Scale Deployment for Machine Learning with Highspeed StorageKota Tsuyuzaki
 
OpenStack Summit Storlets Project Update Queens
OpenStack Summit Storlets Project Update QueensOpenStack Summit Storlets Project Update Queens
OpenStack Summit Storlets Project Update QueensKota Tsuyuzaki
 
OpenStack Swiftの最新機能とStorlets
OpenStack Swiftの最新機能とStorletsOpenStack Swiftの最新機能とStorlets
OpenStack Swiftの最新機能とStorletsKota Tsuyuzaki
 
Using Storlets/Docker For Large Scale Image Processing
Using Storlets/Docker For Large Scale Image ProcessingUsing Storlets/Docker For Large Scale Image Processing
Using Storlets/Docker For Large Scale Image ProcessingKota Tsuyuzaki
 
OpenStack Summit Vancouver Swift 報告
OpenStack Summit Vancouver Swift 報告OpenStack Summit Vancouver Swift 報告
OpenStack Summit Vancouver Swift 報告Kota Tsuyuzaki
 
Container Listing Update (Liberty Swift Design Summit)
Container Listing Update (Liberty Swift Design Summit)Container Listing Update (Liberty Swift Design Summit)
Container Listing Update (Liberty Swift Design Summit)Kota Tsuyuzaki
 
日本OpenStackユーザ会 Atlantaサミット報告会 Swift関連報告
日本OpenStackユーザ会 Atlantaサミット報告会 Swift関連報告日本OpenStackユーザ会 Atlantaサミット報告会 Swift関連報告
日本OpenStackユーザ会 Atlantaサミット報告会 Swift関連報告Kota Tsuyuzaki
 

More from Kota Tsuyuzaki (12)

Storlets Project Update for Train
Storlets Project Update for TrainStorlets Project Update for Train
Storlets Project Update for Train
 
Project Updates Storlets Denver 2019
Project Updates Storlets Denver 2019Project Updates Storlets Denver 2019
Project Updates Storlets Denver 2019
 
NVIDIA/deepopsを触ってみた話
NVIDIA/deepopsを触ってみた話NVIDIA/deepopsを触ってみた話
NVIDIA/deepopsを触ってみた話
 
OpenStack Swift Introduction 2019
OpenStack Swift Introduction 2019OpenStack Swift Introduction 2019
OpenStack Swift Introduction 2019
 
Case Study: Large Scale Deployment for Machine Learning with Highspeed Storage
Case Study: Large Scale Deployment for Machine Learning with Highspeed StorageCase Study: Large Scale Deployment for Machine Learning with Highspeed Storage
Case Study: Large Scale Deployment for Machine Learning with Highspeed Storage
 
OpenStack Summit Storlets Project Update Queens
OpenStack Summit Storlets Project Update QueensOpenStack Summit Storlets Project Update Queens
OpenStack Summit Storlets Project Update Queens
 
OpenStack Swiftの最新機能とStorlets
OpenStack Swiftの最新機能とStorletsOpenStack Swiftの最新機能とStorlets
OpenStack Swiftの最新機能とStorlets
 
Using Storlets/Docker For Large Scale Image Processing
Using Storlets/Docker For Large Scale Image ProcessingUsing Storlets/Docker For Large Scale Image Processing
Using Storlets/Docker For Large Scale Image Processing
 
OpenStack Swift紹介
OpenStack Swift紹介OpenStack Swift紹介
OpenStack Swift紹介
 
OpenStack Summit Vancouver Swift 報告
OpenStack Summit Vancouver Swift 報告OpenStack Summit Vancouver Swift 報告
OpenStack Summit Vancouver Swift 報告
 
Container Listing Update (Liberty Swift Design Summit)
Container Listing Update (Liberty Swift Design Summit)Container Listing Update (Liberty Swift Design Summit)
Container Listing Update (Liberty Swift Design Summit)
 
日本OpenStackユーザ会 Atlantaサミット報告会 Swift関連報告
日本OpenStackユーザ会 Atlantaサミット報告会 Swift関連報告日本OpenStackユーザ会 Atlantaサミット報告会 Swift関連報告
日本OpenStackユーザ会 Atlantaサミット報告会 Swift関連報告
 

Recently uploaded

call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️Delhi Call girls
 
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...Health
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...MyIntelliSource, Inc.
 
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerHow To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerThousandEyes
 
Software Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsSoftware Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsArshad QA
 
Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVshikhaohhpro
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsAlberto González Trastoy
 
5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdfWave PLM
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsJhone kinadey
 
Hand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxHand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxbodapatigopi8531
 
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AISyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AIABDERRAOUF MEHENNI
 
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...OnePlan Solutions
 
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online ☂️
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online  ☂️CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online  ☂️
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online ☂️anilsa9823
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Modelsaagamshah0812
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...kellynguyen01
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comFatema Valibhai
 
How To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsHow To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsAndolasoft Inc
 
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...ICS
 

Recently uploaded (20)

Microsoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdfMicrosoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdf
 
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️
 
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
 
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerHow To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
 
Software Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsSoftware Quality Assurance Interview Questions
Software Quality Assurance Interview Questions
 
Optimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTVOptimizing AI for immediate response in Smart CCTV
Optimizing AI for immediate response in Smart CCTV
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
 
5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf5 Signs You Need a Fashion PLM Software.pdf
5 Signs You Need a Fashion PLM Software.pdf
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial Goals
 
Hand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxHand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptx
 
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AISyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
 
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
Tech Tuesday-Harness the Power of Effective Resource Planning with OnePlan’s ...
 
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS LiveVip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
 
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online ☂️
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online  ☂️CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online  ☂️
CALL ON ➥8923113531 🔝Call Girls Kakori Lucknow best sexual service Online ☂️
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Models
 
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
Short Story: Unveiling the Reasoning Abilities of Large Language Models by Ke...
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.com
 
How To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsHow To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.js
 
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
 

Durability Simulator Design for OpenStack Swift

  • 1. Copyright©2014 NTT Corp. All Rights Reserved. Durability Simulator Design for OpenStack Swift (Interactive Durability Calculation Tools) Kota Tsuyuzaki [IRC: kota_] tsuyuzaki.kota@lab.ntt.co.jp NTT Software Innovation Center Copyright(c)2009-2014 NTT CORPORATION. All Rights Reserved.
  • 2. 2 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Goal & Benefits •How to calculate? •Demo Outline Etherpad: https://etherpad.openstack.org/p/kilo-swift-durability-simulator
  • 3. 3 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential Issue User I wanna build a durable object storage system by using OpenStack Swift. I wanna know also the durability to confirm it will be enough for our SLA.
  • 4. 4 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential Issue User Provider A Provider B Provider C Hey, guys. Could you tell me the Swift system architecture and its storage durability you support. OpenStack Providers
  • 5. 5 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential Issue User Provider A Provider B Provider C A: 7-9s durability with 3 copies B: 9-9s durability with 3 copies C: 11-9s durability with 3 copies WHAT’S HAPPEN!? WHICH IS CORRECT? OpenStack Providers
  • 6. 6 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Goal •Building durability calculation tools supported (or recommended) by Swift community •Enabling to get the calculation result easily from both specs of system component HWs and swift configures. (e.g. # of disks, size of each disk, # of partitions) •Benefits •Swift Administrators (almost beginners) can find their own system durability easily •Enable to standardize the calculation definition among Swift providers •Swift Users can choose the policy for their use case (Replica? EC? Which # of parities are best for you?) Goal & Benefits
  • 7. 7 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential How to calculate the durability?
  • 8. 8 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential For Replica Case
  • 9. 9 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Calculation Using Markov Model (Markov Process) •2 Replica -> k = 1, m = 1 •i.e. Data Lost with 2 Fragments •3 Replica -> k = 1, m = 2 •i.e. Data Lost with 3 Fragments •Reference: •[1]: "Reliability Mechanisms for Very Large Storage Systems" •http://www.ssrc.ucsc.edu/Papers/xin-mss03.pdf How to Calculate EC Durability? [1]
  • 10. 10 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Redundancy Set[1]: •Definition •A block group composed of data blocks or object and their associated replicas or parity blocks. A single redundancy set will typically contain 1MB to 1TB, though we expect that redundancy sets will be at least 1GB to minimize bookkeeping overhead and reduce the likelihood that two redundancy sets will be stored on the same set of object storage system. •Assuming a Reduandancy Set as a Partition Consideration for Swift’s Partition Ring MD5*(URL) = index partitions idx Copy 1 Copy 2 Copy 3 0 1 5 7 … … … … 8 3 2 6 Partition table from part to device id. From [1]
  • 11. 11 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Definition: •Absorbing State: The end state in the state transition model. •P: Transition Probability Matrix Markov Process (1) Absorbing State Temporary State P=푄푈 푂퐼 ퟏ−ퟐ흁ퟐ흁ퟎ 풗ퟏ−(흁+풗)흁 ퟎퟎퟏ Q: Transition Probability Matrix among Temporary State U: Probability Matrix from Temporary State into Absorbing State O: Zero Matrix、I: Identity Matrix State0 State1 State2
  • 12. 12 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Time (t) Limitation of State Transition Matrix (P) shows average # of state transition (M) from initial state to absorbing state •MTTDL (Time to be absorbing state) calculated from sum of each rows in MN Markov Process (2) 퐥퐢퐦 풕→∞ 푷풕=ퟎ푴푼 ퟎ푰 M = (I-Q)-1 MTTDLrs = M ퟏ ⋮ ퟏ P= ퟏ−ퟐ흁ퟐ흁ퟎ 풗ퟏ−(흁+풗)흁 ퟎퟎퟏ ퟏ ퟐ흁 흁+풗 흁 ퟐ 풗 흁 ퟐ State Transition Matrix for 2 replica M MTTDLrs ퟏ ퟐ흁ퟐ ퟑ흁+풗 ퟐ흁+풗 Durability = 1 – N/ MTTDLrs Probability for Data Lost Durability 1 - 2푵흁ퟐ ퟏ ퟑ흁+풗 ퟏ ퟐ흁+풗
  • 13. 13 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential For EC Case
  • 14. 14 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Object Size(bytes): n •# of Sliced Raw Objects: k •# of Parities: m •Total # of Fragments: k + m •Fragment Size(bytes): n / k (+ checksum) •Total Stored Size (bytes): Fragment Size * (k + m) Erasure Code Definition object Data fragment Data fragment parity fragment parity fragment … … k m encode decode Terminology Reference: http://specs.openstack.org/openstack/ swift-specs/specs/swift/erasure_coding.html
  • 15. 15 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Basic Idea •Expansion of Durability Calculation for Replica Model •Calculation Using Markov Model (Markov Process) •Replica Model based on Markov Process: •2 Replica -> k = 1, m = 1 •i.e. Data Lost with 2 Fragments •3 Replica -> k = 1, m = 2 •i.e. Data Lost with 3 Fragments How to Calculate EC Durability? [1] ※ Markov Process works to calculate the durability with matrix calculation. [3]
  • 16. 16 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential •Algorithms •State: Status (exists or lost) for All fragments •Each state is transferred by constant probability •μ = Disk Failure Rate, v = Fragments Repair Rate •Each Rate related to # of Fragments •E.g. RAID related to # of Devices •Extract States to m + 1 (i.e. data lost) Durability Calculation Algorithms 0 1 m-1 m … m+1 state transitions for “m” parities EC D = # of Devices (RAID5) N = k + m (N fragments located in the system) -Nμ v Nμ -(N-1)μ-v (N-m)μ mv (N-(m-1))μ -(N-(m-1))μ-mv
  • 17. 17 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential Demo
  • 18. 18 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential Demo
  • 19. 19 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential Demo
  • 20. 20 Copyright©2014 NTT Corp. All Rights Reserved. NTT Confidential Kota Tsuyuzaki [IRC: kota_] tsuyuzaki.kota@lab.ntt.co.jp NTT Software Innovation Center Questions? Etherpad: https://etherpad.openstack.org/p/kilo-swift-durability-simulator