Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
メルカリのマーケット健全化施策を支えるML基盤
Search
Hirofumi Nakagawa/中河 宏文
May 23, 2018
Programming
10
9k
メルカリのマーケット健全化施策を支えるML基盤
Hirofumi Nakagawa/中河 宏文
May 23, 2018
Tweet
Share
More Decks by Hirofumi Nakagawa/中河 宏文
See All by Hirofumi Nakagawa/中河 宏文
IoTデバイスでMLモデルを動かす技術
hnakagawa
0
160
Kanazawa_AI.pdf
hnakagawa
0
170
メルカリ写真検索における Amazon EKS の活用事例と プロダクトにおけるEdgeAI technologyの展望
hnakagawa
5
8.9k
メルカリの写真検索を支えるバックエンド CCSE 2019 version
hnakagawa
0
310
メルカリ写真検索における Amazon EKS の活用事例
hnakagawa
6
29k
メルカリの写真検索を支えるバックエンド
hnakagawa
1
1.1k
Mercari ML Platform
hnakagawa
1
17k
mlct.pdf
hnakagawa
2
2k
機械学習によるマーケット健全化施策を支える技術
hnakagawa
0
230
Other Decks in Programming
See All in Programming
状態と共に暮らす:ステートフルへの挑戦
ypresto
3
1.3k
カオスに立ち向かう小規模チームの装備の選択〜フルスタックTSという装備の強み _ 弱み〜/Choosing equipment for a small team facing chaos ~ Strengths and weaknesses of full-stack TS~
bitkey
1
150
flutter_kaigi_mini_4.pdf
nobu74658
0
160
一緒に働きたくなるプログラマの思想 #QiitaConference
mu_zaru
82
21k
note の Elasticsearch 更新系を支える技術
tchov
9
3.6k
Ruby で作る RISC-V CPU エミュレーター / RISC-V CPU emulator made with Ruby
hayaokimura
5
1.2k
生成AI時代のフルスタック開発
kenn
7
820
プロフェッショナルとしての成長「問題の深掘り」が導く真のスキルアップ / issue-analysis-and-skill-up
minodriven
8
2k
“技術カンファレンスで何か変わる?” ──RubyKaigi後の自分とチームを振り返る
ssagara00
0
120
GitHub Copilot for Azureを使い倒したい
ymd65536
1
340
Boast Code Party / RubyKaigi 2025 After Event
lemonade_37
0
110
Vibe Coding の話をしよう
schroneko
14
3.9k
Featured
See All Featured
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
32
5.6k
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
29
2.6k
The Pragmatic Product Professional
lauravandoore
33
6.6k
Raft: Consensus for Rubyists
vanstee
137
6.9k
Bash Introduction
62gerente
613
210k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
41
2.3k
Practical Orchestrator
shlominoach
187
11k
The Illustrated Children's Guide to Kubernetes
chrisshort
48
50k
Designing Experiences People Love
moore
142
24k
Become a Pro
speakerdeck
PRO
28
5.3k
Building an army of robots
kneath
305
45k
Reflections from 52 weeks, 52 projects
jeffersonlam
349
20k
Transcript
ϝϧΧϦͷϚʔέοτ݈શԽ ࢪࡦΛࢧ͑ΔMLج൫ Mercari ML Ops Night Vol.1 hnakagawa
ࣗݾհ • Hirofumi Nakagawa (hnakagawa) • 20177݄ೖࣾ • ॴଐSRE •
σόΠευϥΠό։ൃ͔Βϑϩϯ τΤϯυ։ൃ·ͰΔԿͰ • NOT MLΤϯδχΞ • https://github.com/hnakagawa
͓ࣄ • ML Platform։ൃ • MLΤϯδχΞͱSREͷεΩϧΪϟοϓΛຒΊ Δ • ML Reliability,
SysML?, MLOps? • SREͷཱ͔ΒMLγεςϜͷࣗಈԽΛߦ͏
ML Platform • ͷML Platform • kubernetesϕʔε • ϩʔΧϧڥͱΫϥελڥͷ ࠩΛநԽ͢Δ
• ศརAPI܈ • طଘͷML FrameworkΛ༻͠ ؆୯ʹTraining/ServingΛߦ͏ ڥΛఏڙ
ͦͷ͏ͪOSSͰެ։༧ఆ(ଟ
ࣄྫ ϦΞϧλΠϜࢹγεςϜ • ௨শ Lovemachine • ML Platform্ʹ࣮͞Ε͍ͯΔ .-1MBUGPSN USBJOJOHDMVTUFS
-PWFNBDIJOF ($4 GKE PubSub .-1MBUGPSN TFSWJOHDMVTUFS -PWFNBDIJOF
Model Training & Serving Workflow
.-1MBUGPSN USBJOJOHDMVTUFS Workflow for Production $* .-1MBUGPSN TFSWJOHDMVTUFSGPSUFTU .PEFM3FHJTUSZ +PC
+PC ɾɾ 3&45 "1* 4USFBNJOH 5' 4FSWJOH ɾɾɾ
.-1MBUGPSN USBJOJOHDMVTUFS Training Workflow $* .PEFM3FHJTUSZ +PC +PC ɾɾɾ 1.
GitHubͷpushΛτϦΨʹtrainingΛىಈ 2. Training͞ΕͨModelModel Registry ্͕Δ
Serving Workflow .-1MBUGPSN TFSWJOHDMVTUFSGPSUFTU .PEFM3FHJTUSZ ɾɾ 3&45 "1* 4USFBNJOH 5'
4FSWJOH ɾɾɾ 1. Model RegistryΛࢹͯࣗ͠ಈͰModel ΛServing 2. Serving&Test͕ޭ͢Δͱຊ൪༻k8s manifestΛग़ྗ
Model Serving APIͷߏྫ 5FOTPS'MPX 4FSWJOH 5' .PEFM 5' .PEFM 'MBTL
4, .PEFM 4, .PEFM 4, .PEFM gRPC .FSDBSJ"1* REST FlaskͰલॲཧΛߦ͍ ཪͷTensorFlow Servingʹ͍͛ͯΔ
Model Serving API Streaming ver ͷߏྫ 5FOTPS'MPX 4FSWJOH 5' .PEFM
5' .PEFM .-1MBUGPSN 'SBNFXPSL PS "QBDIF#FBN 4, .PEFM 4, .PEFM 4, .PEFM gRPC PubSub
TensorFlow Serving • TensorFlow project͕ఏڙͯ͠ ͍ΔServingڥ • PythonॲཧܥΛհͣ͞ʹTFͷ modelΛservingͰ͖Δ •
ඪ४ͷ࣮ͰgRPCͰAPIΛ ఏڙ
ModelͱίϯςφɾΠϝʔδ • ڊେͳML ModelΛίϯςφɾΠϝʔδʹؚΊ Δ͔൱͔ • ؚΊͳ͍ͷͰ͋ΕԿॲʹஔ͢Δ͔ • ϙʔλϏϦςΟੑͱϩʔυ࣌ؒͷτϨʔυΦϑ •
ྑ͍ΞΠσΟΞ͕͋Εڭ͑ͯԼ͍͞…
௨ৗͷAPIͱҧ͏ • ѻ͏ϦιʔεɺModelαΠζ͕େ͖͘ͳΔ ߹͕ଟ͍(ඦMBʙGB) • CPUɾϝϞϦϦιʔεͷফඅ͕ܹ͍͠ • ߹ʹΑͬͯGPU͏
ϝϞϦফඅ • LovemachineͷPython࣮෦࣮ߦ࣌ʹ 2GBϝϞϦΛফඅ͢Δˠࠓޙ͞Βʹ૿͑Δ༧ ఆ͋Δ • Scikit-learnͰهड़͞ΕͨTF-IDFͷલॲཧ෦ ͕େ͖͘ͳΔࣄ͕ଟ͍
Pythonͱฒྻੑ • વThread͕͑ͳ͍(GILͷͨΊ) • ϓϩηεຖʹModelΛϩʔυ͢Δͱඞཁͳϝ ϞϦαΠζ͕େ͖͘ͳΔˠ Blue-Green DeployͷোʹͳΔ
ਖ਼PythonͰͷServing Πϯϑϥతʹਏ͍ࣄ͕ଟ͍…
ϝϞϦΛݡ͘͏ • fork͢ΔલʹmodelΛϩʔυ͠Copy on Write Λޮ͔͢ • k8sͷone process per
containerηΦϦ͋ ͑ͯഁ͍ͬͯΔ
Copy On Writeͷ෮श ϝϞϦ ϓϩηε ࢠϓϩηε 2.fork 1BHF" 1.allocation ಉ͡ྖҬΛࢀর
ϓϩηε͕ϝϞϦͷ༰Λ ॻ͖͑Δͱ… ϝϞϦ ϓϩηε ࢠϓϩηε 1BHF" 1BHF# OS͕ผͷྖҬΛAllocationͯ͠ݩσʔλΛίϐʔ͢Δ ผͷྖҬΛࢀর
Current Issues • ਓؒͷߦಈΛ૬खʹ͍ͯ͠Δҝɺσʔλͷ ͕มΘΓ͔ͬͨ͢Γɺ༧֎ͷ͕ൃ ੜͨ͠Γͯ͠ɺରԠ͠ଓ͚Δඞཁ͕͋Δ ˠ ML Model࡞ऀʹෛ୲ֻ͕͔Γଓ͚Δ ˠ
SREͱͯࣗ͠ಈԽΛؚΜͩΈͰղܾ ͍ͨ͠
In Progress • ࣾͷσʔλ͔ΒEmbedding͢Δ࣮Λίϯ ϙʔωϯτԽ • ಛఆͷΛղܾ͢ΔϞσϧߏஙΛ͋Δఔ ࣗಈԽ ˠࣾͷղܾʹಛԽͨ͠ઐ༻ͷAutoMLత ͳԿ͔
AutoFlow(Ծ) 'FBUVSF&YUSBDUJPO $PNQPOFOUT $MBTTJpDBUJPO $PNQPOFOUT $PODBUFOBUJPO $PNQPOFOUT .PEFM #VJMEFS $PNQPOFOUT
3FHJTUSZ Ϋϥελ্ͰϞσϧͷࣗಈߏஙͱϋΠύʔύϥ ϝʔλͷࣗಈௐΛߦ͏
·ͱΊ • MLʹগ͠௨ৗͱҧ͏Πϯϑϥ͕ඞཁʹͳΔ ˠ·ͩϕετɾϓϥΫςΟε͔Βͳ͍ • ͦͦMLͳػೳΛຊ֨ӡ༻͠Α͏ͱ͢Δ ͱɺେ෯ͳࣗಈԽɾΈԽΛਐΊͳ͍ͱ্ ख͘ߦ͔ͳ͍
͝ਗ਼ௌ͋Γ͕ͱ͏͍͟͝·ͨ͠!!
We are Hiring!!
SRE ML Reliability • SysML? MLOps? ৽͍͠Job description • SREεΩϧ+MLͷجૅࣝ
• MLΠϯϑϥͷࣗಈԽɾΈԽΛਪ͠ਐΊͯ ͘ΕΔਓࡐ • ͪΖΜଞͷ৬छઈࢍืूத!!
ৄࡉͪ͜Β https://careers.mercari.com/