Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
機械学習でサーバの負荷状態を把握したい
Search
Sponsored
·
Ship Features Fearlessly
Turn features on and off without deploys. Used by thousands of Ruby developers.
→
tsurubee
March 22, 2019
Technology
2.2k
7
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
機械学習でサーバの負荷状態を把握したい
tsurubee
March 22, 2019
More Decks by tsurubee
See All by tsurubee
大規模言語モデルにおけるData-Centric AIと合成データの活用 / Data-Centric AI and Synthetic Data in Large Language Models
tsurubee
1
630
言語モデルによるAI創薬の進展 / Advancements in AI-Driven Drug Discovery Using Language Models
tsurubee
2
650
AIトップカンファレンスからみるData-Centric AIの研究動向 / Research Trends in Data-Centric AI: Insights from Top AI Conferences
tsurubee
3
3.5k
DeepCrysTet: A Deep Learning Approach Using Tetrahedral Mesh for Predicting Properties of Crystalline Materials
tsurubee
0
1.4k
3次元メッシュで表現した結晶構造を用いた材料物性の予測に向けた深層学習モデルの設計 / Design of Deep Learning Model for Predicting Material Properties Using Crystal Structure Represented by Three-Dimensional Mesh
tsurubee
1
2.6k
分散システムの性能異常に対する機械学習の解釈性に基づく原因診断手法 / A Method for Diagnosing the Causes of Performance Issues in Distributed Systems Based on the Interpretability of Machine Learning
tsurubee
0
1.8k
機械学習の解釈性に関する研究動向とシステム運用への応用 / A Survey on Interpretable Machine Learning and Its Application for System Operation
tsurubee
0
400
機械学習モデルの局所的な解釈に着目したシステムにおける異常の原因診断手法の構想
tsurubee
0
8.2k
アニーリングマシンを活用したエッジAIにおける 生成モデルの学習効率化のためのアーキテクチャ
tsurubee
0
1.7k
Other Decks in Technology
See All in Technology
DEFCON_CHV_CTF_Write-up.pdf
bata_24
0
140
Screen Lens - 今見てる画面を翻訳する
komagata
0
250
Claude in Chrome 入門 / Introduction to Claude in Chrome
cielo1985
0
270
#jawssonic2026 あの時代が悪かった ~動かなかったSageMakerと共に迎えたイベント当日~
ktkn1129
0
150
ペアプロの価値はコードを書くことだけじゃない
codmoninc
PRO
0
190
コスト最適化の「めんどくさい」を AWS FinOps Agent でチョット楽にする
classmethod_kaz
0
320
Redmine 7.0で私が開発した新機能の狙いと背景
vividtone
1
160
株式会社シーエーシー エンジニア向け会社紹介資料
cac
0
57k
深夜のクラウド懺悔室 1:29:300 or 1:0:0
kazzpapa3
1
230
Sigmaユーザーのための有用リソース一挙公開 & Sigmaで使えるMCP #sigma_ucj /useful-resources-for-sigma-computing-users-and-mcps-with-sigma
shinyaa31
0
190
Tab5をRubyで動くパソコンにする
kishima
2
340
Code4Lib JAPANカンファレンス2026 開会挨拶 / Code4Lib JAPAN Conference 2026: Opening Remarks
ykiyota
0
340
Featured
See All Featured
Building an army of robots
kneath
306
46k
Producing Creativity
orderedlist
PRO
348
41k
Accessibility Awareness
sabderemane
1
210
How to Align SEO within the Product Triangle To Get Buy-In & Support - #RIMC
aleyda
2
1.8k
Introduction to Domain-Driven Design and Collaborative software design
baasie
1
980
Navigating Algorithm Shifts & AI Overviews - #SMXNext
aleyda
1
1.6k
Into the Great Unknown - MozCon
thekraken
41
2.7k
Measuring & Analyzing Core Web Vitals
bluesmoon
9
990
Large-scale JavaScript Application Architecture
addyosmani
515
110k
Leveraging Curiosity to Care for An Aging Population
cassininazir
1
490
The AI Search Optimization Roadmap by Aleyda Solis
aleyda
1
6.2k
Sam Torres - BigQuery for SEOs
techseoconnect
PRO
0
540
Transcript
!UTVSVCFF(.01FQBCP *OD )PTUJOH$BTVBM5BMLT ػցֶशͰαʔόͷ ෛՙঢ়ଶΛѲ͍ͨ͠
ࣗݾհ (.0ϖύϘגࣜձࣾ ϗεςΟϯάࣄۀ෦ ΠϯϑϥνʔϜ !UTVSVCFF
None
ࠓ͢͜ͱ wʮΠϯϑϥºσʔλαΠΤϯεʯʹ͍ͭͯ͜Μͳ͜ͱ Ͱ͖Δͱ໘നͦ͏ͩͳʔͱࢲ͕ߟ͍͑ͯΔ͜ͱ wࠓճαʔόࢹʹযΛͯͯ͠·͢
wΠϯϑϥͷݱʹʑେྔͷσʔλ͕ྲྀΕ͍ͯΔ wσʔλΛߴղ૾ͰऔಘɾੵͰ͖Δڥ͕͖͍ͬͯͯΔ ʢ1SPNFUIFVTɺ,BGLBͳͲʣ wσʔλੵ͢Δ͚ͩͰͳ͘׆༻͍ͨ͠ wੵͨ͠େྔͷσʔλʹػցֶशΛద༻Ͱ͖Εɺ৽ͨͳ ࣝൃݟʹܨ͕ΓՁΛͰ͖ΔͷͰͳ͍͔ എܠɿҰൠ
wϗεςΟϯάαʔόҟৗ͕ൃੜ͍͢͠ˍ੍ޚͮ͠Β͍ wߴूੵͷڞ༻αʔό wαʔό্Ͱಈ࡞͢ΔίϯςϯπΛཧͰ͖ͳ͍ wϢʔβαʔόΛબͳ͍ͨΊɺՄೳͳݶΓฏʹշదͳ αʔόڥΛఏڙ͍ͨ͠ എܠɿϨϯλϧαʔόʢ-PMJQPQ)FUFNMʣ
wϗεςΟϯάαʔόҟৗ͕ൃੜ͍͢͠ˍ੍ޚͮ͠Β͍ wߴूੵͷڞ༻αʔό wαʔό্Ͱಈ࡞͢ΔίϯςϯπΛཧͰ͖ͳ͍ wϢʔβαʔόΛબͳ͍ͨΊɺՄೳͳݶΓฏʹշదͳ αʔόڥΛఏڙ͍ͨ͠ എܠɿϨϯλϧαʔόʢ-PMJQPQ)FUFNMʣ αʔόͷঢ়ଶΛਫ਼៛ʹѲ੍ͯ͠ޚ͍ͨ͠
wϗεςΟϯάαʔόҟৗ͕ൃੜ͍͢͠ˍ੍ޚͮ͠Β͍ wߴूੵͷڞ༻αʔό wαʔό্Ͱಈ࡞͢ΔίϯςϯπΛཧͰ͖ͳ͍ wϢʔβαʔόΛબͳ͍ͨΊɺՄೳͳݶΓฏʹշదͳ αʔόڥΛఏڙ͍ͨ͠ എܠɿϨϯλϧαʔόʢ-PMJQPQ)FUFNMʣ αʔόͷঢ়ଶΛਫ਼៛ʹѲ੍ͯ͠ޚ͍ͨ͠ ػցֶशʹΑΔ Ξϓϩʔν͕༗ޮ
wαʔόͷϦιʔε༻ঢ়گϩάͳͲͷࢹରͷϝτϦ Ϋε͝ͱʹᮢΛઃఆ͠ɺͦͷᮢΛ্ճΔ߹ʹΞϥʔτ Λൃใ͢Δʮᮢϕʔεͷࢹʯ͕Ұൠత αʔόࢹͷݱঢ় $16༻ ࣌ؒ ᮢ ΞϥʔτΛൃใ
ݱঢ়ΛѲ্ͨ͠Ͱ ඞͣߟ͑ͳ͚ΕͳΒͳ͍ ͜ͱ͕͋Δ
ຊʹػցֶश͕ඞཁͳͷ͔ ʮ.BDIJOF-FBSOJOH5IF)JHI*OUFSFTU$SFEJU$BSEPG 5FDIOJDBM%FCUʯ %4DVMMFZFUBM (PPHMF wػցֶशΛγεςϜʹΈࠐΉͷେ͖ͳٕज़తෛ࠴Λ ๊͑ࠐΉϦεΫ͕͋Δ͜ͱΛೝࣝ͢Δ wจதͰ༷ʑͳϦεΫཁҼʹ͍ͭͯઆ໌͞Ε͍ͯΔ
ຊʹػցֶश͕ඞཁͳͷ͔ ʮ.BDIJOF-FBSOJOH5IF)JHI*OUFSFTU$SFEJU$BSEPG 5FDIOJDBM%FCUʯ %4DVMMFZFUBM (PPHMF wػցֶशΛγεςϜʹΈࠐΉͷେ͖ͳٕज़తෛ࠴Λ ๊͑ࠐΉϦεΫ͕͋Δ͜ͱΛೝࣝ͢Δ wจதͰ༷ʑͳϦεΫཁҼʹ͍ͭͯઆ໌͞Ε͍ͯΔ ػցֶशΛʮ͏ʯ͜ͱ͕తʹͳͬͯͳΒͳ͍
Θͳͯ͘ࡁΉͳΒΘͳ͍͕࠷ྑͷબ
ᮢϕʔεͷࢹͷݶք ࢹͷਫ਼Λ্͛ΔͨΊʹ໌ࣔతʹࣄલࣝΛೖΕͯ ϧʔϧΛ૿͍͔ͯ͘͠͠ͳ͍ ྫ͑ɺ ̍ฏͷ"͔࣌Β#࣌ͷؒͰɺ͔ͭαʔόΛϦϦʔεͯ͠ ͔Β$ϲ݄ະຬͷ$16༻͕%Λ͑ͨͱ͖ҟৗ ̎$16༻͕&ҎͰ͋Δͱ͖ʹϝϞϦ༻͕' Ҏ্ʹͳͬͨͱ͖ҟৗ
ᮢϕʔεͷࢹͷݶք ࢹͷਫ਼Λ্͛ΔͨΊʹ໌ࣔతʹࣄલࣝΛೖΕͯ ϧʔϧΛ૿͍͔ͯ͘͠͠ͳ͍ ྫ͑ɺ ̍ฏͷ"͔࣌Β#࣌ͷؒͰɺ͔ͭαʔόΛϦϦʔεͯ͠ ͔Β$ϲ݄ະຬͷ$16༻͕%Λ͑ͨͱ͖ҟৗ ̎$16༻͕&ҎͰ͋Δͱ͖ʹϝϞϦ༻͕' Ҏ্ʹͳͬͨͱ͖ҟৗ ਓ͕ؒ໌ࣔతʹࢦఆɾཧͰ͖Δϧʔϧͷʹݶք͕͋Δ JGจࠈʹ͍͍ؕͬͯ͘ɾɾ
ᮢϕʔεͷࢹͷݶք ࢹͷਫ਼Λ্͛ΔͨΊʹ໌ࣔతʹࣄલࣝΛೖΕͯ ϧʔϧΛ૿͍͔ͯ͘͠͠ͳ͍ ྫ͑ɺ ̍ฏͷ"͔࣌Β#࣌ͷؒͰɺ͔ͭαʔόΛϦϦʔεͯ͠ ͔Β$ϲ݄ະຬͷ$16༻͕%Λ͑ͨͱ͖ҟৗ ̎$16༻͕&ҎͰ͋Δͱ͖ʹϝϞϦ༻͕' Ҏ্ʹͳͬͨͱ͖ҟৗ ਓ͕ؒ໌ࣔతʹࢦఆɾཧͰ͖Δϧʔϧͷʹݶք͕͋Δ JGจࠈʹ͍͍ؕͬͯ͘ɾɾ
࣌ܥྻੑ
ᮢϕʔεͷࢹͷݶք ࢹͷਫ਼Λ্͛ΔͨΊʹ໌ࣔతʹࣄલࣝΛೖΕͯ ϧʔϧΛ૿͍͔ͯ͘͠͠ͳ͍ ྫ͑ɺ ̍ฏͷ"͔࣌Β#࣌ͷؒͰɺ͔ͭαʔόΛϦϦʔεͯ͠ ͔Β$ϲ݄ະຬͷ$16༻͕%Λ͑ͨͱ͖ҟৗ ̎$16༻͕&ҎͰ͋Δͱ͖ʹϝϞϦ༻͕' Ҏ্ʹͳͬͨͱ͖ҟৗ ਓ͕ؒ໌ࣔతʹࢦఆɾཧͰ͖Δϧʔϧͷʹݶք͕͋Δ JGจࠈʹ͍͍ؕͬͯ͘ɾɾ
࣌ܥྻੑ ଟ࣍ݩੑʢ૬ؔੑʣ
݁ہͲ͏͍͏ͱ͖ʹ ػցֶश͕͑Δͷʁ
wσʔλͷ࣌ܥྻੑΛߟྀ͍ͨ͠߹ w͜ͷ࣌ظͷ͜ͷ࣌ؒଳʹͦͷҟৗ͡Όͳ͍ʁ Έ͍ͨͳύλʔϯ wσʔλಉ࢜ͷ૬ؔଟ࣍ݩੑΛߟྀ͍ͨ͠߹ wͦͷͷ߹ͤҟৗ͡Όͳ͍ʁΈ͍ͨͳύλʔϯ ػցֶश͕༗ޮͳέʔε
wσʔλͷ࣌ܥྻੑΛߟྀ͍ͨ͠߹ w͜ͷ࣌ظͷ͜ͷ࣌ؒଳʹͦͷҟৗ͡Όͳ͍ʁ Έ͍ͨͳύλʔϯ wσʔλಉ࢜ͷ૬ؔଟ࣍ݩੑΛߟྀ͍ͨ͠߹ wͦͷͷ߹ͤҟৗ͡Όͳ͍ʁΈ͍ͨͳύλʔϯ ػցֶश͕༗ޮͳέʔε ͞Βʹͦͷ྆ํͷଟ࣍ݩ࣌ܥྻσʔλ͔Βͷࣝൃݟɺ ϧʔϧϕʔεͰ͘͠ɺػցֶशͷಘҙ
͡Ό͋Ͳ͏ͬͯػցֶशΛ ద༻͍ͯ͘͠ͷ͔ʁ
αʔόΛଟ࣍ݩ࣌ܥྻσʔλͱͯ͠ଊ͑ɺ ͦͷಛΛநग़͢ΔʢಛϕΫτϧԽʣ ಘΒΕͨಛ͔Βঢ়ଶΛਫ਼៛ʹѲ͢Δ ʢෛՙঢ়گͷѲɺҟৗ༧ଌͳͲʣ
·ͣಛϕΫτϧԽ
ಛϕΫτϧԽ ʮใਪનγεςϜೖɿߨٛεϥΠυʯΑΓҾ༻ IUUQTXXXTMJEFTIBSFOFU,FOUB0LVTT
ಛϕΫτϧԽ ʮใਪનγεςϜೖɿߨٛεϥΠυʯΑΓҾ༻ IUUQTXXXTMJEFTIBSFOFU,FOUB0LVTT αʔό ❓
αʔόͷಛϕΫτϧԽ αʔόͷঢ়ଶΛΑ͘දݱͨ͠ಛϕΫτϧͷઃܭ͕ॏཁ $16༻ ϝϞϦ༻ -" ɹɹɹ
ಛϕΫτϧ ن֨Խ ಛҟղ Χʔωϧؔ FUD ಛϕΫτϧͷઃܭࣗ༝͕ߴ͍ αʔό ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾ ɾɾɾ ࣌ؒ ଟ࣍ݩ࣌ܥྻσʔλ ن֨Խ ࣌ؒ
࠷ߴͷಛϕΫτϧ ͕ಘΒΕͨΒʜ
ಛϕΫτϧΛͬͨαʔόࢹ αʔόͷঢ়ଶΛදݱͨ͠ ಛϕΫτϧ ΞϧΰϦζϜͷબࣗ༝͕ߴ͍ ࣌ؒ 0OF$MBTT 47. ࠞ߹ Ϟσϧ ෦ۭؒ๏
σΟʔϓ ϥʔχϯά
IUUQTTQFBLFSEFDLDPNTVHJZBNBNBDLFSFMNFFUVQOVNCFS ࣄྫɿ.BDLFSFMʢגࣜձࣾͯͳʣ
͍ͯ͠ΔΞϧΰϦζϜ
࣌ܥྻΫϥελϦϯά IUUQTCMPHUTVSVCFFUFDIFOUSZ IUUQTCMPHUTVSVCFFUFDIFOUSZ ڭࢣͳֶ͠शͰ͋ΔΫϥελϦϯάΛ࣌ܥྻσʔλʹదԠ ͨ͠ͷ
ͳͥΫϥελϦϯάʁ ϗεςΟϯάαʔόͷಛ wಉ͡ϩʔϧʢׂʣͰΘΕ͍ͯΔαʔόͷ͕ଟ͍ ʢ-PMJQPQͩͱඦεέʔϧʣ wಉҰϩʔϧͰ͋Δ͕ɺαʔόຖʹಛ͕େ͖͘ҟͳΔ w࣌ؒଳʹΑͬͯෛՙঢ়ଶ͕େ͖͘ҟͳΔ ֎ΕݕมԽݕͳͲͷϝτϦΫεͷઈରΛ༻͍ ͨҟৗݕΑΓɺ૬ରతʹݟͯଞͱৼΔ͍͕ҟͳΔͷ ݕग़͢Δํ͕૬ੑ͕ྑͦ͞͏
࣌ܥྻΫϥελϦϯάͷద༻Πϝʔδ ಛϕΫτϧಉ࢜ͷྨࣅΛࢉग़͠ɺଞͱৼΔ͍͕ ҟͳΔαʔόΛ͋ͿΓग़͢ αʔόΛ্ۭؒͷͱͯ͠දݱͯ͠ ಉ࢜ͷڑʢྨࣅʣΛࢉग़ ूஂ͔ΒΕ͍ͯΔ ͷΛҟৗͱ͢Δ ࣌ؒ ͭͷʹͷαʔόͷ ଟ࣍ݩ࣌ܥྻσʔλͷ
ใ͕ೖ͍ͬͯΔΠϝʔδ
UTDMVTUFS࣌ܥྻΫϥελϦϯάύοέʔδ ಈత࣌ؒ৳ॖ๏ʢ%58ʣɾLNFEPJET๏Λ࣮
UTDMVTUFS࣌ܥྻΫϥελϦϯάϥΠϒϥϦ ࣍ݩআྨࣅࢉग़ͷख๏ͳͲɺಠཱͨ͠ෳͷॲཧ ͷΈ߹ΘͤΛࣗ༝ʹม͑ΒΕΔ IUUQTVNFYQFSUVNFEVNZpMFQVCMJDBUJPO@QEG
·ͱΊ wαʔό্Ͱಈ࡞͢Δίϯςϯπ͕ཧͰ͖ͣɺҟৗ੍͕ޚ͠ ͮΒ͍ϗεςΟϯάڥʹ͓͍ͯػցֶशΛ༻͍ͨαʔόࢹ ༗ޮͳͷͰͳ͍͔ wαʔόΛ࣌ܥྻଟ࣍ݩσʔλͱͯ͠ଊ͑ɺαʔόͷঢ়ଶΛΑ ͘දݱͨ͠ಛϕΫτϧΛઃܭ͢Δ͜ͱ͕ॏཁ wಛϕΫτϧΛͲ͏͏͔ʹଟ͘ͷબ͕͋ΓɺϗεςΟ ϯάαʔόʹ͓͍ͯ࣌ܥྻΫϥελϦϯά͕༗ޮͳͷͰͳ ͍͔ͱߟ͍͑ͯΔ w͍·ໝ͍ͯ͠Δ͜ͱΛ࣮ફ͍͖͍ͯͨ͠
͝ਗ਼ௌ͋Γ͕ͱ͏ ͍͟͝·ͨ͠ʂʂ