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分散アプリケーションの高信頼化のための
運用技術に関する研究 / A Study on Operation Technology for High Reliability of Distributed Applications

分散アプリケーションの高信頼化のための
運用技術に関する研究 / A Study on Operation Technology for High Reliability of Distributed Applications

京都大学大学院 情報学研究科 知能情報学専攻 
中間発表(15min)。

Yuuki Tsubouchi (yuuk1)

August 05, 2021
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  1. ෼ࢄΞϓϦέʔγϣϯͷߴ৴པԽͷͨΊͷ

    ӡ༻ٕज़ʹؔ͢Δݚڀ
    ɾΫϥ΢υΛ࢖༻ͨ͠ΞϓϦέʔγϣϯͷ৴པੑΛ޲্ͤ͞Δ
    ΞʔΩςΫνϟΛݚڀ͍ͯ͠Δɻ


    ɾಛʹɺγεςϜͷӡ༻ঢ়گΛࣔ͢σʔλΛޮ཰తʹऩू͢Δख
    ๏ʹߩݙͨ͠ɻ


    ɾݱࡏ͸ɺऩू͞Εͨσʔλ͔ΒɺγεςϜʹൃੜ͢Δҟৗͷݪ
    ҼΛਝ଎ʹಛఆ͢ΔͨΊͷσʔλ෼ੳख๏Λݚڀ͍ͯ͠Δɻ
    ௶಺ ༎थ

    ژ౎େֶେֶӃ ৘ใֶݚڀՊ ஌ೳ৘ใֶઐ߈ ത࢜ޙظ՝ఔ 2೥

    தؒൃද 2021೥8݄5೔

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  2. 2
    1. Ϋϥ΢υ্ͷ෼ࢄΞϓϦέʔγϣϯ


    Ϋϥ΢υ্ͷ෼ࢄΞϓϦέʔγϣϯͷෳࡶԽ


    ৴པੑͷ՝୊: ӡ༻σʔλྔͷ૿Ճ

    2. ݚڀख๏


    ӡ༻σʔλͷऩूͷߴޮ཰Խ


    • [ݚڀ੒Ռ1] ଟ਺ͷ࣌ܥྻσʔλΛૠೖɾอଘ͢ΔͨΊͷσʔλϕʔε


    • [ݚڀ੒Ռ2] ωοτϫʔΫ௨৴ͷґଘؔ܎ͷ௿Φʔόϔουऩू


    ӡ༻σʔλͷղੳ


    • [ݚڀ੒Ռ3] ࣌ܥྻσʔλͷத͔ΒݪҼ਍அʹ༗༻ͳܥྻΛநग़


    3. ·ͱΊ/ݚڀ࣮੷
    ൃද಺༰ͷߏ੒

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  3. 3
    Ϋϥ΢υ্ͷ෼ࢄΞϓϦέʔγϣϯͷෳࡶԽ
    ɾ


    ɾ


    ɾ
    ΞΫηε૿Ճ
    εέʔϧΞ΢τʹΑΔ


    ϗετ਺ͷ૿Ճ
    ػೳͷ૿Ճ
    ΑΓେن໛ͳ

    ෼ࢄΞʔΩςΫνϟ
    ϛυϧ΢ΣΞͷ૿Ճ
    RDBαʔό
    Ωϟογϡ

    αʔό
    ݕࡧαʔό
    Webαʔό
    ωοτϫʔΫ

    αʔϏε
    TCP/UDP
    ɾ


    ɾ


    ɾ
    ϝσΟΞɺECαΠτɺSNSɺIoTͳͲΛߏ੒͢Δ෼ࢄΞϓϦέʔγϣϯ

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  4. 4
    ɾίϯϙʔωϯτ਺ͷ૿େʹΑΓɺӡ༻σʔλྔ͕૿Ճ


    ɾσʔλऩूͷͨΊͷܭࢉػͷෛՙ͕૿Ճ


    ɾγεςϜ؅ཧऀͷೝ஌ෛՙ͕૿Ճ
    ෳࡶԽͨ݁͠Ռͷ৴པੑͷ௿Լ
    ӡ༻σʔλͷ

    ऩू
    ɾෛՙঢ়گΛࣔ࣌͢ܥྻσʔλ


    ɾωοτϫʔΫ௨৴ͷґଘؔ܎


    ɾςΩετϩά
    ৴པੑͷ௿Լ΁
    ো֐෮چ࣌ؒͷ૿େ

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  5. 5
    ɾӡ༻σʔλͷऩूΛߴޮ཰Խ͢Δ ܭࢉػͷෛՙΛ௿ݮ


    [ݚڀ੒Ռ1] ࣌ܥྻσʔλΛߴޮ཰ʹૠೖɾอଘ͢Δσʔλϕʔε


    [ݚڀ੒Ռ2] ωοτϫʔΫ௨৴ͷґଘؔ܎ͷ௿Φʔόϔουऩू
    ໨త: ӡ༻σʔλͷऩूͱղੳͷߴ౓ԽʹΑΓ৴པੑΛ޲্
    ͍ͣΕ΋࣮؀ڥ΁ͷద༻༰қੑΛߟྀ͢Δ
    ɾӡ༻σʔλΛղੳ͠ɺো֐ରԠʹ༗༻ͳಎ࡯ΛಘΔ ೝ஌ෛՙΛ௿ݮ


    [ݚڀ੒Ռ3] ࣌ܥྻσʔλͷத͔ΒݪҼ਍அʹ༗༻ͳܥྻΛநग़
    ʢ↪࿦จࢽ౤ߘதʣ
    ʢ↪࿦จࢽ࠾࿥ࡁʣ
    ʢ↪ࠃࡍձٞ౤ߘ४උதʣ

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  6. 6
    ɾҰൠʹɺσΟεΫϕʔεDB͸ɺࡧҾߏ଄ʹฏߧ໦Λ࢖༻͢Δ


    ɾ՝୊ɿܥྻ਺(n)ͷ૿Ճʹରͯ͠ɺܭࢉྔ͕O(log n)Ͱ૿Ճ͢Δ


    ɾ؅ཧͷෛ୲Λܰݮ͢ΔͨΊʹɺطଘͷDB্ʹߏ੒͍ͨ͠
    [ݚڀ੒Ռ1] ࣌ܥྻσʔλͷऩूͷߴޮ཰Խ
    ௶಺༎थ΄͔, HeteroTSDB: ҟछ෼ࢄKVSؒͷࣗಈ֊૚ԽʹΑΔߴੑೳͳ࣌ܥྻσʔλϕʔε, ৘ใॲཧֶձ࿦จࢽ, Vol.62, No.3, pp.818-828, 2021೥3݄.
    ϝϞϦ

    ϕʔεDB
    σΟεΫ

    ϕʔεDB
    ϋογϡද O(k) ฏߧ໦ O(log n)
    σʔλ఺ૠೖ
    dݸͷσʔλ఺Λ஝ੵޙʹ

    ϑϥογϡॻ͖ࠐΈ
    ղܾɿϝϞϦϕʔεDBͱσΟεΫϕʔεDBͷ֊૚ԽΛఏҊ
    M (insertions/s) M / d (insertions/s)

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  7. 7
    [ݚڀ੒Ռ1] ܥྻ਺ͷ૿Ճʹର͢ΔૠೖεϧʔϓοτมԽ
    ɾσΟεΫϕʔεDBͷΈͱൺֱ͠ɺ
    ࠷େͰ3.96ഒͷεϧʔϓοτ


    ɾεϧʔϓοτͷ௿Լ཰΋վળͨ͠
    0
    20
    40
    60
    80
    100
    100 1K 10K 100k 1M
    0
    20
    40
    60
    Insertion throughput (kilo datapoints / sec)
    Throughput decrease rate (%)
    The number of series
    HeteroTSDB (Proposed)
    KairosDB
    HeteroTSDB (Proposed)
    KairosDB
    ϝϞϦDB → σΟεΫDBͷҠಈεϧʔ
    ϓοτͱϝϞϦDB΁ͷεϧʔϓοτͱ
    ಉఔ౓
    0
    20
    40
    60
    80
    100
    0 300 600 900 1200 1500 1800
    0
    500
    1000
    1500
    2000
    Insertion throughput (kilo datapoints / sec)
    Memory used size (MB)
    Elapsed time (sec)
    Flushed datapoints (/sec)
    Memory used size (MB)
    ௶಺༎थ΄͔, HeteroTSDB: ҟछ෼ࢄKVSؒͷࣗಈ֊૚ԽʹΑΔߴੑೳͳ࣌ܥྻσʔλϕʔε, ৘ใॲཧֶձ࿦จࢽ, Vol.62, No.3, pp.818-828, 2021೥3݄.

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  8. (౤ߘத) Y. Tsubouchi, et al., Low Overhead TCP/UDP Socket-based Tracing for Discovering Network Services Dependencies, Journal of Information Processing 2022.
    [ݚڀ੒Ռ2] ωοτϫʔΫ௨৴ͷґଘؔ܎औಘͷޮ཰Խ
    .


    .


    .
    Kernel
    User
    Service
    Socket
    Tracing

    Process
    … Event
    Event
    Event
    ετϦʔϛϯά๏(Weave Scope)
    ϑϩʔू໿๏ ([Datadog], [SAC 20])
    ϑϩʔूଋ๏ʢఏҊʣ
    .


    .


    .
    Kernel
    Service
    Socket
    Tracing

    Process
    .


    .


    .
    Event
    Flow
    Event
    Event
    Event


    .


    .


    . .


    .


    .
    User
    Service
    Socket
    Tracing

    Process
    .


    .


    .
    ✗ ΧʔωϧˠϢʔβۭؒؒ
    ͷΠϕϯτͷίϐʔίετ
    ✗ TCP઀ଓϨʔτ͕૿Ճ͢Δ
    ͱɺίϐʔίετ͕૿Ճ ෳ਺ͷϑϩʔΛूଋ
    ϑϩʔ= ྆୺ͷΞυϨεͱϙʔτͷ
    ૊ʢλϓϧʣ͕ಉҰͷ௨৴୯Ґ
    Event
    Event …

    Event
    Event
    .


    .


    .
    Event
    Event …
    Event
    Event
    .


    .


    .
    Ұൠతʹ௨৴͸OSΧʔωϧͷTCP/UDPΛ࢖༻͢Δ͜ͱ
    ʹண໨
    8

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  9. 9
    ɾఏҊख๏͸ɺCPUར༻཰͸2.2%ҎԼɻ


    ɾϑϩʔ਺ͷ૿େʹରͯ͠ɺϑϩʔूଋʹΑΓɺ

    CPUར༻཰Λ௿͘ҡ͍࣋ͯ͠Δ
    [ݚڀ੒Ռ2] ϑϩʔ਺ͷ૿େʹର͢ΔCPU࢖༻ྔͷมԽ
    ఏҊख๏
    (౤ߘத) Y. Tsubouchi, et al., Low Overhead TCP/UDP Socket-based Tracing for Discovering Network Services Dependencies, Journal of Information Processing 2022.
    0
    5
    10
    15
    20
    25
    5 10 15 20 25 30 35
    CPU usage / core (%)
    TCP round trips / sec (x103)
    Streaming(client)
    Streaming(server)
    In-Kernel-Aggr(client)
    In-Kernel-Aggr(server)
    In-Kernel-Bundling(client)
    In-Kernel-Bundling(server)

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  10. εςοϓ1: ظؒதͷมಈͷ౓߹͍͕খ͍͞ܥྻΛআڈ


    εςοϓ2: άϥϑͷܗঢ়͕ྨࣅ͢Δ΋ͷ͔Β୅දܥྻΛநग़
    10
    ɾ՝୊: ίϯϙʔωϯτ͝ͱʹɺಛ௃ྔͱͯ͠ܥྻͷछผʢCPU࢖༻ɺϝϞϦ࢖
    ༻ɺωοτϫʔΫଳҬɺ…ʣΛࢦఆ͢Δඞཁ͋Γ


    ɾղܾ: ؔ࿈͢ΔશܥྻΛೖྗͱͯ͠༩͑ɺݪҼ਍அʹ༗༻ͳܥྻΛߴ଎ʹநग़
    [ݚڀ੒Ռ3] ࣌ܥྻσʔλ͔ΒݪҼ਍அʹ༗༻ͳܥྻΛநग़
    ҟৗ

    ݕ஌
    YES
    ࣌ܥྻσʔλͷऩू
    ݪҼ਍அ

    ҼՌάϥϑΛ

    ߏங
    [AutoMAP, Microscope,…]
    ఏҊ
    ࣌ܥྻσʔλͷ

    ࣍ݩ࡟ݮ
    ௶಺༎थ΄͔, TSifter: ϚΠΫϩαʔϏεʹ͓͚Δੑೳҟৗͷਝ଎ͳ਍அʹ޲͍ͨ࣌ܥྻσʔλͷ࣍ݩ࡟ݮख๏, Πϯλʔωοτͱӡ༻ٕज़γϯϙδ΢Ϝ࿦จू, 2020೥.

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  11. 11
    [ݚڀ੒Ռ3] ܥྻ࡟ݮੑೳͱߴ଎ੑ
    ɾCPUίΞ਺4ɺܥྻ਺100k
    εςοϓ1

    ܥྻ୯Ґͷআڈ
    εςοϓ2


    ྨࣅܥྻͷू໿
    ߹ܭ

    ࣮ߦ࣌ؒ
    54.41 (sec) 8.68 (sec) 63.09 (sec)
    ߴ଎ੑ
    ܥྻ࡟ݮੑೳ
    ҟৗ஫ೖ ίϯϙʔωϯτ

    A
    ίϯϙʔωϯτ

    B
    CPUաෛՙ 1545/201/122

    92.1%
    1541/156/89

    94.2%
    ωοτϫʔΫ

    ஗Ԇ
    1596/248/128
    91.9%
    1543/262/128


    91.7%
    ɾܥྻ࡟ݮੑೳ͕ɺߴ͍ਫ਼౓ͷݪҼ
    ਍அͷͨΊʹे෼͔Ͳ͏͔͸ɺࠓ
    ޙݕূ༧ఆ
    ɾݱ৔ͷো֐ରԠʹద༻͢Δ্Ͱɺ
    े෼ͳੑೳΛಘΒΕͨ
    ௶಺༎थ΄͔, TSifter: ϚΠΫϩαʔϏεʹ͓͚Δੑೳҟৗͷਝ଎ͳ਍அʹ޲͍ͨ࣌ܥྻσʔλͷ࣍ݩ࡟ݮख๏, Πϯλʔωοτͱӡ༻ٕज़γϯϙδ΢Ϝ࿦จू, 2020೥.

    View full-size slide

  12. 12
    ɾΫϥ΢υ্ͷ෼ࢄΞϓϦέʔγϣϯͷ৴པੑΛ޲্ͤ͞ΔͨΊͷΞʔΩς
    ΫνϟΛݚڀ͍ͯ͠Δɻ


    ɾಛʹɺγεςϜͷӡ༻σʔλΛߴޮ཰ʹऩू͢Δख๏ʹߩݙͨ͠ɻ


    ɾ࣌ܥྻσʔλ


    ɾωοτϫʔΫ௨৴ͷґଘσʔλ


    ɾݱࡏ͸ɺऩू͞Εͨσʔλ͔ΒɺγεςϜʹൃੜ͢ΔҟৗͷݪҼΛಛఆ͢
    Δख๏Λݚڀ͓ͯ͠Γɺ੒Ռ͕Ͱͭͭ͋Δɻ


    ɾ͜ΕΒͷߩݙ͸ɺ৴པੑͷ޲্ʹد༩͢Δ΋ͷͰ͋Δɻ
    ·ͱΊ

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  13. 13
    ࣮຿্Ͱ͸ɺӡ༻σʔλͷղੳͷࡍʹɺݱ࣮తʹऩूՄೳͳӡ༻σʔλͷ
    छྨ΍ཻ౓Λ૝ఆ͢Δɻ
    ֶज़తߩݙ
    σʔλͷऩूͱղੳͷ2ஈ֊Λ၆ᛌ্ͨ͠Ͱɺ࣮؀ڥ΁ͷద༻ੑͷߴ͍
    ΞʔΩςΫνϟΛఏࣔ͢Δɻ
    ࣮຿্ͷ՝୊
    ֤։ൃɾӡ༻૊৫ͷݸผͷࣄ৘ʹґଘ͢Δ
    σʔλͷऩूͱղੳ͸ݸผʹٞ࿦͞Ε͍ͯΔ
    طଘ࿦จͷ՝୊

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  14. 14
    ɾ Y. Tsubouchi, M. Furukawa, R. Matsumoto, Low Overhead TCP/UDP Socket-based Tracing for
    Discovering Network Services Dependencies, Journal of Information Processing (JIP), 2022.
    ͜Ε·Ͱͷݚڀ੒Ռ: ओͳࠪಡ෇͖࿦จ
    δϟʔφϧ࿦จ
    ࠃࡍձٞ
    ɾ Y. Tsubouchi, M. Furukawa, R. Matsumoto, Transtracer: Socket-Based Tracing of Network Dependencies
    among Processes in Distributed Applications, The 1st IEEE International COMPSAC Workshop on
    Advanced IoT Computing (AIOT 2020), July 2020.
    ࠃ಺γϯϙδ΢Ϝ
    ɾ ௶಺༎थ, ࿬ࡔேਓ, ᖛా݈, দ໦խ޾, খྛོߒ, Ѩ෦ത, দຊ྄հ, HeteroTSDB: ҟछ෼ࢄKVSؒͷࣗಈ֊૚Խ
    ʹΑΔߴੑೳͳ࣌ܥྻσʔλϕʔε, ৘ใॲཧֶձ࿦จࢽ, Vol.62, No.3, pp.818-828, 2021೥3݄.
    ʢ౤ߘதʣ
    ɾ Y. Tsubouchi, A. Wakisaka, K. Hamada, M. Matsuki, H. Abe, R. Matsumoto, HeteroTSDB: An Extensible Time
    Series Database for Automatically Tiering on Heterogeneous Key-Value Stores, The 43rd Annual IEEE
    International Computers, Software & Applications Conference (COMPSAC), pp. 264-269, July 2019.
    ɾ ௶಺༎थ, ௽ాതจ, ݹ઒խେ, TSifter: ϚΠΫϩαʔϏεʹ͓͚Δੑೳҟৗͷਝ଎ͳ਍அʹ޲͍ͨ࣌ܥྻσʔλ
    ͷ࣍ݩ࡟ݮख๏, Πϯλʔωοτͱӡ༻ٕज़γϯϙδ΢Ϝ࿦จू, 2020, 9-16 (2020-11-26), 2020೥12݄.
    ɾ ௶಺༎थ, ҏ໺จ඙, ஔాਅੜ, ࢁ઒૱, ദ໦ַ඙, ഡݪ݉Ұ, ॏෳഉআετϨʔδͷͨΊͷSHA-1ܭ
    ࢉγεςϜͷSSE໋ྩʹΑΔߴεϧʔϓοτԽ, ిࢠ৘ใ௨৴ֶձ࿦จࢽ D, 96(10), pp.2101-2109 2013೥10݄.
    ʢຊൃදʹؚ·ͣʣ

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