IPSJ SIG Technical Report Vol.2019-IOT-44 No /3/8 CRIU HTTP 1,a) 2 PC SNS Web FastContainer HTTP HTTP Web HTTP Web Web Low-cost and High Perfor

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1 CRIU HTTP 1,a) 2 PC SNS Web FastContainer HTTP HTTP Web HTTP Web Web Low-cost and High Performance Scheduling Method for Reactive Relocation of Containers Each HTTP Request Using CRIU Ryosuke Matsumoto 1,a) Uchio Kondo 2 1. Twitter Facebook 1 SAKURA Research Center, SAKURA Internet Inc., Akasaka, Chuo-ku, Fukuoka Japan 2 GMO GMO Pepabo, Inc., Tenjin, Chuo ku, Fukuoka Japan a) r-matsumoto@sakura.ad.jp Web Web Web Web [8] Web Web Web 1

2 [5] [1] Web [12] *1 FastContainer [13] HTTP Web [10] CRIU[2] Linux Checkpoint/Restore Web HTTP *1 FastContainer FastContainer Mortal HTTP FastContainer 1 ICMP TCP HTTP Web Web Web 2 Web HTTP 5 2. Web Web Web HTTP 2.1 Web Web HTTP Web [8] (FQDN) Web Web [8] Web [11] Apache httpd 2

3 Web [14] Web Web Web Web Web *2 Web Web [12] 2.2 [7] Web Web *2 [15] AWS [1] OSS Web Web 2.3 FastContainer Web Web FastContainer [13] FastContainer Web WordPress CMS Web HTTP FastContainer Linux [4] Linux OS FastContainer FastCGI[3] HTTP Web 3

4 FastContainer cgroup cgroup 3. WordPress Web ( 1 ) WordPress Web ( 2 ) ( 3 ) HTTP 3 Fast- Container HTTP HTTP FastContainer ICMP SO LINGER TCP 1 Fig. 1 The Flow of Contaienr Scheduling. mruby-fast-remote-check[9] HTTP (Checkpoint) (Restore) ICMP Host OS 1 Client Container HTTP Client Web Proxy Web Proxy Container CMDB API Container IP / Web Proxy Host OS Container Host OS ICMP Web Proxy ICMP Host OS Container Dispatcher Container Dispatcher HTTP CMDB API Host OS Client CMDB API Web Proxy ICMP ICMP Web Proxy 4

5 Web Proxy CMDB API Host OS Host OS ICMP Host OS Container Dispatcher Container Dispatcher HTTP (1) FastContainer Host OS WordPress Web Host OS (2) HTTP (3) (1) Host OS ICMP TCP ICMP TCP Web Proxy Host OS ICMP TCP FastContainer [13] 3.2 CRIU Checkpoint Web CIRU GUI Client Compute UserDB UserProxy CoreAPI CMDB DataPool Table 1 1 Experimental Environment. Intel Xeon E GHz 1core 2GBytes Intel Xeon E GHz 8core 51GBytes DB Intel Xeon E GHz 8core 51GBytes CMDB Intel Xeon E GHz 1core 2GBytes Intel Xeon E GHz 1core 2GBytes Intel Xeon E GHz 1core 16GBytes Storage FlashPool NetApp FAS8200A 8.73 TB [16] Web Checkpoint/Restore Haconiwa[6] Haconiwa Haconiwa Haconiwa FastContainer Restore 4. 2 FastContainer 1 NIC OS NIC 1Gbps OS Ubuntu generic 5

6 情報処理学会研究報告 図 2 FastContainer のシステム構成例 図 4 Ruby on Rails のベンチマーク Fig. 2 Example of FastContainer System. Fig. 4 Benchmark of Ruby on Rails. 図 5 Django のベンチマーク 図 3 WordPress のベンチマーク Fig. 5 Benchmark of Django. Fig. 3 Benchmark of WordPress. を利用したものを採用した*3 Ruby on Rails は gem を を利用した 本実験では Comupte ノードを 2 台利用し 事前コンパイルしておくことにより起動を高速化させる て ノードの障害をエミュレートした コンテナのデータ bootsnap という機能があるため CRIU を使わない場合 は DataPool 上に保存し Compute から DataPool に対し は bootsnap を使った場合と使わない場合も計測した ま て NFSv3 でマウントした た CRIU によるイメージ化時の Rails のプロセス数は 2 本実験では Checkpoint/Restore によるサーバプロセス の起動の高速化手法を組み込んだ場合と組み込まない場合 スレッド数は 14 単一のプロセスのメモリサイズ (RSS) は 89MBytes であった とで Wordpress Ruby on Rails Django それぞれのレ Django は Python Django gunicorn スポンスタイムを計測した Wordpress は Web サーバに を利用し Rails と同様に 現実的な規模で DB を利用し は Apache PHP Wordpress を利用し た Web アプリケーションを採用した*4 また CRIU によ た PHP は Opcache 機能を有効にした また CRIU に るイメージ化時の Django のプロセス数は 2 スレッド数 よるイメージ化時の Apache のプロセス数は 3 スレッド は 2 単一のプロセスのメモリサイズ (RSS) は 33MBytes 数 3 単一のプロセスのメモリサイズ (RSS) は 35MBytes であった であった Ruby on Rails は Ruby Rails Puma を利用し 起動するアプリケーションは現実的な規模 個 人/グループ内での利用のアプリケーション程度 で DB 2019 Information Processing Society of Japan 全ての Web アプリケーションは Haconiwa で作 成したコンテナ上で起動した データベースは UserDB *3 *

7 MySQL MB 1 ab TCP mruby-fast-remote-check SO LINGER TCP 100ms Compute ipatables UserProxy drop Compute Haconiwa Checkpoint/Restore *5 Web Web CRIU 3 WordPress WordPress 70ms ms TCP 100ms Apache 2937ms WordPress 70ms 2867ms CRIU Wordpress 55 WordPress CRIU 70ms ms TCP 100ms Apache 2063ms WordPress 70ms 1993ms CRIU 874ms 874ms *5 4 Ruby on Rails Ruby on Rails 20ms CRIU bootsnap ms TCP 100ms Rails 8475ms Rails 70ms 8455ms CRIU ms TCP 100ms Rails 1444ms 20ms 1424ms CRIU 7011ms bootsnap 2734ms 5 Django Django 15ms ms Wordpress Rails Web 5915ms CRIU 2249ms CRIU 3781ms UserProxy Compute Compute UserProxy Compute UserProxy OS 2 HTTP Ruby on Rails Django 7

8 Web 5. HTTP HTTP Web OS 1.5s 2s HTTP OS HTTP Infrastructure as a Service and Web Hosting Cloud Providers,10th IEEE/ACM International Conference on Grid Computing, pp , October [9] Ryosuke Matsumoto, mruby-fast-remote-check, [10],,,,,,,, IOT, Vol.2018-IOT-40(2), pp.1-8, [11], Web, ( ), [12],,, Web,, Vol.54, No.3, pp , [13],,,,, FastContainer:, , [14],,, Web,, Vol.59, No.3, pp , [15],,,,, IOT,2017-IOT-38, Vol.13, pp.1-8, [16],, GUI,, 72, pp95-96, [1] Amazon Web Services: Lambda, com/lambda/. [2] CRIU A project to implement checkpoint/restore functionality for Linux, [3] Brown Mark R, FastCGI: A high-performance gateway interface, Fifth International World Wide Web Conference. Vol [4] Felter W, Ferreira A, Rajamony R, Rubio J, An Updated Performance Comparison of Virtual Machines and Linux Containers, IEEE International Symposium Performance Analysis of Systems and Software (ISPASS), pp , March [5] Ferdman M, Adileh A, Kocberber O, Volos S, Alisafaee M, Jevdjic D, Falsafi B, Clearing the clouds: a study of emerging scale-out workloads on modern hardware, ACM SIGPLAN Notices, Vol. 47, No. 4, pp , March [6] Haconiwa - the mruby on container, mruby.org/. [7] P Mell, T Grance, The NIST Definition of Cloud Computing, US Nat l Inst. of Science and Technology, 2011, nistpubs/ /sp pdf. [8] Prodan R, Ostermann S, A Survey and Taxonomy of 8

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