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Velocity 2013 Conference

Sangcheol Hwang
Sangcheol Hwang

The document summarizes a conference called Velocity 2013 Conference. It provides details about: - The purpose of attending the conference was to learn about reference architectures for build/deployment systems, monitoring, and mobile deployment. - The conference covered topics like mobile performance, operations, and web performance. It included technical sessions on solving performance and operational issues in large-scale environments. - Some of the sessions discussed tools for packaging, log collection, monitoring metrics, testing methods, lessons learned from projects, and scaling load balancing infrastructure to over a billion users.

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Velocity 2013 Conference 螳 煙: 豌 : SK Planet > CTO > SQE 煙: 2013715 谿瑚 覈 觜 & 覦壱 ろ 朱一 覦 蟯 ろ 覈磯 朱一 ろ豌 覦蟲 覈覦 覦壱 朱一 覦 企 伎 碁 焔レ 豕 覲 給 Velocity 2013 貉朱一る? 蠍郁: 2013 618~20 レ: 壱企朱, 貂襴 譯殊: る襴 危: http://velocityconf.com/velocity2013/ 谿瑚 蠏覈: 1800覈 蟲: 襴, 語, 覿 貉朱一 'Building a Faster and Stronger Web'企朱 貂豺伎襦 企Π 覲 貉朱一る 蟆 3螳讌 譯殊襯 る螻 . 覈覦 焔: れ危磯,轟, 覦 , 覈覦 焔 豸′ 蟲, 伎: 覈磯, 讌, れ蟯襴, DevOps 焔: 豕 蟲,蠍一, 焔 螳 蟆渚 螻旧 蟆曙 覦 焔レ企 伎 覓語襯 企至 願屋螳 蠍一 伎 蟯 ろ, 蟲, 豌 螳覦 ろ 螳 焔 螳 觜讀れ 企至 螳 伎 Operations Level Up http://velocityconf.com/velocity2013/public/schedule/detail/28203 束 損 1 /123 Mwalls velocity levelup from Mandi Walls Topics Tools for building operating system packages for your own deployments Log collection and aggregation Metrics, monitoring, and statistics Working with software development tools, version control, code review Testing methods, configuration management tools Lessons and Learned Git
Ops Identity Crisis: ろ 蟯襴 貊襯 覈 讌一. Easy to do Right Good Comment, Prc Commit Hook 覯 れ煙 ろ碁ゼ . Bring the Noise: Making Effective Use of a Quarter Million Metrics http://velocityconf.com/velocity2013/public/schedule/detail/28177 覦襭: https://speakerdeck.com/astanway/bring-the-noise-continuously-deploying-under-a-hailstorm-of-metrics Topics Metric Overload: The situation which gave rise to the development of these tools and how we approached the problem Skyline: The architecture and algorithms we use for realtime anomaly detection on a massive scale Oculus: The architecture and algorithms we use to compute similarity and correlation across all of our metric data Lessons and Learned Etsy: http://www.etsy.com/ 1.5 billion pv, 950 thousands users Continuous Delivery 30 deploy a day? Is that safe? れ襯 蠍磯るΜ讌 襷螻 覓語襯 覩碁Μ 谿場 Can't fix what you don't measure 襴狩朱 襦蠏碁ゼ 覿伎 ()襯 谿城. Kale: Skyline + Oculus Skyline A real time anomaly detection system https://github.com/etsy/skyline Oculus: anomaly correlation component https://github.com/etsy/oculus Realtime 覩 Graphite, Ganglia, Redis Euclidian Distance Speeding Up Your Mobile HTML5 Experience http://velocityconf.com/velocity2013/public/schedule/detail/28314 覦襭: https://speakerdeck.com/firtman/speeding-up-your-mobile-html5-experience Topics CSS Sprites vs inline images Animate 3D transforms for hardware acceleration Application Cache Different viewport definitions JavaScript frameworks usage Web Storage vs. SQL Storage vs. IDB Large DOM vs iframes vs object pool SVG vs high resolution canvas Mouse vs. Touch/Pointer events Animation Timing API Images vs CSS3 effects and gradients Using HTML5 abilities to improve performance perception and responsiveness Managing PostgreSQL with Ansible in EC2 http://velocityconf.com/velocity2013/public/schedule/detail/28115 Topics Ansible: https://github.com/ansible/ansible Ansible is a radically simple configuration-management, deployment, task-execution, and multinode orchestration framework. Avoiding Performance Regression at Twitter http://velocityconf.com/velocity2013/public/schedule/detail/28455
束 損 1 /52 Velocity Conf 2013 Workshop: Avoiding Web Performance Regression from Marcel Duran Topics YSlow WebPageTest http://www.webpagetest.org/ https://github.com/WPO-Foundation/webpagetest Meet the Obama Campaign's $250 Million Fundraising Platform http://velocityconf.com/velocity2013/public/schedule/detail/28316 Video http://kylerush.net/blog/meet-the-obama-campaigns-250-million-fundraising-platform/ Lesson and Learned 焔レ vs 觜讀 Is The Web Getting Faster? http://velocityconf.com/velocity2013/public/schedule/detail/30013 Video Lesson and Learned 螻手碓 觜 蠍一 朱 觜殊螳 覦ろ襴渚 20覦 API Design Principles for Accelerated Development http://velocityconf.com/velocity2013/public/schedule/detail/31356 束 損 1 /27 API Design Principles for Accelerated Development from Jonathan LeBlanc Optimizing the Critical Rendering Path for Instant Mobile Websites
http://velocityconf.com/velocity2013/public/schedule/detail/29616 覦襭: https://docs.google.com/presentation/d/1IRHyU7_crIiCjl0Gvue0WY3eY_eYvFQvSfwQouW9368/present#slide=id.p19 Lesson and Learned ろ語 襷 覿 誤蠍 TCP 郁屋 螻 Critical Path襯 谿場 豕 http://modpagespeed.com/ http://ngxpagespeed.com/ngx_pagespeed_example/ Increasing Speed To Market In Mobile Development Through Continuous Integration http://velocityconf.com/velocity2013/public/schedule/detail/31073 Lesson and Learned 覈覦 覦壱 覦 ろ れ ル 覦壱 The Secret of Safe, Continuous Deployment: Perceptual Diffs http://velocityconf.com/velocity2013/public/schedule/detail/28452 覦襭: http://cdn.oreillystatic.com/en/assets/1/event/94/The%20Secret%20of%20Safe,%20Continuous%20Deployment_%20Perceptual%20Diffs%20Presentation%201.pdf Lesson and Learned How perceptual diffs make it safe for web-based software Why its not safe in general to deploy on commit The stumbling blocks weve hit and mistakes weve made Lesson and Learned Perceptual diffs are the best thing! 螻手碓 覯 ろ襴 穴骸 襦 覯 ろ襴 血 觜蟲 覦覯 觜螳朱 覲伎 觜蟲. 蟯 ろ: https://github.com/bslatkin/dpxdt The CSS and GPU Cheatsheet http://velocityconf.com/velocity2013/public/schedule/detail/31377 覦襭: http://cdn.oreillystatic.com/en/assets/1/event/94/The%20CSS%20and%20GPU%20Cheatsheet%20Presentation.pdf Lesson and Learned GPU + Layers = faster rendering Too many layers = seriously bad time Be aware of your CSS tags impact on CPU & GPU perf Use tooling to show off how many layers you have Building A Billion User Load Balancer http://velocityconf.com/velocity2013/public/schedule/detail/28410 Topics how facebook scales their load balancing infrastructure to support more than a billion users? Our Python decision engine is named Cartographer Lesson and Learned Context 殊殊殊 殊 狩 襭譴 11 3螳 狩 譟伎 磯 襭譴 狩 殊. Demo襯 語 る螻れ朱 願襯 り鍵 Scale Out LB 伎 TCP 語 伎 貎 襦襯 螻 覩瑚記覯 豌襴伎 焔レ 碁 Sonar襯 伎 襦 誤讌襯 蟆 Building A Performance Lab For Mobile Apps In A Day http://velocityconf.com/velocity2013/public/schedule/detail/31041 覦襭: http://www.slideshare.net/ashraymathur/velocity-building-a-performance-lab-for-mobile-apps-in-a-day-final Topics How to define and set baselines Performance metrics and instrumentations How to keep the performance optimized from code check-in to rollout
Internal Monitoring to identify problems and avoid regressions Real User Monitoring to gauge customer experience App Crashes How to detect and handle app crashes & memory leaks Tools Some very important tools that need to be in your toolbox Perceived Performance Importance of adding performance in app design Lesson and Learned Metrics: Page Load Times, Network Metrices, Nav Timing Metrics, Server/Client Metrics 3 Esstntial Steps Mobile Automation App Instrumentation Mobile Infrastructure CI Launch Simulator and run tests Selenium for native iOS apps: https://github.com/moredip/Frank Stress/longevity testing Instrumentaion: https://github.com/lognormal/boomerang/ Monitoring gc log, heap dumps(by MAT) DevOps: Its Not Just For WebOps And We Have The Metrics To Prove It http://velocityconf.com/velocity2013/public/schedule/detail/28446

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Velocity 2013 Conference

  • 1. Velocity 2013 Conference 螳 煙: 豌 : SK Planet > CTO > SQE 煙: 2013715 谿瑚 覈 觜 & 覦壱 ろ 朱一 覦 蟯 ろ 覈磯 朱一 ろ豌 覦蟲 覈覦 覦壱 朱一 覦 企 伎 碁 焔レ 豕 覲 給 Velocity 2013 貉朱一る? 蠍郁: 2013 618~20 レ: 壱企朱, 貂襴 譯殊: る襴 危: http://velocityconf.com/velocity2013/ 谿瑚 蠏覈: 1800覈 蟲: 襴, 語, 覿 貉朱一 'Building a Faster and Stronger Web'企朱 貂豺伎襦 企Π 覲 貉朱一る 蟆 3螳讌 譯殊襯 る螻 . 覈覦 焔: れ危磯,轟, 覦 , 覈覦 焔 豸′ 蟲, 伎: 覈磯, 讌, れ蟯襴, DevOps 焔: 豕 蟲,蠍一, 焔 螳 蟆渚 螻旧 蟆曙 覦 焔レ企 伎 覓語襯 企至 願屋螳 蠍一 伎 蟯 ろ, 蟲, 豌 螳覦 ろ 螳 焔 螳 觜讀れ 企至 螳 伎 Operations Level Up http://velocityconf.com/velocity2013/public/schedule/detail/28203 束 損 1 /123 Mwalls velocity levelup from Mandi Walls Topics Tools for building operating system packages for your own deployments Log collection and aggregation Metrics, monitoring, and statistics Working with software development tools, version control, code review Testing methods, configuration management tools Lessons and Learned Git
  • 2. Ops Identity Crisis: ろ 蟯襴 貊襯 覈 讌一. Easy to do Right Good Comment, Prc Commit Hook 覯 れ煙 ろ碁ゼ . Bring the Noise: Making Effective Use of a Quarter Million Metrics http://velocityconf.com/velocity2013/public/schedule/detail/28177 覦襭: https://speakerdeck.com/astanway/bring-the-noise-continuously-deploying-under-a-hailstorm-of-metrics Topics Metric Overload: The situation which gave rise to the development of these tools and how we approached the problem Skyline: The architecture and algorithms we use for realtime anomaly detection on a massive scale Oculus: The architecture and algorithms we use to compute similarity and correlation across all of our metric data Lessons and Learned Etsy: http://www.etsy.com/ 1.5 billion pv, 950 thousands users Continuous Delivery 30 deploy a day? Is that safe? れ襯 蠍磯るΜ讌 襷螻 覓語襯 覩碁Μ 谿場 Can't fix what you don't measure 襴狩朱 襦蠏碁ゼ 覿伎 ()襯 谿城. Kale: Skyline + Oculus Skyline A real time anomaly detection system https://github.com/etsy/skyline Oculus: anomaly correlation component https://github.com/etsy/oculus Realtime 覩 Graphite, Ganglia, Redis Euclidian Distance Speeding Up Your Mobile HTML5 Experience http://velocityconf.com/velocity2013/public/schedule/detail/28314 覦襭: https://speakerdeck.com/firtman/speeding-up-your-mobile-html5-experience Topics CSS Sprites vs inline images Animate 3D transforms for hardware acceleration Application Cache Different viewport definitions JavaScript frameworks usage Web Storage vs. SQL Storage vs. IDB Large DOM vs iframes vs object pool SVG vs high resolution canvas Mouse vs. Touch/Pointer events Animation Timing API Images vs CSS3 effects and gradients Using HTML5 abilities to improve performance perception and responsiveness Managing PostgreSQL with Ansible in EC2 http://velocityconf.com/velocity2013/public/schedule/detail/28115 Topics Ansible: https://github.com/ansible/ansible Ansible is a radically simple configuration-management, deployment, task-execution, and multinode orchestration framework. Avoiding Performance Regression at Twitter http://velocityconf.com/velocity2013/public/schedule/detail/28455
  • 3. 束 損 1 /52 Velocity Conf 2013 Workshop: Avoiding Web Performance Regression from Marcel Duran Topics YSlow WebPageTest http://www.webpagetest.org/ https://github.com/WPO-Foundation/webpagetest Meet the Obama Campaign's $250 Million Fundraising Platform http://velocityconf.com/velocity2013/public/schedule/detail/28316 Video http://kylerush.net/blog/meet-the-obama-campaigns-250-million-fundraising-platform/ Lesson and Learned 焔レ vs 觜讀 Is The Web Getting Faster? http://velocityconf.com/velocity2013/public/schedule/detail/30013 Video Lesson and Learned 螻手碓 觜 蠍一 朱 觜殊螳 覦ろ襴渚 20覦 API Design Principles for Accelerated Development http://velocityconf.com/velocity2013/public/schedule/detail/31356 束 損 1 /27 API Design Principles for Accelerated Development from Jonathan LeBlanc Optimizing the Critical Rendering Path for Instant Mobile Websites
  • 4. http://velocityconf.com/velocity2013/public/schedule/detail/29616 覦襭: https://docs.google.com/presentation/d/1IRHyU7_crIiCjl0Gvue0WY3eY_eYvFQvSfwQouW9368/present#slide=id.p19 Lesson and Learned ろ語 襷 覿 誤蠍 TCP 郁屋 螻 Critical Path襯 谿場 豕 http://modpagespeed.com/ http://ngxpagespeed.com/ngx_pagespeed_example/ Increasing Speed To Market In Mobile Development Through Continuous Integration http://velocityconf.com/velocity2013/public/schedule/detail/31073 Lesson and Learned 覈覦 覦壱 覦 ろ れ ル 覦壱 The Secret of Safe, Continuous Deployment: Perceptual Diffs http://velocityconf.com/velocity2013/public/schedule/detail/28452 覦襭: http://cdn.oreillystatic.com/en/assets/1/event/94/The%20Secret%20of%20Safe,%20Continuous%20Deployment_%20Perceptual%20Diffs%20Presentation%201.pdf Lesson and Learned How perceptual diffs make it safe for web-based software Why its not safe in general to deploy on commit The stumbling blocks weve hit and mistakes weve made Lesson and Learned Perceptual diffs are the best thing! 螻手碓 覯 ろ襴 穴骸 襦 覯 ろ襴 血 觜蟲 覦覯 觜螳朱 覲伎 觜蟲. 蟯 ろ: https://github.com/bslatkin/dpxdt The CSS and GPU Cheatsheet http://velocityconf.com/velocity2013/public/schedule/detail/31377 覦襭: http://cdn.oreillystatic.com/en/assets/1/event/94/The%20CSS%20and%20GPU%20Cheatsheet%20Presentation.pdf Lesson and Learned GPU + Layers = faster rendering Too many layers = seriously bad time Be aware of your CSS tags impact on CPU & GPU perf Use tooling to show off how many layers you have Building A Billion User Load Balancer http://velocityconf.com/velocity2013/public/schedule/detail/28410 Topics how facebook scales their load balancing infrastructure to support more than a billion users? Our Python decision engine is named Cartographer Lesson and Learned Context 殊殊殊 殊 狩 襭譴 11 3螳 狩 譟伎 磯 襭譴 狩 殊. Demo襯 語 る螻れ朱 願襯 り鍵 Scale Out LB 伎 TCP 語 伎 貎 襦襯 螻 覩瑚記覯 豌襴伎 焔レ 碁 Sonar襯 伎 襦 誤讌襯 蟆 Building A Performance Lab For Mobile Apps In A Day http://velocityconf.com/velocity2013/public/schedule/detail/31041 覦襭: http://www.slideshare.net/ashraymathur/velocity-building-a-performance-lab-for-mobile-apps-in-a-day-final Topics How to define and set baselines Performance metrics and instrumentations How to keep the performance optimized from code check-in to rollout
  • 5. Internal Monitoring to identify problems and avoid regressions Real User Monitoring to gauge customer experience App Crashes How to detect and handle app crashes & memory leaks Tools Some very important tools that need to be in your toolbox Perceived Performance Importance of adding performance in app design Lesson and Learned Metrics: Page Load Times, Network Metrices, Nav Timing Metrics, Server/Client Metrics 3 Esstntial Steps Mobile Automation App Instrumentation Mobile Infrastructure CI Launch Simulator and run tests Selenium for native iOS apps: https://github.com/moredip/Frank Stress/longevity testing Instrumentaion: https://github.com/lognormal/boomerang/ Monitoring gc log, heap dumps(by MAT) DevOps: Its Not Just For WebOps And We Have The Metrics To Prove It http://velocityconf.com/velocity2013/public/schedule/detail/28446