Week 15 - Scaling & Security_Jim Huang
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This document discusses software performance analysis and security issues related to app development. It begins by introducing the speaker and his background. The rest of the document covers concepts around scaling systems to handle increased traffic, such as database scaling through master-slave and sharding approaches. It also discusses performance considerations like caching and synchronization primitives. Finally, it touches on security topics like security groups in cloud computing environments.
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Week 15 - Scaling & Security_Jim Huang
- 1. App創業與實作 本授權條款允許使用者重製、散布、傳輸著作，但不得為商業目的之使用，亦不得修改該著作。 使用時必須按照著作人指定的方式表彰其姓名。 App Entrepreneurship and implementation Week 15 軟體效能分析與安全性議題 黃敬群 Jim Huang (聯發科技顧問) (2013-05-30)
- 3. 淺談系統效能與安全議題 Jim Huang ( 黃敬群 ) <jserv@0xlab.org> May 30, 2013 / NTHU, Taiwan
- 4. About me • 台灣創新行動服務推廣協會 / 理事長 • 成功大學資訊工程系 / 兼任教師 • 聯發科技 / 顧問 • 杏昕科技 / 技術長 • 晶心科技 / 幕僚工程師 • 開放原始碼開發 – 新酷音輸入法 , GCC / GNU Classpath, LXDE, Android Open Source Project • Others: http://about.me/jserv
- 5. About this presentation • 我不是專家，只是碼農 • 今天不是以經營者的觀點去解讀，而以 * 低層次 * 工程師的角度去分享
- 6. Think of the possibility 萬一你的期末計畫或者玩票性質的 App 獲得上萬次下載，接著會如何？
- 7. Think of the possibility source: http://www.cw.com.tw/article/article.action?id=5033139 部落客化身食譜網站創辦人，平均年齡三十的大男生，如何改寫日本 最大食譜網站的成功模式，六個月攻陷萬名粉絲？ 三千多道菜，每天有二十多道新菜色上線。每個月有近三百萬瀏覽 量，熱烈討論哪道人氣菜色怎麼煮，食材可以在哪裡買。 這是上線才半年，食譜分享社群網站「 iCook 愛料理」的成績。
- 8. The traffic 3M visit per month; 10K members in 6 month
- 9. The impact • operation cost – 當瀏覽次數從每月 3K 到每月 3M ，成本即以指 數性成長 • membership variance – 當會員數量超過 1K 時，很可能面臨質變，考驗 經營者的智慧 • performance impact – 原本的雛型設計勢必得改寫，無論是 web 前端 、後端、資料庫，抑或整體的運作模型 • security issue – 樹大招風
- 11. Agenda (1) Concepts about Scaling (2) Performance
- 13. Scaling • 以 web 為例，有以下考量點 – web server – database – caching one server load balanced
- 14. Database Scaling Everyone starts with just one server: Multiple steps to take as you move forward
- 16. Step 1: Master/Slave - Preparation Even with one server: Make code write to master and read from slave Don't write code that would fail with slave lag: $master->query('update users set comments += 1'); $slave->query('select comments from users');
- 17. Step 2: Multiple Slaves
- 18. One slave per server? Not as flexible
- 20. Code to select Random Slave class DB { private static $cfg = array( 'write' => array('mysql:dbname=MyDB;host=10.1.2.3'), 'read' => array('mysql:dbname=MyDB;host=10.1.2.7', 'mysql:dbname=MyDB;host=10.1.2.8', 'mysql:dbname=MyDB;host=10.1.2.9'); ); public static function getConnection($pool) { $max = count(self::$cfg[$pool]) - 1; $dsn = self::$cfg[$pool][mt_rand(0, $max)]; return new PDO($dsn, USER, PASS); } } $db = DB::getConnection('read');
- 21. Step 3: Slave Pool Virtually divide your slaves into pools Use this to isolation high database load Potentially enhance query caches
- 23. Step 4: Partitioning Simplest Definition: Break your tables or databases into smaller ones
- 24. Cost of Partitioning • Loss of direct SQL support • Increased Web Server / Application Load • More complicated programming
- 25. Caching in Brief • Often considered performance • Can absolutely be a scalability factor, especially when combined with smaller discrete DB queries • Allows you to get around DB scalability by ignoring the DB
- 26. Type of Caching • Single server memory caches – For PHP: APC or Zend Server Data Cache – Limited due to lack of sync'd cache • Distributed – Memcached (Generic) or Zend Platform (PHP) – Required for true scalability enhancement
- 27. Performance
- 28. Synchronization Primitives Work Partitioning Interacting With Hardware Parallel Access Control Resource Partitioning & Replication Do this first! Job #1 is not selecting primitives!
- 29. Atomic Increment of global variable CPU CPU CPU CPU $ $ $ $ Interconnect CPU CPU CPU CPU $ $ $ $ Interconnect CPU CPU CPU CPU $ $ $ $ Interconnect CPU CPU CPU CPU $ $ $ $ Interconnect Interconnect MemoryMemory Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Lots and Lots of Latency!!!
- 30. Security
- 32. … DB Security Group Web Security Group Understanding security groups … … WebWeb VMVM WebWeb VMVM WebWeb VMVM WebWeb VMVM WebWeb VMVM WebWeb VMVM WebWeb VMVM WebWeb VMVM DB VM DB VM WebWeb VMVM WebWeb VMVM DB VM DB VM WebWeb VMVM WebWeb VMVM Ingress Rule: Allow VMs in Web Security Group access to VMs in DB Security Group on Port 3306
- 33. Atomic Increment of per CPU variable CPU CPU CPU CPU $ $ $ $ Interconnect CPU CPU CPU CPU $ $ $ $ Interconnect CPU CPU CPU CPU $ $ $ $ Interconnect CPU CPU CPU CPU $ $ $ $ Interconnect Interconnect MemoryMemory Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Store Buffer Little Latency, Lots of Increments at Core Clock RateLittle Latency, Lots of Increments at Core Clock Rate
- 34. Cloud at scale • Host management • Capacity management • What host to use to deploy a new VM • Failure handling • Security group propagation
- 35. Reference • Highly Scalable Web Applications, Eli White (2009) • 雲端運算 - 商業模式、核心技術與架構 , Jazz Wang (2012)
- 36. http://0xlab.org