PaaS - google app engine
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The document discusses Google App Engine, a platform as a service (PaaS) that allows developers to focus on development rather than operations. It presents Google App Engine as having a "virtual raised floor" with the IDE above the floor and website/deployment system below. It provides an overview of Google App Engine's history and supported languages/data stores. It also summarizes code samples for a guestbook application and MapReduce workflow on Google App Engine.
PaaS - google app engine
- 1. Google App Engine (Platform as a Service) Boston Cloud Services Meetup J Singh January 14, 2014
- 2. PaaS Goal: Focus on Development, not Ops • Virtual Raised Floor – IDE above the floor – Website for visibility and control below the floor – Deployment System ( Tile Lifter) © DataThinks 2013-14 2 2
- 3. IDE Above the Floor • The programmer’s development environment – Presentation layer: HTML, CSS, JavaScript – Control layer: Web Server code • Access to external APIs – Data layer: Data Model • Indexing advice – Optionally, analytics © DataThinks 2013-14 3 3
- 4. Ops below the floor • Made visible through a web interface – – – – – – Operating System File System User Authentication Utilities (cron, etc.) Logs Database maintenance, backups, etc. © DataThinks 2013-14 4 4
- 5. Deployment System • Methods for continuous deployment – Upload – Version management © DataThinks 2013-14 5 5
- 6. Google App Engine • Strategic Technology Offering for Server-side applications – Vehicle for introducing internal technology to the outside developer community – Not to be confused with Google Apps – Frequent criticism: • Single-source • Except for AppScale (GAE code that runs on Amazon) © DataThinks 2013-14 6 6
- 7. Google App Engine History • Introduced in 2008 – Python, Google DataStore • Now – Languages • Python, Go, PHP, Java – And languages that compile to JVM byte codes – Data Stores • Google DataStore (NoSQL), CloudStore (Cloud intf to MySQL) – Map Reduce © DataThinks 2013-14 7 7
- 8. Sources • Getting Started Instructions: (http://goo.gl/Wc4A9R) • Map Reduce Instructions: (http://goo.gl/gzmj7T) • Code: (http://goo.gl/SqmCKk) (a Github repository) – Commit 0e24b6ad7: Guestbook application – Commit 68f929415: Fetching from a Gutenberg.org URL • Gets “Permission Denied” from gutenberg.org • Change to read & parse pages from Wikipedia or another source – Commit 1740fedc6: Map Reduce changes © DataThinks 2013-14 8 8
- 9. Guestbook Application • Application Demo (http://goo.gl/ItxjME) • Code walk through: – Dispatching – Code – Templates – Write something in the guestbook, – Log in, write again, – … • Change page text • Console walk through: • Delete some guestbook entries – Dashboard – DataStore – Logs © DataThinks 2013-14 9 9
- 10. Map Reduce Flow © DataThinks 2013-14 10 10
- 11. Map Reduce Pipelines • Map Reduce is rarely a singular operation • Multiple Map Reduce operations are pipelined together – Fan out, synchronization semantics © DataThinks 2013-14 11 11
- 12. Map Reduce Application • Application Demo (http://goo.gl/KUPDc1) • Code walk through: – WordCountPipeline – word_count_map – word_count_reduce • Where are the results? © DataThinks 2013-14 12 12
- 13. Thank you • J Singh – Principal, DataThinks • j.singh@datathinks.org – Adj. Prof, WPI © DataThinks 2013-14 13 13