PaaS with Java

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Presentation about PaaS Clouds with Java. Touches Google App Engine, VMforce, Amazon Beanstalk and why Spring is a good idea in these scenario.

Presentation about PaaS Clouds with Java. Touches Google App Engine, VMforce, Amazon Beanstalk and why Spring is a good idea in these scenario.

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  • 1. PaaS Cloud with JavaEberhard Wolff, Principal Technologist, SpringSource – A division of VMwareewolff@vmware.comTwitter: @ewolffBlog: http://ewolff.com © 2009 VMware Inc. All rights reserved
  • 2. Agenda§  A Few Words About Cloud§  PaaS – Platform as a Service§  Google App Engine§  Vmforce§  Amazon Beanstalk 2
  • 3. A Few Words About Cloud 3
  • 4. Three types of Clouds Infrastructure Platform Software as a Service as a Service as a Service •  Virtual Servers •  Virtual Application •  Software or Service •  Virtual Storage Server that you use •  Similar to •  Handles Scale-Out •  Components that you Virtualization •  Everything is add/integrate into your app •  Custom Solutions Services and APIs •  Manage Everything •  Usually Larger Buy-In Yourself •  Mostly Managed by Provider 4
  • 5. Cloud might be...•  Private /internal “on premise” –  In your data center –  Useful in particular for larger organizations•  Public “off premise” –  Hosted and Operated by a third Party –  Ideal for Startups etc•  Even smaller enterprises can create private clouds•  Based on virtualization 5
  • 6. Cloud at the Core is a Business Model§  Customer pays only for what he uses •  Per CPU hour or cycles, per GB of storage, per MB of network bandwidth •  Per user and year •  Not for having stand-by capacity§  Flexibility: More capacity is available on demand •  Instantly available •  Customer uses GUI or API to expand capacity •  Cloud provider is responsible for having capacity ready§  Makes IT just another service 6
  • 7. Why Cloud?§  Compelling Economics •  Lower CapEx •  Cheaper handling of peak loads •  Better resource utilization •  Simple to achieve benefits – direct ROI§  Flexibility and better productivity for development •  Much easier to set up environments •  Feasible to have production-like environments quickly and cheaply available •  Indirect: Better productivity leads to cost saving / better time to market 7
  • 8. OK, so let me get started 8
  • 9. So, let me get started§  Get an account at an IaaS provider§  …or virtualize your data center and create a self service portal§  Install your (Java EE) environment§  Install your (Java) application§  Done§  Wow, that was easy! 9
  • 10. That is not enough§  How do you deal with peaks? Need more app server instances§  The server instances must be shut down after the peak§  …otherwise you would pay for them§  Traditional middleware does not allow for that§  Elastic scaling§  RBMS prefer scale up (larger server)§  In the cloud it is easier to scale out (more server)§  That is why Amazon and Google use NoSQL / key-value stores 10
  • 11. That is not enough: Handling Lot of Date§  Traditional approach: Batch on a few nodes§  Alternative approach: Map / Reduce on many nodes§  Map each value using some function •  Runs on many nodes in parallel •  E.g. given a text file emit a word count each time a word is found§  Reduce takes the result of the map step and reduces it •  E.g. add up all word counts§  Distributed algorithm running on potentially many nodes§  Cloud: Can easily use a lot of nodes to run Map Reduce 11
  • 12. That is not enough: More Than Just a Virtualized Computer§  Additional services •  Amazon Simple Queue Service (SQS) •  Amazon Simple Notification Service (SNS) •  Amazon Simple Storage Service (S3) •  Amazon Elastic Block Store (EBS) 12
  • 13. Cloud Influences the Programming Model§  Some Jave EE technologies are not a good fit •  Non-JMS messaging technologies •  AMQP / RabbitMQ •  Amazon Simple Queue Service (SQS) •  Amazon Simple Notification Service (SNS) •  Two Phase Commit / JTA leads to long locking / strong coupling •  What do you do about Map / Reduce? •  What do you do about NoSQL?§  You might be better off with a different programming model •  Spring can handle non-Java-EE environments (e.g. Tomcat) •  Projects for NoSQL, AMQP … 13
  • 14. More Flexibility Needed§  And remember: You pay the resources you consume§  You need to use more or less resources based on load§  You need to be able to shut down servers if load is low§  You need to be able to start new servers if load is high 14
  • 15. What you will eventually come up with§  A tool to take an Application§  …and create a VM with all needed infrastructure etc§  Need tools to •  Install software •  Manage infrastructure •  Configure infrastructure •  Set up user etc •  Puppet, Chef etc.§  Like a factory for VMs 15
  • 16. So…§  Can we automate this?§  Developers just want a platform to run applications on§  Also: Developers need other non-Java-EE services 16
  • 17. Introducing… 17
  • 18. The PaaS! 18
  • 19. Platform as a service (PaaS) the delivery of acomputing platform and solution stack as a service. 19
  • 20. Not just automated… 20
  • 21. Invisible PaaS 21
  • 22. PaaS: Advantages and Disadvantages§  Advantages •  More useful than IaaS: You would need to install a server anyway •  Automatic scaling •  Resources automatically added •  Can offer additional service •  Tuned for Cloud •  Technical e.g. data store, messaging, GUI elements •  Domain e.g. predefined data model§  Disadvantages •  Less flexible •  Pre-defined programming model •  Defines environment •  Programming model might be different •  Hard to port existing code •  Need to learn 22
  • 23. Google App Engine 23
  • 24. Google App Engine§  Infrastructure offered by Google§  Supports Java and Python§  Infrastructure completely hidden§  GAE sandbox more restrictive than normal JVM sandbox§  So GAE can handle your application better§  Java classes white list •  i.e. some Java classes must not be used •  no Thread •  no file system •  parts of System class (e.g. gc(), exit()…) •  Reflection and ClassLoader work 24
  • 25. Google App Engine: Storage§  Relational database only in App Engine for Business§  Based on BigTable •  Googles storage technology •  Key/value i.e. objects stored under some key •  No joins •  Simple / simplistic (?) •  Scalable •  Example of NoSQL •  Principles will be discussed further in NoSQL§  Max. 1 MB per entity (and other limitations) 25
  • 26. Google App Engine: Storage APIs§  API: Low level com.google.appengine.api.datastore •  Not compatible to JDBC or the like •  Queries, transactions, entities etc. •  Should only be used by framework§  API: JDO (Java Data Objects) •  Standard for O/R Mapper and OODBMS •  Unsupported: Joins, JDOQL grouping and aggregates, polymorphic queries§  API: JPA (Java Persistence API) •  Well established standard for O/R Mappers •  Unsupported: Many-to-many relationships; join, aggregate and polymorphic queries, some inheritance mappings§  Problem: JPA / JDO based on RDBMS, but this is key/value §  So maybe use the low level API instead?§  JPA and JDO actually implemented by Data Nucleus library •  Byte code must be enhanced in an additional compile step 26
  • 27. Google App Engine: Additional services§  Memcache •  Implements JCache (JSR 107) •  Fast access to data in memory§  URL Fetch based on java.net.URL to read data via HTTP§  EMail support using JavaMail§  XMPP instant messages (proprietary API)§  Image Manipulation (proprietary API)§  Authentication / Authorization based on Google accounts (proprietary API)§  Task queuing (proprietary API, experimental)§  Blob store (proprietary API, experimental) for data >1MB§  Numerous other services available (not tied to App Engine) §  Google Predict, Google BigQuery … 27
  • 28. Google App Engine for Business§  Centralized administration.§  99.9% uptime SLA§  Premium developer support available.§  Sign on for users from your Google Apps domain§  Announced •  SSL on your company’s domain for secure communications •  Access to advanced Google services. 28
  • 29. Google App Engine§  Documentation + SDK + Eclipse Plug In available§  SDK contains environment for local tests§  Spring / Spring Roo is the preferred programming model§  …as it is popular and works with the limited model of the Google App Engine§  http://code.google.com/appengine/ 29
  • 30. Google App Engine Demo © 2009 VMware Inc. All rights reserved
  • 31. 31
  • 32. VMforce§  Joined offerings by Salesforce and VMware§  Salesforce •  Leading provider for SaaS / CRM§  Salesforce offers force.com environment •  Scalable PaaS •  Database + data model •  Charting •  Reporting •  Chat etc§  VMforce = force.com + VMware virtualization + SpringSource programming model 32
  • 33. vmforce Vision§  VMforce = force.com§  + VMware virtualization •  Offers IaaS foundation§  + SpringSource tc Server / Hyperic§  + Spring programming model force.com§  i.e. run your standard Platform Spring Apps SpringSource Services tc Server§  Use force.com data (charts, model / database reports) VMware§  …and charts / reports Force.com vSphere Database§  Apply for the beta at http://www.vmforce.com/ 33
  • 34. Amazon BeanStalk§  Based on the Amazon EC2 infrastructure§  Add Linux, OpenJDK, Tomcat§  Currently in beta§  …and only in US-East§  Eclipse Plug In available§  Supports version handling of applications§  Supports scaling depending on load indicators§  Access to Tomcat logs etc.§  Videos to get started§  Demo application based on Spring •  Uses also S3 (storage) and Simple Notification Service (SNS) 34
  • 35. PaaS: Conclusion§  PaaS offer a runtime environment in the cloud§  Usually based on IaaS§  Makes Cloud easier usable for a developer§  …but less customizable and less choice§  Technical challenges (scalability) solved by platform§  Spring can be used as a universal model§  Each PaaS differentiate themselves with their added services §  VMforce: database model, charts, reports, GUI elements (functional components) §  GAE: Big Table, caching, security, image processing, blob storage (technical platform) §  Amazon Beanstalk: Standard Java stack§  Choose the right tool for the job! 35