首页 Spring in the Cloud

Spring in the Cloud

举报
开通vip

Spring in the Cloud Spring in the Cloud About me •  Eberhard Wolff •  Architecture & Technology Manager at adesso •  adesso is a leading IT consultancy in Germany •  Speaker •  Author (i.e. first German Spring book) •  Blog: http://ewolff.com •  Twitter: @ewolff •  ...

Spring in the Cloud
Spring in the Cloud About me •  Eberhard Wolff •  Architecture & Technology Manager at adesso •  adesso is a leading IT consultancy in Germany •  Speaker •  Author (i.e. first German Spring book) •  Blog: http://ewolff.com •  Twitter: @ewolff •  eberhard.wolff@adesso.de Content •  What is the Cloud? •  My First Cloud App •  Scaling the App •  Another Cloud Challenge •  Java EE 7 •  Conclusion What is the Cloud? Infrastructure as a Service Platform as a Service Software as a Service >  Software or Service that you use >  Components that you add/integrate into your app >  Virtual Application Server >  Handles Scale-Out >  Mostly Managed by Provider >  Virtual Servers >  Similar to Virtualization >  Manage Everything Yourself Why Cloud? •  Compelling Economics –  Lower CapEx –  Cheaper handling of peak loads •  Flexibility and better productivity for development –  Self service portal –  Much easier to set up environments •  Better Service –  Redundancy across multiple data centers –  Lower latency because of local data centers So: What Shall I use? •  IaaS: Maximum control, but: –  Need to install infrastructure –  Need to install application –  How do you do application updates? •  PaaS: Much easier to handle –  …but often less flexible –  Monitoring, deployment etc built in –  Probably the better choice Google App Engine •  Non relation data store (NoSQL) •  (Limited) JPA interface to data store •  Available Java classes limited (White List) •  No control over web server, operating system •  Strategic partnership SpringSource / Google •  Spring works Amazon Beanstalk •  Tomcat + OpenJDK + Linux on EC2 •  + Monitoring, Versioning, Events… •  Auto Scaling •  Can add MySQL (RDS) with backup etc •  Sample application uses Spring Cloud Bees •  Focus on DEV@Cloud –  Continuous Integration –  Maven Repository •  RUN@Cloud: Tomcat+OpenJDK + Linux on EC2 •  Announce beta for Private Cloud •  MySQL also available •  Very limited scaling / SLAs •  Spring works VMware Cloud Foundry •  Tomcat on VMware Public Cloud or Micro Cloud (i.e. laptop) or EC2 or … •  Platform is Open Source •  Can add MySQL, Redis, MongoDB •  Services injected into application •  Framework support needed •  Spring: A MySQL DataSource is rewired to a MySQL service Cloud Foundry Spring Integration •  Cloud namespace: bind to Cloud Foundry services •  Works with Spring 3.0.5 •  Note: No need for environment specific config •  App can run unchanged in test / dev / production Cloud Foundry environments PaaS Conclusion •  Spring (+ Tomcat) own the Cloud •  Also predominant non-Cloud Enterprise platform •  Lightweight – more important for Cloud –  Pay any consumed resource –  PaaS: Need operations / monitoring / deployment –  Easier for a simple environment •  Spring has always been about portability •  Not just Java EE / Tomcat / … - also Cloud Full Java EE Stack? •  Spring & Tomcat: The Enterprise & Cloud Java dream team •  Of course can also use other Java EE APIs on Tomcat •  There is no offering for a full Java EE PaaS stack •  i.e. including EJB, JMS, JTA … My First Cloud App Tomcat Catalog Order RDBMS My First Cloud App: Platform •  Programming model Same as for Enterprise Java Apps •  E.g. JSF + Spring + JPA … •  Run on IaaS: Need to install infrastructure –  Must be automated •  Google App Engine –  JSF probably won’t work –  Spring and GWT will –  No RDBMS - but NoSQL with (limited) JPA My First Cloud App: Platform •  Amazon Beanstalk Cloud Bees Cloud Foundry –  Environment you are used to: Tomcat + MySQL –  Cloud Foundry: Optional cloud namespace in the configuration •  For a start a normal Spring application is OK •  What are the limits? How Is Cloud Different? •  Need to be able to add new servers •  Provided for by PaaS •  New servers must be able to handle load instantly (warm cache) •  Prefer Scale Out instead of Scale Up •  i.e. add new servers instead of bigger ones •  Usually not an option with RDBMS •  Scale up is possible but limited How Is Cloud Different? •  Complex networks setup •  Nodes might be unavailable •  Might want to run cluster across data center for availability •  Server might and will fail •  Very different from normal servers How Is Cloud Different? So How Is Cloud Different? •  No operations department to blame •  Unreliable and potentially slow network •  How can you even dare to build reliable systems that way? •  Amazon and Google accomplish that •  Will happen in Enterprises as well •  Much more efficient in operations / development So How Is Cloud Different? •  No operations department to deal with – just a portal! •  Multiple world-wide distributed data centers available to you! –  Redundancy –  Low latency from any place •  New virtual computers spun up in minutes! •  Need a larger machine – just reboot! Cloud is Just Another Trade Off •  How can applications be successfully created in this environment? CAP Theorem •  C: Consistency: All nodes see the same data •  A: Availability: Node failure does not prevent survivors from operating •  P: Partition Tolerance: System works even though message are lost •  Choose any two •  No P in the Cloud? •  So A or C? Consistency Partition Tolerance Availability RDBMS 2 Phase Commit DNS Replication Quorum My First Cloud App Tomcat Catalog Order RDBMS Actually works Now let’s scale it up …and enter the globalized world Scaling My First Cloud App Tomcat Catalog Order RDBMS RDBMS RDBMS Replication? Across data centers? Write performance? Reliable? Fast? Global business More customers Catalog used a lot more than Order Scaling My First Cloud App •  IaaS –  Can use other regions and scale datastore –  Limits of technology (RDBMS) still apply –  Need to installation / configuration it yourself •  Google App Engine –  Datastore scales well –  Global data centers? •  Amazon Beanstalk –  Turn key MySQL with replication (RDS) –  …but of you can’t change the limits of RDBMS –  Beanstalk only in US East at the moment Scaling My First Cloud App •  Cloud Bees –  Data center only in the US –  MySQL installation very limited –  Can use Amazon RDS •  Cloud Foundry –  Data centers only in the US –  MySQL limited •  You will need to do more yourself e.g. on EC2 •  Less support by the PaaS Tomcat My Second Cloud Application Tomcat Catalog Catalog Updates as messages Will be eventually delivered AP, but no C Catalog separated Because of load My Second Cloud Application •  Parts of application separated because of scaling scheme •  Introduce “Eventual Consistency” –  Either using NoSQL (e.g. CouchDB) –  …or using messaging –  Might consider in memory or cache (Redis, memcached, GemFire) •  RabbitMQ is the predominant approach for messaging in the cloud –  NASA’s nebula project –  #1 on EC2 –  Support in Cloud Foundry planned •  More messaging: Amazon SNS, SQS … Tomcat My Second Cloud Application Tomcat Order Order Orders are sent as messages Will eventually be sent to the backend Will eventually be handled by the backend 2nd Cloud App: Programming Model •  Very different from a normal Enterprise Java three tier application •  Not so different from a portal •  No one global database •  Focus on messaging •  Need support for RabbitMQ / AMQP •  I.e. Spring AMQP (see other talk) •  Programming model very much like Spring JMS •  Can create message driven POJOs 2nd Cloud App: Programming Model •  Need NoSQL / Caching / Data Fabric •  See Spring Data talk •  Spring supports many relational technologies –  iBATIS, Hibernate, JPA … –  E.g. common exception –  Uniform API approach –  Still specific API for each technology •  These abstractions are flexible •  Can be used for NoSQL as well! •  Catalog browsing statistics from log files •  i.e. how many customer looked at X? •  Sounds like a batch •  File in, statistics out •  With Spring Batch •  But: Globally distributed data •  A lot of data •  Some systems might not be online •  How do you deal with that? Another Cloud Challenges Spring Batch? •  Spring Batch can be used to run batches •  I.e. Jobs with steps •  But: –  How do you deal with the distribution? –  No central place with all the data –  Do you prefer incomplete data or no data at all? •  Need something different. Map / Reduce •  Map: Apply a function to all data –  Emit (item name, 1) for each log file line •  Master sorts by item name •  Reduce: Add all (item name, 1) to the total score •  Map can be done on any node •  Master collects data Map Map Reduce Map / Reduce Benefits •  Data can stay on workers •  Can done in parallel on many machines •  Prefer answer on available data over no answer at all •  Can deal with redundant storage •  But: –  Lot of network communication –  More work in total Spring Hadoop •  Hadoop is a complete solution for Map/Reduce •  HDFS Filesystem •  HBase Database •  Hive for Data Warehousing / ad hoc queries •  Spring Hadoop adds templates and POJO based model •  https://github.com/springsource/spring-hadoop And What About Java EE 7? •  Cloud is one of topics for Java EE 7 •  Theme: Multi-Tenant / Isolation of customers •  New role: PaaS Administrator •  Additional security •  QoS •  Application Metadata •  Caching will become more important and will be covered by Java EE The Cloud Challenge Java EE Does Not Solve •  JTA = 2PC = CA, not P •  JPA / JDBC = CA, not P •  Will you use that in the Cloud? •  NoSQL? •  RabbitMQ? Java EE 7 & Cloud •  Multi tenant: Just one way to isolate users •  Can also use virtual machines, individual servers etc •  Multi tenant good for lots of small applications •  Has been used for SaaS systems •  Tomcat and Servlets dominate the Cloud market •  When will certified Java EE 7 servers be available? •  Who will provide a Cloud based on Java EE 7? Conclusion •  IaaS is very flexible •  PaaS makes deployment, monitoring and operations easier •  All Java PaaS support Spring •  Demanding Cloud applications need –  AMQP messaging –  NoSQL / Caching –  Map/Reduce •  Spring’s general abstractions can be extended to support this •  Concepts you are used to! •  Java EE is stuck with “traditional” enterprise systems www.AAAjobs.de jobs@adesso.de Wir suchen Sie als   Software-Architekt (m/w)   Projektleiter (m/w)   Senior Software Engineer (m/w)   Kommen Sie zum Stand und gewinnen Sie ein iPad 2!
本文档为【Spring in the Cloud】,请使用软件OFFICE或WPS软件打开。作品中的文字与图均可以修改和编辑, 图片更改请在作品中右键图片并更换,文字修改请直接点击文字进行修改,也可以新增和删除文档中的内容。
该文档来自用户分享,如有侵权行为请发邮件ishare@vip.sina.com联系网站客服,我们会及时删除。
[版权声明] 本站所有资料为用户分享产生,若发现您的权利被侵害,请联系客服邮件isharekefu@iask.cn,我们尽快处理。
本作品所展示的图片、画像、字体、音乐的版权可能需版权方额外授权,请谨慎使用。
网站提供的党政主题相关内容(国旗、国徽、党徽..)目的在于配合国家政策宣传,仅限个人学习分享使用,禁止用于任何广告和商用目的。
下载需要: 免费 已有0 人下载
最新资料
资料动态
专题动态
is_688726
暂无简介~
格式:pdf
大小:4MB
软件:PDF阅读器
页数:44
分类:互联网
上传时间:2012-01-20
浏览量:87