Presentation about Cloud technologies for Java from the Berlin Expert Days.

1. Cloudy in Indonesia – Java and Cloud
Eberhard Wolff
Architecture and Technology Manager
adesso AG
Twitter: @ewolff
Blog: http://ewolff.com

2. About me
► Eberhard Wolff
► Architecture & Technology Manager at adesso
► adesso is a leading IT consultancy in Germany
► We are hiring
► Speaker
► Author (i.e. first German Spring book)
► Blog: http://ewolff.com
► Twitter: @ewolff
► eberhard.wolff@adesso.de

3. Agenda
 A Few Words About Cloud
 Java and IaaS
 PaaS – Platform as a Service
 Google App Engine
 CloudBees
 Amazon Beanstalk

4. A Few Words About Cloud

5. Infrastructure Platform Software
as a Service as a Service as a Service
> Virtual Servers > Virtual Application Server > Software or Service
that you use
> Similar to Virtualization > Handles Scale-Out
> Components that you
> Manage Everything > Mostly Managed by add/integrate into your
Yourself Provider app

6. 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

7. 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

8. Why Cloud?
► Compelling Economics
> Lower CapEx
> Cheaper handling of peak loads
> Better resource utilization
> Simple to achieve benefits – direct ROI
> Chances are your data center is not as efficient as Amazon’s, Microsoft’s or
Googles’s

9. Why Cloud?
► Flexibility and better productivity for development
> Self service portal
> Much easier to set up environments
> Feasible to have production-like environments quickly
and cheaply available
> …or environment for load tests
> Indirect: Better productivity leads to cost saving / better
time to market

10. Why Cloud?
► Better Service
> Higher Availability
> Better Reliability
> Redundancy across multiple data centers
> Lower latency because of local data centers

11. What this is all about...
WAR

12. 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!

13. 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
► Map / Reduce for analyzing large data sets

14. 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 …

15. And what about Java EE 7?
► Java EE 7 is supposed to be about Cloud
> Multi-Tenant systems
> Probably new roles like PaaS Administrator
> Cloud services
► I am currently not aware of Cloud offerings that support Java EE out of the box
► I.e. beyond manual installation on an IaaS or provided images
► In particular no PaaS

16. 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

17. What you will eventually come up with
► A tool to take an Application
App
► …and create a VM with all needed infrastructure etc
► Dynamically i.e. scale up and down
► Need tools to
> Install software
> Manage infrastructure
> Configure infrastructure
> Set up user etc
> Puppet, Chef etc.
► Like a factory for VMs
► Works on Private Cloud, Public Cloud or your VM VM
local machine
► Vagrant

18. So…
► Very flexible
► Works for any IaaS and any software to be installed
► Works for complex environments with many infrastructure pieces
> Install a database server, some Tomcats, a load balancer and a cache server
> Fine tune all the parameters
► Can deploy different parts of the application to special nodes
► But often developers just want a platform to run applications on
► No fine tuning
► Also: Developers need other non-Java-EE services

19. Not just automated…
App
VM

20. Invisible
App
PaaS

21. PaaS
► Platform as a service (PaaS) is the delivery of a computing platform and solution
stack as a service.

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
• …but IaaS does the same (Amazon)
 Disadvantages
• Less flexible
• Pre-defined programming model
• Defines environment
• Programming model might be different
• Hard to port existing code
• Need to learn

23. Google App Engine

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

25. Google App Engine: Storage
 Relational database only in App Engine for Business
 Based on BigTable
• Google's storage technology
• High replication or simple master / slave
• Key/value i.e. objects stored under some key
• No joins
• Simple / simplistic (?)
• Scalable
• Example of NoSQL
 Max. 1 MB per entity (and other limitations)

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

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
 Channel (to talk to JavaScript in the browser)
 Numerous other services available (not tied to App Engine)
 Google Predict, Google BigQuery, AdSense, Search, …

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
> Relational database

29. Google App Engine
 Documentation + SDK + Eclipse Plug In available
 SDK contains environment for local tests
 http://code.google.com/appengine/

30. Google App Engine
► Pioneer: Very early in the market
► Very restrictive environment
> Limited sandbox
> Focus on NoSQL while typical Java applications use RDBMS
> Limit on start up time of application etc
> Limit on response time (30 seconds)
> No control or access to operating system
> Not even the web server
► So specialized frameworks have been created (Gaelyk for Groovy)
► Benefits?

31. Amazon Beanstalk

32. Amazon Web Services
► Collection of Cloud Offerings (mostly IaaS)
► Elastic Compute Cloud (EC2)
► Elastic Map Reduce
► Auto Scaling
► SimpleDB : Big Table like NoSQL database
► Simple Queue Service (SQS)
► Simple Notification Service (SNS)
► Simple Email Service (SES)
► Virtual Private Cloud (VPC)
► Simple Storage Service (S3)
► Elastic Block Storage (EBS)
► Third party offerings like https://mongohq.com/ for MongoDB and
https://cloudant.com/ for CouchDB

33. Amazon BeanStalk
► Based on the Amazon EC2 infrastructure
► …and Auto Scaling and S3
► Add Linux, OpenJDK, Tomcat
► Currently in beta
► …and only in US-East
► Eclipse Plug In available
► Supports version handling of applications
► Supports elastic scaling depending on load indicators
► Simple Monitoring built in
► Detailed control over the environment (Tomcat parameters, used AMIs, log in to
machine etc.)

34. Amazon BeanStalk
► Access to Tomcat logs etc.
► Access to the OS
► Fine tuning of Tomcat parameters possible
► Easy, yet powerful
► Videos to get started
► Demo application based on Spring
> Uses also S3 (storage) and Simple Notification Service (SNS)
► Add Relational Database Service (RDS) for enterprise scale MySQL
► …and all the other Amazon Web Services (AWS)

35. Amazon BeanStalk
► Much like your average Enterprise Java environment
► =Tomcat + RDBMS
► Cloud features like elastic scaling available
► Can easily add other AWS elements
► Runs on a proven environment
► But: 1 server = 1 virtual machine
► GAE can run multiple applications on one machine
► More cost efficient (?)

36. CloudBees

37. CloudBees: DEV@Cloud
► In fact two services: DEV@Cloud and RUN@Cloud
► DEV@Cloud: Developer services
► Continuous Integration (Jenkins)
> Good application of the Cloud: Peaks and high load only during working hours
> Standardized and universally applicable service
> Some Essentials Plug Ins in free version
> More in Base / Pro / Enterprise pay version
> Also more parallel build in pay version
> …and faster build machines
► Maven repository
> Snapshot / Release
> Builds can be automatically deployed
► Potentially other services

38. CloudBees: RUN@Cloud
► Tomcat on EC2
► Easily deploy a WAR
> either by web interface
> or command line utility (bees SDK)
► Little control
> Only 256MB heap
> Single instance or multiple instance
> No elastic scaling
> Potentially cheaper: Can you multiple application on one machine
► Simple monitoring (web / command line)
► MySQL database
> Very simple (i.e. just one server, but backup included)
> Could use Amazon RDS instead

39. Java in the Cloud: Conclusion
 Feasible to run Java applications in the cloud
 IaaS
 Maximum control
 Automatic installation needed
 Also works on private cloud / virtualized environment
 Google App Engine
 Very limited sandbox
 Advantage?
 Amazon Beanstalk
 Standard Enterprise Java Stack
 Lots of additional Amazon Web Services (Relational Database Service)
 CloudBees
 DEV@Cloud: Developer-only features (Jenkins)
 RUN@Cloud: simple but probably more price efficient

40. Wir suchen Sie als
 Software-Architekt (m/w)
 Projektleiter (m/w)
 Senior Software Engineer (m/w)
jobs@adesso.de
www.AAAjobs.de