Platform as a Service and CloudBees

10 min read

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Platform as a Service (PaaS) is a crossover between IaaS and SaaS. This is a fuzzy definition, but it defines well the existing actors in this industry well and possible confusions. A general presentation of PaaS uses a pyramid. Depending on what the graphics try to demonstrate, the pyramid can be drawn upside down, as shown in the following diagram:

Cloud pyramids

The pyramid on the left-hand side shows XaaS platforms based on the target users’ profiles. It demonstrates that IaaS is the basis for all Cloud services. It provides the required flexibility for PaaS to support applications that are exposed as SaaS to the end users. Some SaaS actually don’t use a PaaS and directly rely on IaaS, but that doesn’t really matter here.

The pyramid on the right-hand side represents the providers and the three levels suggests the number of providers in each category. IaaS only makes sense for highly concentrated, large-scale providers. PaaS can have more actors, probably focused on some ecosystem, but the need is to have a neutral and standard platform that is actually attractive for developers. SaaS is about all the possible applications running in Cloud. The top-level shape should then be far larger than what the graphic shows.

So, which platform?

With the previous definition of platform, you just have a faint idea; your understanding about PaaS is more than IaaS and less than SaaS. The missing definition is to know what the platform is about.

A platform is a standardization of the runtime for which a developer is waiting to do his/her job. This depends on the software ecosystem you’re considering. For a Java EE developer, a platform means having at least a servlet container, managing DataSource to access the database, and having few comparable resources wrapped as standard Java EE APIs. A Play! framework developer will consider this as overweight and only ask for a JVM with web socket’s support. A PHP developer will expect a Linux/Apache/MySQL/PHP (LAMP) stack, similar to the one he/she has been using for years, with a traditional server hosting service.

So, depending on the development ecosystem you’re considering, platforms don’t have the exact same meaning, but they all share a common principle. A platform is the common denominator for a software language ecosystem, where the application is all that a specific developer will write or choose on their own. Java EE developers will ask for a container, and Ruby developers will ask for an RVM environment. What they run on top is their own choice.

With this definition, you understand that a platform is about the standardization of runtime for a software ecosystem. Maybe some of you have patched OpenJDK to enable some magic features in the JVM (really?), but most of us just use the standard Oracle Java distribution. Such a standardization makes it possible to share resources and engineering skills on a large scale, to reduce cost, and provide a reliable runtime.

Cloud and clustering

Another consideration for a platform is clustering. Cloud is based on slicing resources into small virtual elements and letting the users select as many as they need. In most cases, this requires the application to support a clustering mode, as using more resources will require you to scale out on multiple hosts.

Clustering has never been a trivial thing, and many developers aren’t familiar with the related constraints. The platform can help them by providing specialized services to distribute the load around the cluster’s nodes. Some PaaS such as CloudBees or Google App Engine provide such features, while some don’t. This is the major difference between PaaS offers. Some are IaaS-like preinstalled middleware services, while some offer a highly integrated platform.

A typical issue faced is that of state management. Java EE developers rely on HttpSession to store user’s data and retrieve them on subsequent interaction. Modern frameworks tend to be stateless, but the state needs to be managed anyway. PaaS has to provide options to developers, so that they can choose the best strategy to match their own business requirements. This is a typical clustering issue that is well addressed by PaaS because the technical solutions (sticky session, session replication, distributed storage engines, and so on) have been implemented once with all the required skills to do it right, and can be used by all platform users.

Thanks to a PaaS, you don’t need to be a clustering guru. This doesn’t mean that it will magically let your legacy application scale out, but it gives you adequate tools to design the application for scalability.

Private versus public Clouds

Many companies are interested in Cloud, thanks to the press for publishing all product announcements as the new revolution, and would like to benefit from them but as a private resource.

If you go back to the comparison in the Preface with an electricity production, this may make sense if you’re well established. Amazon or Google should have private power plants to supply giant data centers can make sense—anyway it doesn’t seems that they do but as backends. For most of companies, this would be a surprising company choice.

The main reason is that the principle of the Cloud relies on the last letter of XaaS (S) that stands for Service. You can install an OpenStack or VMware farm on your data center, but then you won’t have an IaaS. You will have some virtualization and flexibility that probably is far better than traditional dedicated hardware, but you miss the major change. You still will have to hire operators to administer the servers and software stack. You will even have a more complex software stack (search for an OpenStack administrator and you’ll understand). Using Cloud makes sense because there are thousands of users all around the world sharing the same lower-level resources, and a centralized, highly specialized team to manage them all.

Building your own, private PaaS is yet another challenge. This is not a simple middleware stack. This is not about providing virtual machine images with a preinstalled Tomcat server. What about maintenance, application scalability, deployment APIs, clustering, backup, data replication, high availability,monitoring, and support?

Support is a major added value of cloud services—I’m not just saying this because I’m a support engineer—but because when something fails, you need someone to help. You can’t just wait with the promise for a patch provided by the community. The guy who’s running your application needs to have significant knowledge of the platform. That’s one reason that CloudBees is focusing on Java first, as this is the ecosystem and environment we know best (even we have some Erlang and Ruby engineers whose preferred game is to troll on this displeasing language).

With a private Cloud, you probably can have level-one support with an internal support team, but you can’t handle all the issues. As for resource concentration, to build an impressive knowledge base.

All those topics are ignored in most cases as people only focus on the app:deploy automation, as opposed to the old-style deployments to dedicated hardware. If this is what you’re looking for, you should know that Maven was able to do this for years on all the Java EE containers using cargo. You can check the same at Cloud isn’t just about abstracting the runtime behind an API; it’s about changing the way in which developers manage and access runtime so that it becomes a service they can consume without any need to worry about what’s happening behind the scene.


The reason that companies claim to prefer a private cloud solution is security.

Amazon datacenters are far more secure than any private datacenter, due to both strong security policy and anonymous user data. Security is not about exploiting encryption algorithms, like in Hollywood movies, but about social attacks that are far more fragile. Few companies take care of administrative, financial, familial, or personal safety.

Thanks to the combination of VPN, HTTPS, fixed IPs, and firewall filters, you can safely deploy an application on Amazon Cloud as an extension to your own network, to access data from your legacy Oracle or SAP mainframe hosted in your datacenter. As a mobile application demonstrates, your data is already going out from your private network. There’s no concrete reason why your backend application can’t be hosted outside your walls.

CloudBees – embrace the development stack

CloudBees PaaS has something special in its DNA that you won’t find in other PaaS; focusing on the Java ecosystem first, even with polyglot support, CloudBees understands well the Java ecosystem’s complexity and its underlying practices.

Heroku was one of the first successful PaaS, focusing on Ruby runtime. Deployment of a Ruby application is just about sending source code to the platform using the following command:

git push heroku master

Ruby is a pleasant ecosystem because there are no such long debates on building and provisioning tools that we know of, unlike in JavaWorld, GemFile, and Rake, period.

In the Java ecosystem, there is a need to generate, compile the source code, and then sometime post the process classes, hence a large set of build tools are required. There’s also a need to provision runtime with dozens of dependencies, so a set of dependency management tools, inter-project relations, and so on are required. With Agile development practices, automated testing has introduced a huge set of test frameworks that developers want to integrate into the deployment process.

The Java platform is not just about hosting a JVM or a servlet container, it’s about managing Ant, Maven, SBT, or Gradle builds, as well as Grails-, Play-, Clojure-, and Scala-specific tooling. It’s about hosting dependency repositories. It’s about handling complex build processes to include multiple levels of testing and code analysis.

The CloudBees platform has two major components:

  • RUN@cloud is a PaaS, as described earlier, to host applications and provide high-level runtime services
  • DEV@cloud is a continuous integration and deployment SaaS based on Jenkins

Jenkins is not the subject of this article, but it is the de facto standard for but not limited to continuous integration in the Java ecosystem. With a large set of plugins, it can be extended to support a large set of tools, processes, and views about your project.

The CloudBees team includes major Jenkins committers (including myself #selfpromotion), and so it has a deep knowledge on Jenkins ecosystem and is best placed to offer it as a Cloud service. We also can help you to diagnose your project workflow by applying the best continuous integration and deployment practices. This also helps you to get more efficient and focused results on your actual business development.

The following screenshot displays the continuous Cloud delivery concept in CloudBees:

With some CloudBees-specific plugins to help, DEV@cloud Jenkins creates a smooth code-build-deploy pipeline, comparable to Heroku’s Git push, but with full control over the intermediary process to convert your source code to a runnable application. This is such a significant component to build a full stack for Java developers that CloudBees is the official provider for the continuous integration service for Google App Engine (, Cloud Foundry (, and Amazon.


This article introduced the Cloud principles and benefits, and compared CloudBees to its competitors.

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