Review: Cloud automation tools

RightScale, Tap In, Appistry automate batch processing jobs in the public cloud

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Fortunately, other Appistry processing parts can be highly automated and Appistry lends its power specifically towards Web instances and development. To get the best automation results, we found that you need to build your applications more or less around Appistry — although it's not required. Appistry applications need, at minimum, a wrapper built around application unless Java, .Net, and/or C/C++ code is used to talk to Appistry's CloudIQ Engine.

We tested Appistry on Amazon EC2, although it's also supported on GoGrid or private clouds. Installation is easy, although after launching the first instance, we needed to copy the Private DNS host address into the user data of each subsequent instance so the others can find the first instance on Amazon Machine Images.

If you use it on your own private cloud (on your own network), the instances should be able to find each other through multicast. We occasionally found communications problems among components of Appistry instances and processes on Amazon.

The CloudIQ Engine is a runtime container for Java, .Net and/or C/C++ code. It's also possible to create other 'wrappers' around code and executables in other languages. The console displays fabrics, which are the framework of cloud instances that workers process within.

The console can be accessed on any of the instances within the fabric, and the fabrics can be woven together through instances of the Appistry Network Bridge. Console access requires a browser, an instance of Java, and Adobe Air. The CloudIQ engine can launch tasks which will then be taken care of by the fabric workers.

The CloudIQ Platform user interface divides a fabric into applications, services, packages and workers. Applications monitored are fabric processes, that use services, existing in packages, that are, in turn, attended to by workers. The fabric's work output is homogeneous, as workers have identical processes running on them. The fabrics can be linked together to create dependencies among the workers' discrete fabric processes.

CloudIQ Storage is similar in concept to Amazon S3, and in a way competes with S3. Each instance of CloudIQ Storage can be in different locations but they all work together as one group and look like one virtual drive. Generally, CloudIQ files are synced with each other (for example the same files are located on each storage location).

In the case of the Amazon Appistry images, the CloudIQ storage is built-in to the image which means by default the storage will disappear along with the instances, unless of course you change the default directories to Amazon Elastic Block Storage (EBS) volumes. This also means that storage is pre-allocated, and finite within the instance by default.

In our testing, we created a wrapper program to launch the ffmpeg video rendering application. We used the CloudIQ engine coded in such a way that if we launched the client multiple times it would distribute a task to another fabric worker. When the work was done, we copied the results over to a single EBS volume attached to the first instance. To access the files in the storage and control the storage process, we could use the 'curl' command to send http requests to do things like delete, deploy, get, put, stop and some other things.

There are three different types of programs installed onto a fabric: a fabric application that's a batch processing application or computing application, a service such as Tomcat, Weblogic, or Apache, or a package such as Java Development Kit (JDK), Ruby, RPM, or command line installation like "yum install".

Appistry is a sophisticated construction set for distributed cloud computing, but generally for more persistent applications. Its monitoring and reporting infrastructure relies on mostly external tools, when compared to the instance monitoring capabilities of RightScale and Tap In Systems Control Plan.

Appistry can use a variety of code that can be linked in with the Appistry APIs to produce a distributed system (or set of systems) if you're adept at coding the project, and Appistry's success is fully dependent on lots of custom coding. The results, however, could be very useful. But first, you need to get thru the 1,400 pages of documentation. Fortunately, paid customers get dedicated systems engineering help, and there's available architectural support as well.

Henderson is managing director and Brendan Allen is a researcher for ExtremeLabs, of Bloomington, Ind. Henderson can be reached at thenderson@extremelabs.com.

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