cloudify

Recently, Microsoft released a new feature for the Azure platform allowing users to launch both Windows and Linux virtual machines. As part of this, a set of new APIs are now available for developers who want to interact with the Azure IaaS platform ... [More] programmatically. This is pretty exciting, Microsoft has entered the world of IaaS and is now offering users much more freedom in their deployments than they used to. We at Cloudify decided to use these APIs to implement a new cloud driver to allow for easy deployment of any application to Azure. (See the source at: Cloudify Azure REST Client) This implementation unifies the Microsoft Azure experience in Cloudify with all of our other supported IaaS providers to enable a seamless transition between providers. Let me give you an example: First we need to launch Cloudify management agent. This will require some Azure account credentials configurations. Then, we execute the command: Once these commands are complete, you will have a fully running Tomcat web server connected to a Cassandra DB on the Azure infrastructure. We also provide our own UI management console that provides you with a broader look at your services and applications, including service metric monitoring and logs. (You can access this via the link provided in the shell once bootstrapping is complete). Notice there are 3 VMs in the Azure console, one for the Cloudify management components, one for tomcat, and one for Cassandra.    So, apart from the initial configuration which may take a few minutes, there is really nothing more to do, just use the shell to install, monitor, and uninstall any service or application you desire. The Azure API REST protocol requires you to have an intimate familiarity with a lot of XML-based API calls. These XMLs are not trivial and can get pretty complex, thus requiring you to spend some time and learn how to use them correctly. By using Cloudify you can sidestep this issue (and many more), not spend any time or money on stuff you, for the most part, don’t really care about and just focus on the business logic of your application. We will take care of the REST (pun intended J). [Less]

Following our previous post with a preview of our latest WebSphere recipe - here’s a video tutorial for how to actually get it up and running on any cloud. You can also check out this dedicated blog post - Using WebSphere’s wsadmin tool on any Cloud - to learn even more.

Your Apps on the Cloud - What it really takes from Uri Cohen

I would like to introduce the “locationAware” service recipe flag which enhances the behavior of machine failover and scaling rules: 1. When a machine fails, and “locationAware” is enabled, Cloudify starts the machine in the same location of the ... [More] failed machine. 2. Scaling rules are separately enforced on each location. Effectively, Cloudify starts a new machine in the location that triggered the scale-out rule. In the example below, we assume we have 2 Tomcat web servers deployed on each location (a total of 4 web servers): https://gist.github.com/4000673 Notice that each Web Server CPU load is 40%: https://gist.github.com/4001155 One scenario is network disconnection between the load balancer and the Tomcat Servers in “Location 1”. We assume the Load Balancer directs all traffic to “Location 2”. The result is that 2 Web Servers are handling all of the traffic which results with an increase of the CPU load up to 80%. https://gist.github.com/4000676 The high CPU load triggers a scaling rule which starts another web server virtual machine. Since the recipe is location-aware, the virtual machine is started at “Location 2” (and not Location 1 which is now disconnected from the load balancer). Notice how the CPU load is then down to normal values: https://gist.github.com/4000947 When the Location 1 network failure is fixed, we have one server too many. https://gist.github.com/4001033 The scaling rules detect that since the CPU usage is too low (meaning we can handle this load with less machines), the extra machine is then removed. https://gist.github.com/4000673 [Less]

Event Recording: Cloudify for IBM InfoSphere BigInsights- The Elephant in the Cloud at IBM Information on Demand The massive computing and storage resources that are needed to support big data deployments in general, and Hadoop in particular, make ... [More] cloud environments, public and private, an ideal fit.    Managing your big data app, however, is no walk in the park - especially when considering the fact that these systems and application stacks often include other services beyond Hadoop such as: relational databases, other NoSQL databases and more, where each framework comes with its own management, installation, configuration, and scaling solutions.  This is where Cloudify fits in.  Cloudify provides consistent management that makes the provisioning, deployment, and scaling of your Hadoop system simple and consistent with the rest of your stack.  What’s more, it enables cloud portability between bare-metal and public cloud offering for Hadoop/BigInsights making it possible to run your system on the right cloud for the job—public/virtualized environment for on-demand workloads and bare-metal for I/O intensive operations. [Less]

With our new WebSphere recipe you can now install WebSphere on any cloud. It configures WebSphere and also installs two WebSphere sample applications (we used Plants and AlbumCatalog).   Find it in the Cloudify Recipe Repo on GitHub, and play around a little.

This recipe enables users to install MySQL on any cloud in two modes: standalone and master-slave. In addition, after installing the MySQL service you can then take advantage of Cloudify’s custom commands mechanism in order to manipulate the data and ... [More] even modify the database structure. Tamir Korem, Cloud Evangelist, will present in this video how to install this service on EC2, and then invoke several custom commands on the newly installed database. You can inherit and extend this recipe very easily, just by changing the mysql-service.properties file, without changing even one line of code in the recipe. Feel free to try this at home! [Less]

Using BYON (Bring Your Own Node) - You don’t have to set up a private or public cloud, just take several machines and let Cloudify manage them. Have a look at this code snippet - what you see here is an example of how to configure your machines, as if they are cloud nodes. Yup! it’s just that easy… https://gist.github.com/2709727

@natishalom and @katsnelson’s presentation at #IBMIOD The Elephant in the Cloud: Bring True Cloud Economics to Hadoop/BigInsights from Nati Shalom

Cloudify at the Open Source China Meetup in Hangzhou