For the last few months we have been working towards adding cloud providers to the Product Availability Matrix (PAM). This project is known internally as Cloud Phase 1 and has proven to be, on the whole, a DevOps project. DevOps For us to add support for a platform there are several things that we must do - the most important of which is to test it, on every platform, for every build, to make sure it works. The framework we use to test Uniface is a custom-built application with the imaginative name of RT (Regression Test) and contains tests targeted at proving the Uniface functionality. The tests have been built up or added to as new functionality is added, enhanced or maintained. Up until the cloud project, the process of building and testing Uniface (and this is a very simplistic description) was to:

  • Create a Uniface installation by collecting the compiled objects from various build output locations (we have both 3GL and Uniface Script)
  • Compile the RT application and tests using the newly created version
  • Run the test suite
  • Analyze the output for failures and if successful
    • Create the installable distribution (E-Dist or Patch)

The testing and building was completed on pre-configured (virtual) machines with databases and other 3rd party applications already installed. To add a new platform (or versions of existing platform) to our support matrix could mean manually creating a whole new machine, from scratch, that represents the new platform. To extend support onto cloud platforms, we have some new dimensions to consider

  • The test platform needs to be decoupled from the build machine as we need build in-house and test in the cloud
  • Tests need to run on the same platform (i.e. CentOS) but in different providers (Azure, AWS, …)
  • Support for constantly updating Relational Database Service (RDS) type databases needs to be added
  • The environment needs to be scalable with the ability to run multiple test runs in parallel
  • It has to be easily maintainable

As we are going to be supporting the platforms on various cloud providers, we decided to use DevOps methodologies and the tools most common for this type of work. The process, for each provider and platform, now looks like this:

  • Template machine images are created at regular intervals using Packer. Ansible is used to script the installation of the base packages that are always required
  • Test pipelines are controlled using Jenkins
  • Machine instances (based on the pre-created packer image) and other cloud resources (like networks and storage) are created and destroyed using Terraform
  • Ansible is used to install Uniface from the distribution media and, if needed, overlay the patch we are testing
  • The RT application is installed using rsync and Ansible
  • RT is then executed one test suite at a time with Ansible dynamically configuring the environment
  • Docker containers are used to make available any 3rd party software and services we need for individual tests and they are only started if the current test needs them. Examples of containers we have made available to the test framework are mail server, proxy server, webserver and LDAP server
  • Assets such as log files are returned to the Jenkins server from the cloud based virtual machine using rsync
  • The results from Jenkins and the cloud tests are combined along with the results from our standard internal test run to give an overview of all the test results.

As quite large chunks of the processing are executed repeatedly (e.g. configure and run a test) we have grouped the steps together and wrapped them with make. As most of the platforms go through the same process we have also been able to parameterize each step. This should mean that a new platform or database to test on, after the distribution becomes available, “could” be a simple as adding a new configuration file. The result of Phase 1 of the Cloud project is that the Product Availability Matrix has been extended to include new platforms and databases. Internally we also have the benefit of having a much more scalable and extendable testing framework. The new platforms added to the PAM in 9.7.04 and 10.2.02 by the cloud project: Uniface Deployment-in-Cloud In this initial phase, we have been concentrating on the Linux platforms; next (in Phase 2) we will be working on Windows and MS SQL server. During this process, I have learnt a lot about our test framework and the tests it runs. Much of the work we have undertaken has just been a case of lifting what we already have and scripting its execution. This has not been the case for everything, there have been some challenges. An example of something that has been more complex than expected is testing LDAP. The existing environment would use a single installation of LDAP for every platform being tested. Tests would connect to this server and use it to check the functionality. As the tests are for both read and write, we could only allow one test to be active at a time; other tests and platforms would have to wait until the LDAP server was released and become available before continuing. With the cloud framework, we have an isolated instance of the service for each test that needs it. The project to bring cloud support to Uniface has been an interesting one. As well as allowing us to add new platforms and providers onto our supported matrix, it has also allowed us to be more scalable and flexible when testing Uniface.  

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