When people talk about "automation" with ALM, are they talking about the integration of different tools or are they talking about generating output automatically? And if it's generation, do they mean generating reports, code or test cases?
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Hannah Smalltree, Editorial Director
In my experience, ALM automation runs the gamut and is defined by an individual organization’s ALM processes, but most often I find that when people talk about "ALM automation," they are referring to integration. Historically, companies invest in ALM automation by purchasing tools to address what they consider to be the most critical aspects of their ALM strategy, and then make an effort to mesh this specialized tool work with the rest of the process. For some organizations, the main focus is on managing the application portfolio or individual development projects. The latest wave of Agile project management tools is a good example of this activity. Others have invested in requirements management, build tools and testing solutions to address delivery problems such as poor quality and systems that don’t meet business needs. And others have invested in IDEs to assist with the development and change of application code, while still others have gone on to leverage DSLs and model-driven development environments to help improve their application lifecycle efficiency. However, the big challenge for automation, and where a lot of the talk comes from, is about how to get all of these individual investments to work together.
Looking ahead, I expect this integration problem to become exacerbated as IT shops embrace cloud
computing. Cloud computing impacts several stages of the application lifecycle, including
development, testing and deployment, and this will quickly test legacy ALM tools and open the door
for a new wave of tightly integrated ALM offerings that provide what I think of as "cloud-ready"
ALM platforms. Organizations wanting to update their ALM tool suites should look for modern ALM platforms
that address the main integration problems and are able to match the efficiency of the cloud. In
addition, these new tools must offer the flexibility to operate both on premise and in the cloud.
These new cloud-ready ALM platforms should cover as much of the ALM landscape as possible to
deliver the efficiency in your ALM processes that matches the efficiency you will get from having a
scalable, on-demand computing infrastructure.
This was first published in February 2011