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Repetition is the Key to Network Automation Success

Test Early, Test Often for Data Centre’s Muscle Memory

Training your data center “muscle memory” will ensure that when the pressure is on your network will make all the right moves.


If you’ve ever taken dancing lessons – or musical lessons – or tried to teach yourself to type you know that repetition is the key to success. Or as your mom would tell you, “practice makes perfect.” The reason repetition is a key factor in the success of endeavors that require specific movements in a precisely orchestrated fashion is that it builds what instructors call “muscle memory.” You’re actually teaching your muscles to react to a thought or movement automatically. Once you’ve repeated the same movement over and over it becomes second nature, like a Pavlovian response.

To achieve the efficiencies associated with network automation you’ve got to build the data center’s “muscle memory”, as it were. You can’t jump from no automation to full automation in one day, just as you can’t go from the basic steps of a waltz to flying around the floor like a seasoned pro. It takes time and repetition.

Application developers may recognize this approach as an iterative, or agile one, with the key mantra being “test early, test often.”


First, start by identifying two or three key tasks in an operation process and automate each of them individually. Test them (this is the practice part, by the way). Then tie them together and test again. And again. And again. Once you’re comfortable with the basic steps you can move on to adding one step at a time – always practicing the individual step first (automation) and then again as part of the operational orchestration.

As you continue to add to the orchestration through new individual steps you might start to see patterns emerging or redundant steps. This is one of the ways in which you can squeeze more efficiencies out of this new paradigm: streamline operational processes. Eliminate redundancies and, if patterns occur, abstract them into reusable operational tasks that can be leveraged across multiple orchestrations.

As you’re practicing (because you are testing and retesting, right?) and getting more proficient in the data center orchestration dance you’ll be able to start weaving together those patterns in different ways. You might find that step “a” leads more naturally into step “c” for you and, given performance data collected during practice it might even execute faster. If that’s the case, change the order around and … yes, test it again. Being light on your feet (agile) means the ability to change steps around quickly – but not at the cost of introducing errors, hence the need to practice whenever any individual step changes or the order in which steps are orchestration is modified.


It is through automation and orchestration that a data center realizes the operational efficiencies associated with cloud computing and, to a lesser extent one of its key enabling technologies, virtualization. But that automation and orchestration requires a commitment to consistently practice (test) and refine those operational processes until they can execute in your sleep. Because that is one of the goals, after all: you can sleep at night without worrying about the availability or performance of applications being delivered over your network because your new network knows the right steps to take at the right time.

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More Stories By Lori MacVittie

Lori MacVittie is responsible for education and evangelism of application services available across F5’s entire product suite. Her role includes authorship of technical materials and participation in a number of community-based forums and industry standards organizations, among other efforts. MacVittie has extensive programming experience as an application architect, as well as network and systems development and administration expertise. Prior to joining F5, MacVittie was an award-winning Senior Technology Editor at Network Computing Magazine, where she conducted product research and evaluation focused on integration with application and network architectures, and authored articles on a variety of topics aimed at IT professionals. Her most recent area of focus included SOA-related products and architectures. She holds a B.S. in Information and Computing Science from the University of Wisconsin at Green Bay, and an M.S. in Computer Science from Nova Southeastern University.