Management, Leadership, Continuous Improvement, and DevOps

There is a management aphorism that “If you can’t measure it, you can’t manage it.” That gets attributed to Peter Drucker, though it is not actually what he said. What he said was “If you can’t measure it, you can’t IMPROVE it”. That’s an important difference as we talk about bringing DevOps and its related practices and disciplines to enterprises.

If you think about it, measuring with an intent to improve something is a much more challenging statement. Management of something is usually about keeping it within known parameters – maintaining a certain status quo. That is not to imply that Management is not valuable – it is absolutely crucial in maintaining a level of rigor to what is going on. But Improvement deliberately pressures the status quo to redefine the status quo at a new point. In fact, redefining a status quo to a better state sounds an awful lot like what we talk about in the DevOps movement.

Improvement always sounds very cool, but there is also an icky truth about Improvement – it is a relative thing. There are no easy answers for questions like:

  • ‘What point are we improving to?’
  • ‘How do we know when we have improved enough for a while in one area?’
  • ‘What is the acceptable rate of progress toward the improved state?’
  • and so on…

Those must be answered carefully and the answers must be related to each other. Answering those questions requires something different from Management. It requires Leadership to provide a vision. That brings us to another famous Drucker quote: “Management is doing things right; leadership is doing the right things.”

That quote is a sharp observation, but it does not really judge one as ‘better’ than the other. Leadership is exciting and tends to be much more inspirational at the human level. It therefore usually gets more attention in transitional efforts. However, without the balance of Management, Leadership may not be a sustainable thing in a business situation.

In terms of DevOps and the discipline of Continuous Improvement, the balance of these two things can be articulated with relative clarity. Leadership provides the answers for the hard questions. Management provides the rigor and discipline to maintain steady progress toward the new status quo defined by those answers. Put more simply, Leadership sets forth the goals and Management makes sure we get to those goals.

There is a certain bias in DevOps where we value Leadership – the desire to set and pursue improvement of our daily tech grind. Maybe that is because DevOps is an emergent area that requires a certain fortitude and focus on the doing the right things to get it started. And Leadership is certainly good for that. However, I also work with organizations where the well-intended, but unfocused, efforts of leadership-minded people lead to chaos. And those DevOps ‘transformations’ tend to flounder and even make things worse for the people involved. Which is not very DevOps at all.

I have seen enough of these that I have been spending time lately trying to organize my thoughts on the balance point. In the meantime, a piece of advice when you want to pursue a great idea / innovation – figure out how you want to answer the hard questions so you can make them stick in your organization and truly reap the benefit of that idea. Then, you can get on to the next one, and the next one, and the next one – to achieve the steady improvement of your status quo that is near the heart of DevOps culture.

This article is also on LinkedIn here: https://www.linkedin.com/pulse/management-leadership-continuous-improvement-devops-dan-zentgraf

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Predictability is Predictably Hard

In order to successfully automate something, the pieces being automated have to be ‘predictable’. I use ‘predictable’ here – rather than ‘consistent’ – deliberately. A ‘predictable’ environment means you can anticipate its state and configuration. ‘Consistent’ gets misconstrued as ‘unchanging’, which is the opposite of what Agile software delivery is trying to achieve.

Consider deploying a fresh build of an application into a test environment. If you cannot predict what the build being deployed looks like and how the environment will be set up, why would you expect to reliably be able to get that build working in that environment in a predictable window of time? And yet, that is exactly what so many teams do.

The proposed solution is usually to automate the deployment. That, however, leads to its own problems if you do not address the predictability of the underlying stuff being automated. I talk to teams with stories about how they abandoned automation because it ‘slowed things down’ or ‘just did not work’. That leads teams to say, and in some cases believe, that their applications are ‘too complex to deploy automatically’.

At the heart of achieving predictability of the code packages and environments is the fact that they are different teams. Somehow it is harder to collaborate with the developers or operations team than it is to spend months attempting to build a mountain of hard to maintain deployment code. A mountain of code that stands a good chance of being abandoned, by the way. That represents months of wasted time, effort, and life because people working on the same application do not collaborate or cooperate.

And we get another example of why so many DevOps conversations become about culture rather than technology… Which really sucks, because that example is at the expense of a fair bit of pain from the real people on those teams.

The lesson here is that there is no skipping the hard work of establishing predictability in the packaging of the code and environments before charging into automating deployments. We are in an era now where really good packaging and configuration management tools are very mature.
And the next generation of tools that unifies the code and environment changes into immutable, deployable, and promotable artifacts is coming fast. But even with the all of these awesome tools, cross-disciplinary experts will have to come together to contribute to the creation of predictable versions of those artifacts.

The ‘C’ in CAMS stands for “Collaboration”. There are no shortcuts.

This article is also on LinkedIn here: https://www.linkedin.com/pulse/predictability-predictably-hard-dan-zentgraf/

Old Habits Make DevOps Transformation Hard

My father is a computer guy. Mainframes and all of the technologies that were cool a few decades ago. I have early memories of playing with fascinating electro-mechanical stuff at Dad’s office and its datacenter. Printers, plotters, and their last remaining card punch machine in a back corner. Crazy cool stuff for a kid if you have ever seen that gear in action. There’s all kinds of noise and things zipping around.

Now the interesting thing about talking to Dad is that he is seriously geeky about tech. Always fascinated by the future of how tech would be applied and he completely groks the principals and potentials of new technology even if he does not really get the specific implementations. Recently he had a problem printing from his iPhone. He had set it up a long time ago and it worked great. He’s 78 and didn’t bat an eye at connecting his newfangled mobile device to his printer. What was interesting was his behavior when the connection stopped working. He tried mightily to fix the connection definition rather than deleting the configuration and simply recreating it with the wizard. That got me thinking about “fix it” behavior and troubleshooting behavior in IT.

My dad, as an old IT guy, had long experience and training that you fix things when they got out of whack. You certainly didn’t expect to delete a printer definition back in the day – you would edit the file, you would test it, and you would fiddle with it until you got the thing working again. After all, you had just the relatively few pieces of equipment in the datacenter and offices. That makes no sense in a situation where you can simply blow the problematic thing away and let the software automatically recreate it.

And that made me think about DevOps transformations in the enterprise.

I run into so many IT shops where people far younger than my dad struggle mightily to troubleshoot and fix things that could (or should) be easily recreated. To be fair – some troubleshooting is valuable and educational, but a lot is over routine stuff that is either well known, industry standard, or just plain basic. Why isn’t that stuff in an automated configuration management system? Or a VM snapshot? Or a container? Heck – why isn’t it in the Wiki, at least?! And the funny thing is that these shops are using virtualization and cloud technologies already, but treat the virtual artifacts the same way as they did the long-lasting, physical equipment-centric setups of generations past. And that is why so many DevOps conversations come back to culture. Or perhaps ‘habit’ is a better term in this case.

Breaking habits is hard, but we must if we are to move forward. When the old ways do not work for a retired IT guy, you really have to think about why anyone still believes they work in a current technology environment.

This article is on LinkedIn here: https://www.linkedin.com/pulse/old-habits-make-devops-transformation-hard-dan-zentgraf