DevOps: It's a cultural change that starts with collaboration between people.
I bet you have heard this many times. The statement is absolutely true, but the DevOps journey doesn't necessarily begin from collaboration. In fact, there is no single recipe of success. That's the beauty of it -- everyone can make a difference from wherever they are. For any enterprise level transformation, Change Management and COE are critical concepts that can allow different business units and teams to benefit from "economies of scale" and "economies of learning". DevOps journey is no different, however, there are two interesting components that can make this journey easier and much more fun: "Standardization" and "Automation".
Standardization: Variety is the enemy of stability, and hence has an adversarial relationship with Operations. Variety means too many variables, and every variable in turn comes with its own set of dependencies. The less the variety, the fewer variables, resulting in a decrease in risk associated with fast paced changes coming down the conveyer belt. Standardizing technology, architecture, tools, and processes has tremendous impact; it not only reduces risk but also paves the path for extreme Automation. Cloud Manager Platforms are a perfect example of how they use policy based pre-defined blueprints to establish standards across teams. They minimize the variables involved and help enforce a standard.
Automation: Most Analysts credit automation as the critical ingredient for DevOps success. It's clear that manual labor is not only slow, but also error prone because of the human capital involved. Quality issues and longer release cycles are common issues attached to manual labor. Automation has obvious benefits around improved quality and time to market. There’s a reason why you hear numerous “continuous” terms such as continuous build, continuous integration, continuous validation, and continuous delivery. Automation encapsulates every possible manual step, which can be automated - including automation of environment, releases, testing, code promotion, and even the feedback loop.
Double down on Automation: The problem with automation is that it still requires manual labor i.e. the process of automation itself is Manual. For example, manually automating test cases is also slow and error prone -- automating regression tests can take weeks and/or months and still results in questionable coverage. In this era of self-driving cars and fast-paced feedback loops, automating the automation is not a far-fetched goal. In fact, DevOps data mining uses the feedback look to auto-generate regression baselines, which not only shrinks months to weeks and days, but also keeps your test coverage close to 100% at all times.
Has Standardization or Automation enabled you to gain speed in your DevOps initiative? Have you tried doubling down on automation? Are you interested in telling others about it? You could have the opportunity to speak at CA World with a sponsored event registration!