The recent 2016 State of IT Report from Spiceworks reveals that IT budgets either are not increasing or are barely increasing from what they were in 2015. This has IT execs worried about how they will do more with less, not to mention helping the business drive top-line growth.
What helps make up 21st century data centers? In my last article, I focused on the automation aspect of the modern-day data center. My main point was that there is no right or wrong answer when it comes to choosing which automation engine to use in your environment. There are plenty of options available, and you should make your decision based on which solution makes the most sense for your environment and the systems that are running on it. You should also take advantage of other automation tools or engines that may be provided as part of another solution. Native functionality that is vendor-provided is a gift that should be opened and taken advantage of. Continue reading Tools of the 21st Century Data Centers
The world of cloud is changing yet again. IBM announced recently that it is acquiring Austin, Texas–based Gravitant. Financial details of the deal were not released.
Automation has evolved from its humble beginnings as a local basic scheduler kicking off scripts and tasks into an enterprise-level tool used in most, if not all, of the unique silos that encompass corporate IT. In this article, I focus on some of the different kinds of automation engines that are in use. This post will not even begin to touch on all of the different products and solutions that are out there, and I certainly won’t claim that there is any one right way or tool. However, I would like to go on record to say that, in my humble opinion, there is one primary wrong answer with automation, and that wrong answer is to be completely dependent on any one solution or product itself.
Steve Flanders (@smflanders) and I had a late-night Twitter conversation over the complexities inherent in cloud-native applications. My take was that we need to broaden our view and see the entire picture before we can delve into the weeds. Steve’s was that we need DevOps. I countered by saying we need better communication. In essence, we may have been saying the same thing, but we were on different planets, which led to a useful analogy. During the race to the moon, who were the systems engineers, the ones who saw the big picture of a program with well over 15 million moving parts, not to say people, involved?
Difficulty and complexity are two things human beings tend to avoid. For the most part, people seem to be much happier with concepts that are easy on the brain, take little time to implement, and have the promise of immediate return on investment. This tendency gives rise to quick fixes that are simple and low-cost. The problem with most of these approaches applied to transformation is that transformation does not come with speed or simplicity. I know many organizations that wish it did! It would make it so much easier in my consulting practice, and it would provide services to organizations making transformational changes. Unfortunately, it just doesn’t work out that way.