<div id="readability-page-1"><div>Field CTO for the Americas at Infinidat. 
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Simplicity is a path to improved productivity, but it is a road less traveled for far too many IT-related companies. Over the years, tech companies have been notorious for giving their users ever-increasing complexity instead of incrementally greater simplicity. In this decade of user experience, complexity will not be tolerated the way it has in the past. And this applies to the data storage industry as much as any other area of the IT field. 
Complexity raises the risk of human error, wastes people’s time and prevents users from focusing on their other priorities. Technology should enable business operational efficiency, continuity and growth, not keep staff busy for the sake of being busy. 
 
Even something as common as a physical storage hardware upgrade to an existing system introduces unnecessary complexity and can be avoided with more modern seamless approaches when adding capacity. 
 
If you have fewer things that require management, you have more time to devote to more important tasks. Simplicity can also reduce or eliminate potential problems from human error associated with manual management activities. 
 
But to take this road to simplicity, a tech company needs to start with a core philosophy that provides the discipline to be user-centric, committed to a modern, lean approach, and to navigate the challenges and pitfalls along the way. This is where the architecture of the IT solution gets tested for flexibility and foresight. Nevertheless, the real reason IT solutions get so complex may seem “harmless” at first glance, but it is actually part of a vicious cycle that repeats itself. 
Feature Creep Drives Complexity 
IT management complexity often comes from what I’ll call “feature creep.” As users become familiar with technology, they see what it can do, and their always-increasing experience also exposes feature gaps and limitations for other features and functionality that they would like.  
As new features are then introduced, any features that were not originally planned and expected when a technology was first developed were also never part of any planned management of the overall system. The management of those new features may not only be inconsistent with existing management capabilities but also incompatible with them, requiring independent additional management tools, thereby creating more complexity. 
Eventually, new management capabilities are created to simplify or abstract the management of the new features and things get a bit easier — until yet another new feature comes along and it all starts over again.  
The Answer To Being Simple Is Simple 
The crux of the answer (or antidote) to the “feature creep” is analogous to the doctor’s response in the classic joke about a patient saying, “Doctor, please help me. It hurts when I do this,” to which the doctor replies, “Then stop doing that!” 
The key to IT management simplicity is not doing things. Instead, have the system do things for you so that you no longer need to do them manually at all. Unfortunately, over the history of the IT industry, the more common practice has been to constantly try to find ways to make manual management by people easier and easier, such as graphical user interfaces (GUIs) versus command line interfaces (CLIs) and drop-down menu item selection instead of text entry. These things help, but they can never fully solve the bigger problem. 
The answer is to use intelligent software to do things automatically as if a really smart person had done them manually. The common overarching term for this, of course, is artificial intelligence (AI). But just as things can change in a system, good software needs to be able to adapt to those changes in real time. That requires a direct subset of AI called machine learning (ML), where the system itself can interpret new information and make a new (good) decision without external human direction.  
The ultimate effectiveness can be achieved if a system can employ that rarely seen subset of machine learning known as deep learning (DL). Deep learning is the ability of a system to continuously interpret and evaluate multiple potential options for how to act and then learn from continuously evaluating their relative successes to guide future actions. Developing true deep learning requires much more effort and creativity from really smart people to design it, but the potential effectiveness for the systems and people who will use it is massively greater. 
The right approach is to bring the “set it and forget it” mentality to IT management. There are many different areas of IT that can benefit from greater simplicity through intelligent software, such as performance management, capacity planning, predictive maintenance and resource utilization. 
But only those companies that “get it” and have implemented technologies that intelligently use software to eliminate the need for extensive human involvement will have the potential to give you those kinds of benefits.  
It’s that simple. 
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Simplicity is a path to improved productivity, but it is a road less traveled for far too many IT-related companies.

理事會帖子: IT 基礎架構管理: 應該很簡單