Web Ops (web operations) is one of the most prominent domains within information technology systems management, and essentially involves the “deployment, operation, maintenance, tuning, and repair of web-based applications and systems” (according to Google). As you may expect, web ops is a foundational function of computer systems and machines that has become more and more popular over the years, constantly gaining traction to become bolder and stronger all the time (think the introduction of the Pantheon’s WebOps Platform, or the steady evolution into movements in artificial intelligence and machine learning, for instance). Now, the most popular innovation in web ops is its expansion into machine learning capabilities and continuous advancement and growth. It is a motion that has really popped in recent months, and it is already showing immense promise, even in its relatively early stages.
It goes without saying that computers have assisted us in successfully exceeding our own expectations regarding what is possible. In just about every way that matters, computers have fundamentally changed how we learn about, see, and even take part in the world. Thanks to computers, we have more of a well-rounded understanding of the world around us, and that understanding only continues to become more and more pronounced all the time. A new twist in web ops has arrived, and it has brought with it an incredibly profound sense of hope and promise about what is to come in the next few years, and beyond, in terms of web operations and computer advancements. That twist comes in the form of continuous advancement in AI, and more specifically, machine learning. While web ops’ goal is to stay on top of web-based innovation, structuring, maintenance, and advancement, machine learning operations would take all those constructs and work towards elevating them to smarter and stronger standards.
Understanding machine learning is the first step in utilising it properly. In short, machine learning essentially uses statistical techniques to give computers the capability to learn (i.e. through the use of data to progressively enhance performance on a set task, without having to be specifically programmed to accomplish said feat). Machine learning operations, to delve further, is all about taking operations and making them smarter overall. Like software, machine learning improves over time, through ongoing advancement and production releases. Over time, as those releases are brought to the world, the machine learning ops take on further aspects and components of all operations, making them more convenient and efficient to not only oversee, but to innovate and update as time goes on. Web ops is fantastic, of course, but the inclusion of machine learning operations means that it will operate at a much higher rate of efficiency and transparency.
The reality is that, if all continues in this general positive direction, machine learning operations are going to easily innovate and transpire into widespread use, both at the personal level and through business and empires of all shapes and sizes, and across all industries. Web ops are all about ensuring that web-based systems run effectively and in due course, and one of the most exciting potential applications of machine learning operations, lies in its collaboration with web operations to make web-based devices and systems even more convenient and efficient than they are now. The power of machine learning capabilities rests in their potential and subsequent likelihood of taking exciting systems and innovations, and making them even bigger and better. If the point of web ops is to transform the way we experience web-based technologies, then the point of machine learning ops is to take those experiences and elevate them to the highest possible concentration, again and again. Together, the two will likely function and thrive to all-new heights. Machine learning ops have only just begun to strap the surface in terms of capability going forward, and it is an incredibly exciting time to watch unfold.
Web ops is without a doubt one of the most instrumental components in most (if not all) computers and other devices. Forming the foundational support system for “deployment, operation, maintenance, tuning, and repair of web-based applications and systems”, web ops is a necessary construct that helps computers and other web-based devices to function and thrive at their peak. Over the years, web ops have steadily but surely become an immensely popular notion, and today it is a necessary function for all web-based devices. And now, web ops are getting an intelligent revitalisation, in the form of machine learning capability. While still relatively fresh in terms of being a mainstream construct, machine learning ops seek to make web ops, and other device-based operations, smarter, bolder, stronger, and more capable all round. There is much promise for this innovation going forward, and it is likely that the best is yet to come.