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Natural Language Processing is a specialized subdomain of Machine Learning which is generally concerned with the interactions between the human and machine using a human verbal or written language.
NLP helps in processing huge volumes of text which would take a significant amount of time for a human to comprehend and process otherwise. Hence a lot of organizations take advantage of NLP to gain useful insights out of their text and free formatted data.
Change management is another example of an ITIL-based process which can be significantly improved by the application of DevOps practices. Change management is often implemented in ways which fly in the face of key principles of DevOps. Traditional implementations put multiple layers of approval in place for every change, inserting significant bureaucracy and gates which almost guarantee longer release cycles and delays in getting value to the customer. This fundamentally contradicts the DevOps emphasis of short release cycles and the rapid delivery of value to customers.
However, there can be little argument that tracking changes in a technical environment can be highly valuable. Especially in large environments where many different changes are occurring at the same time, it is critical to have visibility into what is changing and how those changes might impact one another and, ultimately, the end customer. By bringing DevOps principles to bear on change management we can ensure we are tracking and managing changes while enabling speed and agility.
It is not true that ITIL disallows innovation and that DevOps and IT Service Management (ITSM) and the IT Infrastructure Library (ITIL) are like oil and water. ITIL is a framework from which you can take or leave portions you like and, in fact, this framework provides many useful paradigms for DevOps implementations.
There’s actually lots in common between ITIL and DevOps. ITIL is a set of detailed practices which provides a set of process frameworks. DevOps is primarily a culture of collaboration so there is no reason you cannot have a process framework integrate very well with a culture of collaboration.
Continuous delivery is the ability to get changes into a software solution, into production, or into the hands of users, safely and quickly in a sustainable way. Think of new features, configurations, bug fixes and tweaks to existing programming. The benefit of this approach can mean immediate fixes to problems that previously sat for months in the traditional waterfall approach. Ultimately, continuous delivery (CD) approaches to development can mean high-performance teams can consistently deliver services faster and more reliably.
In previous approaches, typically the waterfall models, release management involves the planning, scheduling and controlling software delivery throughout the cycle. Now, continuous delivery changes this entire model. Through the approach, organizations are able to be more responsive and agile to manage these quicker development terms. Essentially, software development has become an always-on product like most of the other consumer ventures we participate in.