Topics In Demand
Notification
New

No notification found.

301

0

The use of AI and machine learning is growing rapidly as businesses go through digital transformation. Models and data flow to become more challenging to manage as they become more complicated. The fact that MLOps and AIOps are still fairly new fields of study presents another difficulty.

Organizations throughout the world are increasingly looking to automation technologies as a means of improving operational efficiency. This indicates that tech leaders are becoming more and more interested in MLOps and AIOps.

While MLOps and AIOps are quite separate disciplines involving various technologies and procedures, both machine learning and artificial intelligence play a significant role in aiding businesses in achieving operational efficiency. Most importantly, they accomplish distinct objectives.

By automating incident management and machine monitoring using machine learning, AIOps improve the effectiveness of IT operations. Putting ML models into production is known as MLOps. To put models into production more quickly it makes it simpler to bridge the gap between data operations and infrastructure teams. MLOps doesn’t specifically refer to an ML capability, in contrast to AIOps.

In other words, MLOps standardizes processes whereas AIOps automates machines.There are parallels in the teams and abilities needed to properly execute AIOps and MLOps, despite the obvious distinctions. It is worthwhile to consider where they intersect before focusing on one or the other to determine which resources can support both disciplines. For instance, both the MLOps and AIOps processes can be sped up with a comprehensive ModelOps platform that has ready-to-deploy models.

Sources:


That the contents of third-party articles/blogs published here on the website, and the interpretation of all information in the article/blogs such as data, maps, numbers, opinions etc. displayed in the article/blogs and views or the opinions expressed within the content are solely of the author's; and do not reflect the opinions and beliefs of NASSCOM or its affiliates in any manner. NASSCOM does not take any liability w.r.t. content in any manner and will not be liable in any manner whatsoever for any kind of liability arising out of any act, error or omission. The contents of third-party article/blogs published, are provided solely as convenience; and the presence of these articles/blogs should not, under any circumstances, be considered as an endorsement of the contents by NASSCOM in any manner; and if you chose to access these articles/blogs , you do so at your own risk.


Current Focus Areas: IT Services, AIOps, 5G, Cloud, Project Management. Also specialises in Application Rationalization, Cost Optimization, Benchmarking, Report writing, and Market Research.

© Copyright nasscom. All Rights Reserved.