Authors :
Naveen Vemuri; Naresh Thaneeru; Venkata Manoj Tatikonda
Volume/Issue :
Volume 9 - 2024, Issue 2 - February
Google Scholar :
http://tinyurl.com/4yzvwctb
Scribd :
http://tinyurl.com/35k9xfwj
DOI :
https://doi.org/10.5281/zenodo.10673085
Abstract :
This research pays attention to the merging of
Development Operations with Artificial Intelligence (AI).
It starts by realizing that AI will be an important factor in
many aspects of work and that it will be automating some
job functions. Consequently, AI will be presented as a tool
that will enhance knowledge acquisition, provide job
performance and professional development. The story
stresses the opportunity cost attributed to the shift from
software licensing to Software as a Service (SaaS) and
underscores the benefits gained through early and regular
software release by the organizations which have adopted
the practice. DevOps, as a revolutionary approach, seeks
to eliminate the gaps in the two central processes namely
development and operations. The technology emerging,
which includes big data, cloud computing, and mobile
internet, calls for quick software deployment and
consequently, the DevOps approach is what you get.
However, DevOps is a unified approach. In the abstract, it
will talk about continuous integration (CI) and continuous
delivery (CD) spotting the cost-effectiveness and role of
automation in the production process. Through AI and
DevOps described, air is evident which is the AI role in
automation and troubleshooting development in the
software and hardware field. In the paragraph the author
puts forth AI-optimized DevOps as a proposal that is not
only efficient in development and distribution process but
also fast in pacing. The overall wrap-up summarizes the
AIOps and MLOps applications in conjunction with
DevOps workflow to eliminate disconnection between
machine learning model development and operational
deployment. The big picture actually is condensed at the
end. It outlines exactly how the AI DevOps approach
works in modern software development, with particular
focus on the cloud CI/ CD platform.
Keywords :
AI-Optimized DevOps, Continuous Integration, Continuous Delivery, Automation in Software Deployment, Streamlined Cloud CI/CD, AIOps and MLOps Integration
This research pays attention to the merging of
Development Operations with Artificial Intelligence (AI).
It starts by realizing that AI will be an important factor in
many aspects of work and that it will be automating some
job functions. Consequently, AI will be presented as a tool
that will enhance knowledge acquisition, provide job
performance and professional development. The story
stresses the opportunity cost attributed to the shift from
software licensing to Software as a Service (SaaS) and
underscores the benefits gained through early and regular
software release by the organizations which have adopted
the practice. DevOps, as a revolutionary approach, seeks
to eliminate the gaps in the two central processes namely
development and operations. The technology emerging,
which includes big data, cloud computing, and mobile
internet, calls for quick software deployment and
consequently, the DevOps approach is what you get.
However, DevOps is a unified approach. In the abstract, it
will talk about continuous integration (CI) and continuous
delivery (CD) spotting the cost-effectiveness and role of
automation in the production process. Through AI and
DevOps described, air is evident which is the AI role in
automation and troubleshooting development in the
software and hardware field. In the paragraph the author
puts forth AI-optimized DevOps as a proposal that is not
only efficient in development and distribution process but
also fast in pacing. The overall wrap-up summarizes the
AIOps and MLOps applications in conjunction with
DevOps workflow to eliminate disconnection between
machine learning model development and operational
deployment. The big picture actually is condensed at the
end. It outlines exactly how the AI DevOps approach
works in modern software development, with particular
focus on the cloud CI/ CD platform.
Keywords :
AI-Optimized DevOps, Continuous Integration, Continuous Delivery, Automation in Software Deployment, Streamlined Cloud CI/CD, AIOps and MLOps Integration
