Machine Learning is Transforming and Optimizing DevOps
When they work together, software development and operations teams can advance a company's business transformation. The integration of these teams, also known as DevOps, streamlines the legacy software development process. However, with the growing emphasis on digital transformation, the pace of development and innovation has increased. Therefore, the need for optimal orchestration in DevOps is rising, which requires innovation and advanced tools and technologies.
Typically, companies face significant challenges when running and managing DevOps teams. It involves large volumes of continuous data flow, which leads to complexities and inefficient data management. The manual effort to absorb and channel DevOps teams’ data and information becomes incompetent in a dynamic application environment. Another challenge for developers in today’s rapidly evolving digital era is the inability to quickly build and deliver applications to meet customers’ needs. To address these challenges, ML/artificial intelligence (AI) is emerging as a promising technology to transform and optimize DevOps processes.
The analyst has assessed the impact of ML on DevOps; this research service covers the following topics:
- An Introduction to Machine Learning in DevOps
- A Technology Market Overview
- The Transformation of DevOps with Machine Learning
- The Intellectual property (IP) Landscape
- The Key Market Participants
- Growth Opportunities
Table of Contents
Companies Mentioned (Partial List)
A selection of companies mentioned in this report includes, but is not limited to:
- Algorithmia
- Alteryx
- Databricks
- JFrog
- Snyk
