Agile Software Development

How is AI Accelerating DevOps?

Artificial intelligence (AI) and DevOps are interdependent. DevOps is an approach to deliver software while AI will enhance functionality. The future of DevOps looks promising with AI and machine learning (ML) because the technology automates DevOps processes and improves code quality. In this article at ZDNet, Joe McKendrick shares insights into Gitlab’s ‘2021 Global DevSecOps Survey’ and explains how AI is taking over DevOps functions.

Highlights of the Survey

According to Gitlab’s ‘2021 Global DevSecOps Survey,’ the researchers found a sharp increase in automation, continuous deployments, and security postures. Additionally, 75% of survey respondents relied extensively on cutting-edge technologies such as AI, ML, and bots to test and review their codes before release. On the other hand, 56% of respondents reported their teams are either ‘fully’ or ‘mostly’ automated.

On the security front, 72% of security professionals rated their organizations’ security as either ‘good’ or ‘strong.’ The survey also revealed that the DevOps teams are running more security scans than ever before.

AI’s Role in DevOps

Improved Data Access

As a lot of data is generated in DevOps, teams may face issues accessing the data. However, AI helps in compiling and organizing data from multiple sources. This provides an organization with a good picture of trends.


Distributed Denial of Service (DDoS) can target any organization or website—irrespective of its size. However, AI and ML can efficiently help in identifying and managing these threats. For example, DevOps teams can use algorithms to differentiate normal and abnormal conditions and accordingly take actions.

Software Testing

AI helps in enhancing process development by identifying the pattern of collected data. The technology then determines coding practices that led to the error. DevOps teams can use this information to increase their efficiency.

Experts believe that more established companies may find it hard to implement policies and procedures due to complex organizational structures. To effectively implement a DevOps program, an organization must invest the financial and human resources necessary for maintaining a quick-release schedule.

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