How AI and ML Are Set to Change the Face of DevOps
December 01, 2021

Chandra Shekhar

Transformative technologies like Artificial Intelligence (AI) and Machine Learning (ML) have changed the way we perceive DevOps. They have transformed the DevOps environment in such a way that execution of processes like data analysis and management has not only become simpler but also faster. Not to mention, these next-level solutions help users speed up their software development cycle, thus ensuring faster time-to-value.

AI and ML are two buzzwords that are often used interchangeably. In fact, they are perceived similarly by many. But that isn't true.

As the name suggests, AI can be loosely interpreted to mean incorporating human intelligence into machines. In other words, it uses a machine to solve problems on the basis of a set of stipulated rules.

Contrarily, ML is a subset of AI, and it enables machines to learn by themselves (based on the available data) and make accurate predictions.

Despite the differences, both AI and ML play a vital role in reimagining the DevOps environment.

But before delving into ways AI and Ml do that, let's find out what DevOps entails.

Unraveling the Intricacies of DevOps

DevOps is the union of people, processes, and technology to provide delightful experiences and maximum value. By adopting such a culture, businesses can gain better insights into the data, deliver on the emerging needs and requirements of customers, increase confidence in the applications they build and achieve business ROI faster.

Let us take a real-life scenario for better understanding.

A manufacturing organization needs to bring its development and operations teams together to rapidly integrate and analyze partner or customer data for better collaboration and faster transactions. Ensuring a strong DevOps environment can accelerate this process, thus allowing the organization to accelerate time-to-market and deliver the promised value to customers and partners. Additionally, it can facilitate continuous improvement, thus maintaining system reliability and stability.

Applying Machine Learning and Artificial Intelligence to DevOps Culture

It's clear that organizations must create a strong DevOps framework to ensure reliable experiences, expand market share, and improve ease of doing business. However, it isn't as easy as it sounds.

Many times, teams find it challenging to manage their development and processes and handle operations. The role of AI and ML comes into play.

Integrating technologies like AI and ML can help companies transform their DevOps environment and increase their efficiency. Tasks like testing, coding, releasing, and monitoring software and harnessing the true potential of partner data become simpler and faster than ever. AI and ML can also improve automation, quickly identify and resolve issues, and improve collaboration, ensuring delightful experiences and maximum revenue. Let's find out how AI and ML can transform DevOps.

Improving Teams' Efficiency to Access Data

Oftentimes, business users of a DevOps organization find it difficult to access their own data. This lack of unrestrained data access can greatly affect a user's capability to onboard, integrate, and unlock data.

Consequently, a company's ability to make decisions and deliver value takes a toll. Solutions like AI-enabled data mapping can be of great importance here. They can empower even non-technical business users to access and unlock the true potential of data — at speed and scale.

Business users with minimal technical expertise can utilize machine learning algorithms to create intelligent data mappings in minutes, which allows them to create connections and integrate new customers — easily and securely. Meanwhile, IT users can focus on more important tasks, enabling innovation and ultimately growth.

Accelerating Automation

By leveraging AI and ML, business users can automate processes, turning them faster and accurate than ever. As machine learning algorithms are used to handle complex data streams, users can gain accurate insights, at a much faster pace — and that helps them make good decisions and delight their customers faster. AI enables teams to self-heal problems, track security threats, and resolve issues.

Fosterig Effective Collaboration Across Partner Network

While developers release code at high velocity, the operation teams have to ensure minimum disruption to the existing systems. AI and ML can transform DevOps by improving collaboration between developing and operations teams. They can provide a single, unified view into systems as well as problems across the complex chain of DevOps. And so, companies can improve the complete understanding and knowledge of anomalies detected and rectify them without any delay.


AI and ML are uniquely positioned to transform the DevOps environment in an organization, enabling users to harness data, speed up operations, improve time-to-market, and ultimately deliver maximum value.

Chandra Shekhar is a Technology Analyst at Adeptia
Share this

Industry News

November 22, 2022

Red Hat introduced Red Hat Enterprise Linux 9.1and Red Hat Enterprise Linux 8.7.

November 22, 2022

Armory announced its new cloud-based solution called Continuous Deployment-as-a-Service, now available on the AWS Marketplace.

November 22, 2022

Rapid has has formally rebranded Paw to RapidAPI for Mac.

November 21, 2022

Red Hat announced the general availability of Migration Toolkit for Applications 6, based on the open source project Konveyor, aimed at helping customers accelerate large-scale application modernization efforts.

November 21, 2022

Palo Alto Networks signed a definitive agreement to acquire Cider Security (Cider).

November 17, 2022

OutSystems announced its new cloud-native development solution OutSystems Developer Cloud (ODC).

November 17, 2022

Retool announced Retool Workflows, a fast, extensible way for developers to build cron jobs, scheduled notifications, ETL tasks, and everything in between.

November 15, 2022

OutSystems announced the new OutSystems AI Mentor System.

November 15, 2022

Redpanda launched the general availability of its Redpanda Cloud managed service.

November 15, 2022

Edge Delta announced the launch of a free version, Edge Delta Free Edition, providing an intelligent and highly automated monitoring and troubleshooting experience for applications and services running in Kubernetes.

November 14, 2022

Codenotary announced TrueSBOM, a patent-pending, self-updating Software Bill of Materials (SBOM) for every application that is made possible by simply adding one line to the application source code.

November 14, 2022

Azion announced the release of the Azion Build product suite.

November 09, 2022

Puppet by Perforce announced the latest Long-Term Support (LTS) release of Puppet Enterprise.

November 09, 2022

Couchbase announced new enhancements to its database-as-a-service (DBaaS) Couchbase Capella.

November 09, 2022

Macrometa Corporation announced a new strategic equity investment, go-to-market partnership, and powerful product integrations with Akamai Technologies.