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

Chandra Shekhar
Adeptia

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.

Conclusion

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

August 18, 2022

GitHub Enterprise Server 3.6 is now generally available.

August 18, 2022

Opsera announced the availability of Opsera GitCustodian.

August 18, 2022

CircleCI announced the general availability of the CircleCI Visual Configuration Editor, an all-in-one open source project for configuration editing, including creating component definitions and usages.

August 17, 2022

Cloudera announced the launch of Cloudera Data Platform (CDP) One, an all-in-one data lakehouse software as a service (SaaS) offering that enables fast and easy self-service analytics and exploratory data science on any type of data.

August 17, 2022

Prosimo introduced a new NetDevOps Infrastructure-as-Code (IaC) Toolkit that enables enterprises to accelerate the deployment of cloud networking.

August 17, 2022

Aqua Security announced the addition of cloud security posture management (CSPM) capabilities to the open source tool Aqua Trivy.

August 16, 2022

Canonical welcomes the .NET development platform, one of Microsoft’s earliest contributions to open source projects, as a native experience on Ubuntu hosts and container images, starting in Ubuntu 22.04 LTS.

August 16, 2022

Veracode announced the launch of the Veracode Velocity Partner Program.

August 16, 2022

Render announced a new monorepository feature that enables its customers to keep all of their code in one super repository instead of managing multiple smaller repositories.

August 15, 2022

Gadget announced Connections, a major new feature that gives app developers access to building blocks that enable them to build and scale ecommerce apps in a fraction of the time, at a fraction of the cost.

August 15, 2022

Opsera is on the Salesforce AppExchange to help enterprise customers shorten software delivery cycles, improve pipeline quality and security, lower operations costs and better align software delivery to business outcomes.

August 15, 2022

Virtusa Corporation earned the DevOps with GitHub on Microsoft Azure advanced specialization, a validation of a services partner's deep knowledge, extensive experience and proven success in implementing secure software development practices applying DevOps principles and using Azure and GitHub solutions.

August 15, 2022

Companies looking to reduce their cloud costs with automated optimization can now easily procure CAST AI via Google Cloud Marketplace using their existing committed spend.

August 11, 2022

Granulate, an Intel Company, announced the upcoming launch of its latest free cost-reduction solution, gMaestro, a continuous workload and pod rightsizing tool for Kubernetes cost optimization.

August 11, 2022

Rezilion announced the availability of MI-X, a newly created open-source tool developed by Rezilion's vulnerability research team.