How AI is Changing DevOps for the Better

Managing a DevOps environment involves a high degree of complexity. The rapid proliferation of data has made it difficult for DevOps teams to effectively onboard, ingest and unlock data and implement information to make good business decisions and deliver delightful experiences. Imagine a team poring over troves of information to identify critical factors that triggered an event—they would end up investing long hours to interpret and analyze the information.

The future of DevOps will be AI-driven. It’s fair to say that it’s challenging for human intelligence to harness large volumes of highly complex data. Consequently, AI-powered solutions will become the number one choice for integrating and analyzing data and transforming how teams develop, deliver, deploy and manage applications.

By 2023, 40% of DevOps teams will leverage application and infrastructure monitoring solutions with built-in AI capabilities, Gartner noted. Currently, in times of disruption, Gartner predicts the AIOps market will grow at breakneck speed, between $300 million and $500 million per year.

Let us explore how AI and DevOps are intertwined before we explore how AI is transforming DevOps.

DevOps and AI are Intertwined

AI and DevOps are intertwined. Integrating AI in a DevOps environment boosts the overall performance and efficiency of an organization.

AI and ML-powered solutions enable DevOps teams to onboard, map and integrate large volumes of customer or partner data with accuracy and speed. That is to say, business users find it easier to drive processes like data onboarding, data mapping and data integration, thus improving ease of doing business and delivering improved customer experience (CX).

Organizations that rely on AI-powered solutions no longer need to devote long hours to custom coding and EDI mapping to analyze large volumes of data. The time saved can be used to focus on more important, innovation-driven tasks.

AI also boosts automation, allows users to address and resolve issues in both data and applications and facilitates better cooperation among teams.

4 Ways AI is Transforming DevOps

The efficacy of DevOps correlates with an upward shift in AI. It can empower even non-technical business users to create connections and drive transactions at the speed of business. As a result, it brings non-technical business users to the forefront of business, thus freeing IT and developer teams to focus on more important tasks. Business users can leverage machine learning algorithms to collect data from different parts of DevOps systems and then map and integrate it in minutes through predictions.

Here are four ways AI is transforming DevOps:

1. Improved data access: The lack of free access to complex data streams is a challenge for DevOps teams. AI enables business users to access all the siloed data and harness its true potential for better insights delivery and decision-making. AI-powered tools can gather data from various sources for consistent and repeatable analysis.

1. Faster data integration: AI and ML-enabled technologies enable non-technical business users to execute data mapping and data integration in minutes instead of months. As non-technical users drive operations, IT becomes free to take up governance and instead focus on more high-value tasks. Thus, not only can AI help business users integrate data faster to deliver experiences and value but also enables IT teams to drive innovation and growth.

1. Higher implementation efficiency: With the support of AI, businesses can perform more tasks with less human intervention and minimal coding. This reduces the burden laid on IT or developer teams, enabling them to concentrate more on innovation and creativity.

1. Better security: As security is essential to facilitate a successful software implementation, DevSecOps is a fundamental aspect of software development. Organizations must bolster their security systems to guard against an increase in threats. AI can play a vital role here. It can enhance DevSecOps and boost security by recording threats and executing ML-based anomaly detection through a central logging architecture. By combining AI and DevOps, business users can maximize performance and prevent breaches and thefts.

Accelerating development cycles while making sure data is interpreted and analyzed properly is a challenge faced by DevOps teams today. Artificial intelligence-powered solutions are helping organizations transform every stage of DevOps building cycles without burdening IT teams or adding costs. Ergo, AI can enable users to transform the DevOps environment, deliver delightful experiences and grow revenue.