How DevOps Takes Advantage of AI

Artificial Intelligence (AI) which encompasses Machine Learning (ML) and Deep Learning (DL), is one of the most widely adopted disruptive technologies by businesses and enterprises. The amount of data that DevOps teams need to handle has proliferated by multiples, making it increasingly difficult for teams to apply this data effectively to gain insights and address end-user concerns. The data explosion makes it difficult for teams to carry out critical and computation-intensive operations.

 AI can play a significant role in addressing this data explosion, thereby offloading human intervention for handling operations that demand intensive data processing. AI mimics the human brain and involves training computer systems to analyze from experience, like movie or product recommendation systems which are based on recurrent neural networks. In addition, home security and compliance systems deploy AI-based Natural Language Processing (NLP) techniques to grant authorization and access.

DevOps stands for Development and operations. It is a combination of cultural philosophies, tools, and practices that empower organizations to deliver quality software products and applications that satisfy customer requirements. It emphasizes shortening the development life cycle of software products and services by integrating the functions of development and Information Technology(IT) operations. The main aim of the DevOps strategy is to ensure uninterrupted delivery of services with top-notch quality that are devoid of errors or other glitches.

Let's see how AI can be used to transform DevOps.

How AI Improves and Transforms DevOps?

AI can increase the efficiency and productivity of DevOps practices. AI enables DevOps teams to create resilient codes that can be monitored and tested before the release. AI can also pave the way to automation that enables the development teams to quickly identify and trace out the bugs. AI fosters better data collection from various parts of the system and collates and subjects it to extensive data processing and analysis. Incorporating AI in your DevOps practices benefits you in the following ways.

Benefits of Deploying AI in Your DevOps Practices

1. AI Facilitates DevOps Teams to Have Better Accessibility to Data

The explosion in data demands the use of big data analytics and data science. As far as a DevOps consulting company is concerned, data accessibility is one of the biggest concerns. AI enables you to collect data from multiple sources that can be processed and analyzed to gain good insights.

2. AI Enhances DevOps Efficiency

AI paves the way for self-governed systems that can act on existing trained knowledge bases. This enables enterprises to transit from human-managed and maintained systems to self-driven intelligent systems. This can reduce the manpower requirements and drive their attention to other pressing issues.

3. AI Paves the Way to Easy DevOps Testing Practices 

AI speeds up the software development life cycle from the very outset to the delivery stage. AI tools can decrypt the underlying codes and patterns in the data that is acquired through unit tests, functional tests, integration tests, etc., and trace out erroneous coding practices, thus enabling teams to develop codes that are resilient to failure. 

4. Enhanced Resource and Time Management 

DevOps itself has automation at its core to reduce human intervention; adding to it a disruptive technology like AI, which emphasizes deploying self-driven intelligent systems, is a shot in the arm for the development team, thus further enhancing the overall pace of the software development life cycle. This accelerates the overall development process, thus enabling you to deliver quality applications to your customers in a time-bound manner.

5. AI Capabilities to Alert the DevOps Team Based on Abnormal Deviations 

Spotting the glitches and the flaws in the development process is an important step in your pursuit to deliver the applications to the end user. The development team may be bombarded with alerts that may be ranked with the same priority or severity. An intelligent and self-governed system based on AI can help teams to prioritize alerts based on past experience, their frequency of recurrence, alert severity, consequences, etc. Such a system enables teams to direct better their follow-up actions based on the nature of the alerts.

Conclusion

The prerequisite to employing AI capabilities in your software development process is a strong foundation of your DevOps structure. AI  can enable DevOps teams to direct their energy and time to specific functionalities and operations that are used to demand human intervention. AI capabilities empower enterprises and development teams to address and manage data independent of constraints such as the amount, variability, and processing. AI enables teams to test, release, and monitor their applications more efficiently. This not only paves the way to a faster development process but an enhanced customer satisfaction by providing them with high-quality applications and software that are devoid of any bugs and errors, ensuring that you do not find yourself in an untoward situation like recalling your product.