Introduction to DevOps

Benefits of using DevOps in Machine Learning

If you are considering DevOps as a tool or software then you are wrong, it is a culture that you can adopt for continuous improvement. DevOps integrates developers team and operations team to improve collaboration. DevOps insure fast and shorter release cycle that can get new applications and features to customers quickly.

MACHINE LEARNING

Is a part of computer science which provide the computer with the ability to learn without being programmed. It uses pattern recognition and computational learning theory to build algorithm and predict future data.

DEVOPS PIPELINE

The pipeline breaks down the software development and delivery process into various stages. Each stage in the DevOps pipeline aims at verifying the quality of product and its features from a different angles to fix the errors and insure fast and shorter release cycle that can get new applications and features to customers quickly. The purpose of DevOps pipeline is to create a continuous management and release quick setting where bugs, compatibility and security issues are identified. As this pipeline is visible to each team member working on the product when any error occurs all team members are informed and work together to fix it.

Benefits of using Machine Learning in DevOps pipeline

In DevOps it is essential to keep all the necessary information of the product which organization is working on. There should be professionals who are familiar with product flow, analytics and trouble shooting and must be able to figure out errors in the process and report continuously. Here machine learning helps aiming to reduce human efforts in troubleshooting or error recognizing. Machine learning plan and analyze the data to predict the future workflow for reducing any unwanted bugs.