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Red Hat and IBM tandem to improve AIops with open source project

Gartner defines AIops as what you get when you combine big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and cause and effect detection. But what about provisioning, configuration, deployment and orchestration? All of these important parts of IT operations don't get

Dmitry Spodarets profile image
by Dmitry Spodarets
Red Hat and IBM tandem to improve AIops with open source project

Gartner defines AIops as what you get when you combine big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and cause and effect detection. But what about provisioning, configuration, deployment and orchestration?

All of these important parts of IT operations don't get as much attention from AIops, because they are also at the heart of Red Hat's open source IT automation tool, Ansible.  The tool is one of the world's most popular open-source projects focused on using automation to install software, automate day-to-day tasks, provide infrastructure, improve security and compliance, patch systems, and share automation across the organization.

Ansible simplifies the creation and operation of IT infrastructure by abstracting them into a common language. Rather than learning the specifics of each piece of infrastructure - whether it's Cisco or NetApp, Postgres or MySQL - Ansible offers a layer of modules that interact with the underlying APIs of those pieces of infrastructure and abstract them into a common Ansible language.

As part of Project Wisdom, Red Hat has new plans for Ansible.  In partnership with IBM Research, the company aims to take automation to the next level. Red Hat calls Project Wisdom the first community project to build intelligent natural language processing (NLP) capabilities for Ansible and the IT automation industry.

Project Wisdom "applies artificial intelligence to automate infrastructure and application deployment, using natural language processing to translate English commands into automation scripts. The goal of Project Wisdom is to make automation experts more efficient and help newcomers get up to speed faster. Instead of figuring out all the intricacies of the underlying infrastructure and using YAML, users can simply enter English commands in natural language.

By 2030, the growth of data and the associated increase in cloud computing will result in a projected global AIops market of $644.96 billion.

And in a previous news story, we wrote about IBM Research's Artificial Intelligence Hardware Center creating a specialized computer chip for artificial intelligence - the Artificial Intelligence Unit, or AIU. This is the first complete system-on-a-chip designed to run and train deep learning models faster and more efficiently than general purpose CPUs.

Dmitry Spodarets profile image
by Dmitry Spodarets

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