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Truth and Proof: Building Trust in Machines Through AIOps

IT systems are only getting more complex, with greater pressures to solve issues faster and demonstrate value consistently. Issues within systems, which dev teams could once handle all on their own, sprout up too fast and too often for direct human intervention. Artificial intelligence for IT Operations (AIOps) tools exist today to deliver automated monitoring and solution development, “no humans required” — significantly easing dev teams’ many burdens.

Adopting AIOps should be simple enough, then. But one of the tougher sticking points has been trust. Can humans trust a machine to identify root causes of issues and create accurate and effective solutions? The stakes are high — if a machine gets it wrong, the burden on human teams compounds quickly.

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DevSecOps: A Complete Guide

Why should you learn about the basics of DevSecOps even if you’re not a software developer? The short answer is to improve security at your business or company. Organizations have long had a heavy focus on speeding up application development to deploy new software as soon as possible, but this frequently came at the cost of security.

Unfortunately, if an application was discovered to have security issues at this stage, it meant rewriting large amounts of code which could easily become a very convoluted, difficult, and time-consuming task for developers.

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Understanding AI Ops: Part 2

Welcome everyone to the second of my AIOps introduction. In Part 1 I talked about the challenges that exist today with digital transformation and how more and more automation is being used in software build and delivery areas.  I also talked about the fact that there is more and more pressure on IT Operations to react quickly, deal with infra, software, config, connectivity, security, multi-cloud; the list goes on and on.

Today, I am going to consider AIOps from the vantage point of the tools used for Operations Management and how they leverage AI/ML to solve common problems in the IT management domain. I have also included a link to part two of the video I highlighted in my last blog which imagines a future that AIOps could enable for IT Operations teams, allowing those teams to be true enablers of business outcomes.

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Agile In IT Support and IT Operation Teams

Introduction

A few colleagues and I had a discussion and we tried to capture our experience in the article below. During our engagement we devoted some time to understanding IT Operations and IT support teams, to discover their world, and how different their world was from the IT Product Development team.

These are a few of the questions we asked during our transformation drive:

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What is AIOps or Artificial Intelligence for IT Operations? Top 10 AIOps Use Cases

What is AIOps

Artificial Intelligence for IT Operations (AIOps) involves using Artificial Intelligence and Machine Learning technologies along with big data, data integration, and automation technologies to help make IT operations smarter and more predictive. AIOps complement manual operations with machine-driven decisions.

Types of AIOps Solutions

At a high level, AIOps solutions are categorized into two areas: domain-centric and domain-agnostic, as defined by Gartner. Domain-centric solutions apply AIOps for a certain domain like network monitoring, log monitoring, application monitoring, or log collection. You will often see monitoring vendors claim AIOps but primarily they are domain-agnostic, bringing the power of AI to the domain they manage. Domain-agnostic solutions operate more broadly and work across domains, monitoring, logging, cloud, infrastructure, etc., and they take data from all domains/tools and learn from this data to more accurately establishing patterns and inferences.

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IT Ops Drives Bottom-Line Growth

I had the opportunity to meet with Vijay Kurkal, Chief Operating Officer at Resolve Systems to discuss the current state of IT automation and orchestration. 

Most of Resolve Systems' customers are large Fortune 500 companies trying to figure out how to use automation to improve IT management processes the same way DevOps has improved development and deployment. Large legacy enterprises are spending 85% of their IT management budget just to keep lights on. 70% of that is personnel costs. Management is asking how we can use automation to improve IT management the same way it has improved development and deployment. 

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Why Cloud and DevOps Succeed Together

Businesses are continuously striving to bring high availability to customers with unmatched application performance, little to zero downtime, and seamless multi-channel experience. Moving to the cloud is one way to achieve these goals. However, even moving to the cloud is not a foolproof survival strategy. They still need agility, cost-savings, and better performance for millions of connected devices. The development and cloud operations must go hand-in-hand to make the most of cloud platforms. Companies missing DevOps on cloud operations or development are not reaping the promises of using cloud platforms.

Cloud and DevOps Are Better Off Together

First, using DevOps engineering (developers and QA teams) can work with the operations team employing a cloud platform. Developers can quickly set up new environments without the help of IT operations. Meanwhile, IT operations can investigate other operations of infrastructure costs, enabling security and dynamics. Cloud is the common language here and thus, connects two different teams.