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AIOps of the Future: Building Confidence in Corporations

By Richard Whitehead, Chief Technology Officer for Moogsoft

Technology has revolutionized our world and impacted our daily lives. From increasing the amount of e-commerce sales to increasing the number of remote employees, technology now dominates nearly every aspect of modern-day life and business.

Most people take for granted technology's role in their personal and professional lives. We need food, we open a food delivery app and - with just a few clicks - the food miraculously shows up on our doorsteps. We have the same expectations with our remote work tools, messaging apps, transportation platforms, streaming services and the list can go on. We expect - make that demand - that digital apps and services work flawlessly - 24 hours per day, 7 days per week.

And what if these digital apps and services aren't consistently available? The stakes are high. Just consider what would happen if your food service delivery app went down. You'd probably lose at least some confidence in the brand and look for an alternative digital solution to your problem. And, chances are, depending on your customer experience, you'll look for that "dependable" solution the next time around. For modern business, that means: the already exorbitant upfront cost of downtime is compounded by fewer customers, diminished sales and slow long term growth.

In other words, corporations are under immense pressure to deliver continuous service assurance. But this is no easy task. Today's technologies are complex, distributed and evolving, meaning incidents will affect digital apps and services.

The secret to maintaining uptime of complex systems in a society intolerant of performance issues? The DevOps and SRE teams behind service assurance must anticipate incidents instead of just fixing them. And there's only one way to accomplish this: advanced artificial intelligence for IT operations (AIOps) solutions.

Let's get clarity on the tools DevOps and SRE teams need to maintain modern-day availability - and what no longer works.

Why some AIOps technologies don't cut it

Gartner coined the term "AIOps" in 2016, defining it as "combining big data and machine learning to automate IT operations processes, including event correlation, anomaly detection and causality determination." AIOps platforms would ingest data, scanning for abnormalities and notifying teams if there were performance-affecting incidents.

In reality, many early AIOps solutions were simply traditional infrastructure monitoring and APM tools rebranded as AIOps, many contained no actual AI at all, and others added AI and Machine Learning (ML) capability, but a usually unused option. While these capabilities were useful, and provided additional diagnostic capability, they are generally only useful after the incident, and after they affected end users. In fact, 45% of customers alert companies to a problem before their tools do. However, as consumers rely more on digital apps and services, downtime can harm corporate brands.

Companies can no longer afford to fix incidents after they have impacted the end user. They must adopt advanced AIOps tools that detect issues early in the incident lifecycle and automate the workflow for rapid mean time to recovery (MTTR).

What modern teams need from AIOps solutions

As IT environments become more complex, businesses need to know there is a problem before their customers do. Modern AIOps tools help detect incidents early in the lifecycle by ingesting various kinds of data - not just event data - from across the entire IT ecosystem. With early detection, DevOps and SRE teams can fix anomalies before they become outages or performance issues.

But that's not all modern AIOps does in its mission to increase uptime. The solution eliminates noise and non-incidents and provides valuable context to the problem for quicker root cause identification and incident resolution. The solution also automates the entire incident management lifecycle.

What are the potential outcomes?

By finding anomalies early and automating incident management, advanced AIOps solutions enable DevOps practitioners and SREs to react to incidents early before they impact the customers' experience. A seamless user experience doesn't only benefit end users, it allows DevOps to accelerate the feedback from deployments, and allows SRE's to preserve the valuable error budget. It also gives time back to DevOps practitioners and SRE teams to spend more time on value-driven initiatives like building new features and working on platform improvements. This is critical as most teams spend far more time on monitoring than any other activity.

As we continue to navigate a digital-first world, people increasingly rely on technology - and increasingly expect a seamless user experience. Modern companies need to maintain customer sentiment while keeping up with the complexity of a modern IT environment. To do so effectively, they need advanced AIOps that support continuous availability by detecting problems before they impact their customer experience.



Richard Whitehead 

As Chief Evangelist, Richard brings a keen sense of what is required to build transformational solutions. He's a DevOps Institute Ambassador, and serves on the DevNetwork AI/ML Advisory Board.

A former CTO, and Technology VP, Richard brought new technologies to market, and was responsible for strategy, partnerships and product research.

Richard served on Splunk's Technology Advisory Board through their Series A, and more recently co-chaired the ONUG Monitoring & Observability Working Group.

Richard holds three patents, and is considered dangerous with JavaScript.

Published Wednesday, November 09, 2022 7:31 AM by David Marshall
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