Rev Up Your Digital Transformation Engine with AIOps » FixStream
How to Predict and Avoid IT Problems and Outages with AIOps Not All AIOps Solutions are Created Equal

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Rev Up Your Digital Transformation Engine with AIOps

Digital transformation is a mandate for the online business world, and it’s at the top of every CIO’s agenda. More than just an IT challenge, digital is changing economic fundamentals, business dynamics, and competition on a global scale.

To support the scope and scale of digital-driven change on the organization, IT executives are spending big money on solutions. Industry analyst firm IDC estimates spending will exceed $2 trillion in 2019, and 40 percent of all technology spending will be for digital transformation technologies. And for good reason. Sixty-four percent of IT executives surveyed expect to derive significant value from digital technologies over the next two years.

Yet, despite the investment, IDC also predicts that 75% of CIOs and their enterprises will fail to meet all of their digital objectives in 2018. There are many reasons why digital initiatives fail, but one reason is that they create a whole new set of issues for IT. The level of complexity created by digital has never been seen before, and it continually drains resources and budget.

IT is Drowning in Complexity

It’s easy to see why digital transformation is falling short. IT teams are bogged down by the sheer complexity of today’s hybrid, dynamic IT environments. Along with steep learning curves and lightning-fast changes to new technology, IT departments must cope with soaring consumer expectations, supporting legacy systems, lack of skilled talent, disparate tool sets, and opaque physical and virtual IT infrastructures. These factors complicate IT staff’s ability to oversee operations and optimize system performance.

To demonstrate how data complexity impairs IT operations, a recent IDC article describes how data analysts spend over 80% of their time on data collection, preparation, and governance, versus just 20% of their time on data analytics, where the real business value lies. The problem is compounded by the growth in data volumes as well as the increasing complexity of the data itself. The article points out possible solutions, noting that “machine learning has the potential to significantly change the way data is managed and automate many of the tasks related to data.”

Blinded by the Details

Despite continued investments in system resources, IT cannot holistically see what’s in their physical and virtual infrastructure. And without a clear view of the entire IT environment and the ability to make sense of the mountain of data being served up by various system tools, Ops teams can’t figure out what’s wrong – or how to fix it.

We have seen this challenge repeatedly at our prospective customers. Recently, we visited a company using 17 different tools to monitor infrastructure, applications and services. Each tool has its own portal, its own alert system, and is owned by a different department. There is no way to correlate the data generated from each of these disparate tools. When there is a critical alert, support staff must email back and forth between departments to gather information needed to identify root cause – MTTR can take hours while the business is at a standstill.

Transforming IT with AIOps

Traditional, domain-centric monitoring and IT operations management is no longer adequate in today’s dynamic virtualized environment. These older systems cannot correlate the onslaught of data various IT domains create, and they’re unable to provide the insights IT operations teams need to proactively manage their environments.

But you can rev up digital transformation initiatives with AIOps – Artificial Intelligence for IT Operations. These software systems combine big data and AI or machine learning technology to enhance and partially replace a broad range of IT operations processes and tasks, including availability and performance monitoring, event correlation and analysis, IT service management, and automation — dramatically simplifying IT operations.

AIOps automatically correlates the millions of data points across the entire stack, applying machine learning so IT can increase end-to-end application assurance and uptime. By correlating, visualizing and predicting issues across hybrid IT stacks, AIOps provides the insights IT teams need to proactively manage and support their digital environments. The improved visibility into the system components and their interdependencies helps organizations accelerate their technology migrations.

The business benefits of AIOps are clear. AIOps optimizes IT by automating 
root cause analysis, enhancing system performance and availability. It can dramatically simplify IT operations, improve efficiencies, and drive down costs. The technology can free up an amazing amount of resources, reducing waste to make operations more efficient. In turn, the organization can align IT and LOB to focus on business transformations that drive higher financial results.

This article was originally published in insideBigData.

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