Between next-generation technologies such as software-defined networking, a never-ending flood of Internet of Things devices and a threefold increase in data traffic through 2021, enterprise IT environments keep getting bigger, busier and more complex. Add in the chronic shortage of IT professionals, and it’s clear that enterprises need a new, fundamentally different way of managing their systems.
That’s why vendors such as Splunk are adding artificial intelligence capabilities to their IT operations analytics platforms. AI-powered ITOA promises to decrease the amount of time and number of people required to track down and resolve problems.
For example, suppose a lot of customers suddenly complain that they can’t make purchases on your e-commerce site. Traditionally, you’d have to consult each vendor-specific tool that comes with each piece of hardware, software and cloud service supporting the site, and then try to connect all those dots to ferret out the problem. Every minute spent on that legwork translates into lost sales and frustrated customers.
New and Deeper Insights
ITOA saves time and money by pulling data from all of those vendor-specific tools and putting it in a centralized dashboard. That makes it quicker and easier to analyze and resolve problems. (For a deeper dive into how ITOA works, see my recent blog post series.)
AI-powered ITOA provides a host of additional capabilities and benefits. For example, it can identify nascent trends in traffic patterns and alert you with predictions about how those will play out — such as with declining performance that undermines customer experience or employee productivity.
These kinds of insights enable you to head off problems by automatically applying changes before these problems even become noticeable. By enabling you to be more proactive, AI ITOA means you spend less time being reactive.
Not a DIY Project
To do its job, AI ITOA needs two types of data. The more of each it gets, the more effective it is.
The first type is historical data, which establishes a baseline and trains the AI ITOA platform to see how normal looks — and what it doesn’t look like. The other is live, streaming data, which the platform compares to the historical data in real time to identify events, trends, anomalies and other conditions.
So, when enterprises implement AI ITOA, the first key step is ensuring all of the necessary data capabilities are in place to serve the platform: ingestion, storage, access and the ability to marry historical data sets and streaming feeds in real time.
Laying that foundation takes a lot of time and expertise, which is why enterprises typically turn to a partner such as CDW. With all of the day-to-day tasks on your plate, there’s not much time left to get up to speed on all of the AI ITOA solutions on the market and determine what it takes to implement each one.
A good partner analyzes your environment, develops an AI ITOA strategy, provides an implementation roadmap and gets everything up and running. The sooner you get started, the sooner you can start reaping the benefits.
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