It’s a perfect storm: infrastructure silos, increasing volumes of data, growing hybrid infrastructures, and mounting anomalies can bring down enterprise applications, or at least compromise availability or performance.
These forces in combination have already outstripped the human capacity and intuition to solve infrastructure issues – which may occur routinely or unpredictably. Today, IT’s typical toolset comprises many of the tools of the past 20 or more years; unfortunately, each of those “oversees” only a small percentage of the entire infrastructure.
As can happen, infrastructure issues only grow as infrastructures become more complex, and those issues go begging for solutions. One time-honored approach, the “War Room”, brings IT specialists together from siloed organizations across the infrastructure. Too often, though, their best outcome is identifying a trouble spot and patching it. But a patch is typically just a bandage on the wound. Until the source or sources are pinpointed, the issue will most likely crop up again without any warning.
Over just the last few years, the burgeoning use of artificial intelligence has promised a more substantive solution: AIOps, or Artificial Intelligence for IT Operations. Gartner nicely defines the problems that AIOps attacks:
“AIOps platforms utilize big data, modern machine learning and other advanced analytics technologies to directly and indirectly enhance IT operations (monitoring, automation and service desk) functions with proactive, personal and dynamic insight. AIOps platforms enable the concurrent use of multiple data sources, data collection methods, analytical (real-time and deep) technologies, and presentation technologies.”
That’s a mouthful, but what it all boils down to is this: AIOps is the first holistic approach to a deepening problem that threatens to strangle infrastructure availability and performance. But why has AIOps taken hold, as no other approach, methodology or technology has before? There are many possible answers to that question, but let me propose a three-part answer:
- AIOps pinpoints issues with a high probability of success. That’s because it has vast amounts of data to work with, generated in every node of the infrastructure – and more data means greater accuracy and better outcomes.
- AIOps works in real time. AIOps, well at least the Virtana version, is the first approach that can pinpoint the source or sources of issues in real time. That’s critical for functions such as anomaly detection, root cause analysis, remediation, prevention and planning, all of which can allay the risks of compromised infrastructure availability or even downtime.
- AIOps is reactive, proactive and predictive. Earlier AIOps tools performed reactively, such as to correlate alerts in order to address an issue on the infrastructure. Newer AIOps tools add proactive and predictive components – for example, knowing how to proactively automate workload balancing to eliminate an imbalance that could jeopardize performance.
AIOps is here to stay. And when you combine man + machine, AIOps may make the war room obsolete.
AIOps is the driving force behind Virtana’s VirtualWisdom, the industry’s leading hybrid IT infrastructure management and AIOps platform for mission-critical workloads. You can now try a free 30-day trial version of both VirtualWisdom and our latest cloud cost optimization and monitoring platform, CloudWisdom. Request your free trials today, and be sure to stay up on the latest and greatest in hybrid AIOps by following us on Twitter, LinkedIn and Facebook.
James Bettencourt
