For years, industry leaders have rightfully evangelized the massive benefits of digital transformation. Abandoning outdated legacy systems and processes in favor of cloud-enabled ones helps produce greater insights, lowers operating costs, and streamlines operations for faster time-to-market of new products or services and a better overall customer experience. Already, 73% of organizations have at least a portion of their computing infrastructure in the cloud, and by 2020 more than two-thirds of all IT infrastructure will be cloud-based, according to a recent survey by IDC Global.
But as companies continue to migrate larger portions of their infrastructure to the cloud, they’re quickly finding that modernization doesn’t necessarily mean less work. There are more systems to configure, more data to transform and analyze, and more endpoints to secure. And each of these components comes with its own dashboards, monitoring systems, and alerting mechanisms. There’s more of everything to manage, but less time and fewer resources to do it. In fact, some studies suggest that global demand for data scientists to operationalize corporate data will outstrip supply by more than 50% and the talent shortage for cybersecurity expertise will grow to a whopping 3.5 million jobs by 2021.
In short, the growth of IT infrastructure is simply too much for humans to monitor and operate effectively. So what’s an IT team to do?
More data, more (serious) problems
Organizations across of all shapes and sizes are adopting artificial intelligence for IT operations (AIOps) to react and resolve IT issues faster, build models to predict when new ones will occur, and enable teams to properly leverage the latest analytics tools and applications without requiring data science expertise.
But to understand how they’re doing it requires clearly defining what AIOps is and how it works. While seemingly every industry and sector is abuzz with the promise of AI, how they define the technology differs greatly from market to market.
In the context of IT Ops, AIOps platforms utilize big data, modern machine learning and other advanced analytics technologies to provide real-time insights and automated processes to enhance IT monitoring, automation and service desk functions without the need for human intervention. That last part is especially important for already overburdened IT teams just trying to keep their heads above proverbial water every day.
In fact, recent OpsRamp research suggests that the strongest contributing factor to the rapid adoption of AI tools for IT is that IT teams are simply drowning in data. More than a quarter of IT incidents – interruptions, misconfigurations, or other tickets – are repeats of previously resolved incidents.
More concerning, over 60% of survey respondents said that cutting through the noise of so many alerts and other information was the biggest obstacle to doing their jobs. This alert fatigue has emerged as a significant issue, both operationally and financially.
What can AIOps do for you and IT
AIOps solutions help organizations cut through the alerting noise and gain critical control by proactively managing the health and performance of their enterprise IT services. By applying data science and computational techniques, AIOps tools can accurately predict a range of incidents across infrastructure, common IT management tools, and enterprise processes – and resolve them autonomously.
Specifically, AIOps solutions can help create complete visibility across your environment, aligning your hybrid IT resources and linking them with native performance management and monitoring tools. Incorporating intelligence Application Performance Management (APM) and Infrastructure Performance Management (IPM) tools makes it possible to accelerate incident detection across your entire environment and dramatically reduce the volume of alerts.
More importantly, intelligent operations solutions are designed to correlate and escalate incident alerts across distributed IT environments while consolidating raw alerts into context-infused events so that you can reduce noise across endless alert floods. They scour your infrastructure to uncover previously unidentified technical issues, automatically take preventive action or prescribed remediation, and automatically route incidents to the appropriate team for more rapid, targeted incident responses without time-consuming and costly administrative overhead.
In short, AIOps solutions create a distinct competitive advantage by reducing the effort required to sustain optimal performance and availability, preventing problems before they affect the customer and the bottom line, and providing previously non-existent context to the business impact by quantifying the cost of not taking action.
Those benefits aren’t just marketing-speak. Surveys reveal that more than two-thirds of IT decision makers are experimenting with AIOps tools in production for a range of purposes, all of them mission critical.
- 73% are using the tools for extracting relevant data insights
- 68% are conducting root cause analysis
- 49% rely on AIOps for alert correlation
- 28% rely on the tools to cut through the alert noise
Where to go from here
To keep up with the demands of digital business, organizations need new ways of managing incidents and maintaining system health. AIOps enables IT teams to rapidly sift through mountains of IT infrastructure data and assert control over the chaos of multiple alert streams.
As you move closer to adopting AIOps solutions in your own operations, be sure to select a platform that’s easy to deploy, configure, and maintain across a sprawling IT infrastructure. Choose tools that enable data aggregation and enrichment and proactive dashboards with real-time event context to achieve the strongest return on your investment.
Given the pressing need for modern incident management techniques, AIOps is clearly more than a passing trend. It’s an inflection point in the future of the agile IT Ops team and the key to a successful digital transformation.
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