What is AIOps and How is it Changing IT Operations?

IT Ops teams are under nonstop pressure to work faster and deliver better results—at less cost. This isn’t easy, as IT organizations must support infrastructure in multiple clouds, on-premises, the connections in between, and SaaS applications to enable business advantages and keep up with stakeholder expectations. Organizations are up against rapidly soaring volumes of data, generated by infrastructure and applications that must be captured, analyzed, and used to improve business processes.

To meet these challenges, many are turning to AIOps.

What is AIOps?

AIOps (Artificial Intelligence for IT Operations) uses machine learning (ML) and data science to automate and enhance IT operations. By combining big data and AI, AIOps helps IT teams identify, troubleshoot, and resolve availability and performance issues, improving operational efficiency and system reliability. Central functions of AIOps include:

Ingesting data from multiple sources, agnostic to source or vendor
Performing real-time analysis at the point of ingestion
Performing historical analysis of stored data
Leveraging machine learning
Initiating an action or next step based on insights and analytics

What Problems can AIOps Solve?

The real power of AIOps lies in the ability to consume and analyze the ever-increasing data generated by IT—and present it in a practical, actionable way. This data includes:

Infrastructure and application data, such as the data from monitoring systems and logs from IASM tools
IT service management (ITSM) data, such as tickets, change controls, and asset information
Business system data like robotics process automation (RPA) tools

AIOps especially offers benefits for performance monitoring and other essential IT operations. Modern monitoring platforms can provide visibility through monitoring for today’s complex, hybrid infrastructures, but visibility alone is no longer enough. Traditional manual processes of sorting through deep arrays of monitored data to find meaningful information are not scalable—and take too much time in the event of an outage.

IT operations teams need an intelligent monitoring platform that can cut through the noise to quickly surface information that lets them minimize downtime and maximize performance. By adding AIOps capabilities, monitoring platforms can provide the intelligence needed to help IT operations succeed, even in today’s increasingly complex environments.

By automating analysis, AIOps provides the data-validated insight IT teams need to make smarter, faster decisions. AIOps has enabled enterprise organizations to reduce costs, optimize resource utilization and capacity, identify threats and performance anomalies sooner, resolve issues faster, and in general better understand and act on operational challenges.

AIOps Drives Better Business Outcomes

For IT organizations, bringing together a full range of relevant data can enable service improvements that can dramatically enhance business outcomes.

Maximizing Service Quality and Availability

AIOps can provide IT teams with more context and insight that, when combined with automation, can enable incident prevention. For example, AIOps may be used to identify that resource usage patterns, if they continue, will result in an outage and provide recommendations for avoiding said outage. When integrated with an automation platform, these recommendations may be executed to correct resource usage and prevent the outage.

In addition, AIOps can deliver the insights required to support more stable, highly available customer-facing services. Organizations can prioritize the elimination of application and infrastructure faults based on their impact on stability. The result is improved user satisfaction, better long-term customer retention, and enhanced revenues.

Accurately Assessing Problems

Business stakeholders require quantified metrics to understand how issues affect their business. AIOps lets enterprises apply contextualized data to create more precise, tangible estimates about the impact of an incident. Instead of collecting and analyzing data from several systems, infrastructure and operations teams can leverage AIOps-developed insights from a data lake.

Industry Adoption is Accelerating

AIOps is rapidly gaining adoption as organizations in every industry accelerate digital transformation.

According to Gartner, global AI-derived business value will reach nearly $3.9 trillion by 2022.
Gartner also predicts that, by 2022, 40% of medium and large-scale enterprises will adopt artificial intelligence (AI) to increase IT productivity.
According to WisdomPlexus, 60% of management is predicted to adopt AIOps to improve their work quality and workplace conditions.

Enabling Future Intelligence and Automation

As organizations embrace AIOps, its capabilities will continue to evolve. AI sense and automation are expected to unlock new capabilities such as:

Enhanced prescriptive and predictive functionality: The ability to mine more data centers for patterns with ML will provide more actionable insights and new proactive capabilities. Contextualizing machine data with incident, problem, change, and knowledge-based data from humans or the infrastructure sets the stage for self-healing organizations.
More effective security analytics: Organizations are already contextualizing data to detect application and infrastructure anomalies. The next step is to spot anomalous user behavior. The average cost of a corporate data breach is $3.9 million. Security analytics are a compelling capability for organizations that do not have a complete security information and event management (SIEM) solution.
Superior employee experience: In today’s talent-driven economy, organizations are focusing on measuring the employee experience (EX) to boost retention and productivity. The right application of technology can help them determine how happy employees are with their applications, and which tools are most effective. End-user experience management capabilities will increasingly become commodity capabilities.

“IT leaders are enthusiastic about the promise of applying AI to IT operations, but as with moving a large object, it will be necessary to overcome inertia to build velocity. The good news is that AI capabilities are advancing, and more real solutions are becoming available every day.”—Padraig Byrne, Senior Director Analyst at Gartner

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Intelligent, unified monitoring platforms allow enterprises to predict and plan for what’s ahead. Monitoring helps businesses move from asking “what happened?” to predicting what’s coming, solving problems before they start, and using data to unlock opportunities. LogicMonitor, for example, is an agentless, automated monitoring platform that provides comprehensive coverage of hybrid cloud and on-prem environments via software provided as a service (SaaS). A SaaS-based IT infrastructure monitoring platform makes it easy for any organization to monitor the health and performance of hybrid infrastructure, the performance and availability of applications running on that infrastructure, and key indicators for business-critical services. Consider a solution like LogicMonitor that utilizes agentless collectors and an AIOps Early Warning System to reduce implementation time and realize ROI more rapidly. Click here to learn more or request a free trial of LogicMonitor’s monitoring solution.

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