How AIOps Can Keep Your Organization Up and Running

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In this special guest feature, George Thangadurai, CEO, HEAL Software Inc., believes that if your IT team is ready to make the switch to an AIOps solution, it is important to understand what capabilities are available. The article includes four key capabilities you will want to be sure your software includes. Heal Software is a global leader in AIOps and developer of the game-changing preventive healing software known as HEAL, which helps businesses fix problems before they happen.

The growing adoption of complex digital solutions has put increasing pressure on IT leaders to ensure businesses stay up and running. Any downtime can have a significant impact on a company’s revenue, productivity and reputation. Thankfully, artificial intelligence for IT operations (AIOps) solutions have emerged and gained popularity in recent years to help companies run more smoothly. 

If your IT team is ready to make the switch to an AIOps solution, it is important to understand what capabilities are available. Here are four key capabilities you will want to be sure your software includes:  

  • Predictive and Preventive: Rather than waiting for an issue to occur, some solutions offer preventive healing capabilities that intelligently detect anomalies. Oftentimes, these solutions leverage healing actions and remedial workflows to bring system parameters back to normal before an issue occurs, and without requiring human intervention. That saves your IT staff time and prevents a costly outage. 
  • Collective Knowledge: Organizations commonly rely on several separate monitoring tools. Each of these tools gathers extensive data, but often operates in silos requiring IT teams to monitor alerts from various systems. To make that process more efficient, look for an AIOps solution with collective knowledge capabilities comprised of a suite of APIs and connectors that integrate with APM vendors and content formats. Additionally, some solutions come equipped with their own agents to collect workload, behavior, configuration and log data.  
  • Situational Awareness: When IT teams are plagued with alert fatigue, it is often hard to determine where to start. Some AIOps help produce precise predictions using contextual data – including forensic data that captures the state of the processes/queries running on the system at the time of the anomaly. This helps reduce mean-time-to-resolution (MTTR). 
  • Remedial and Autonomous: When an anomaly occurs, leveraging intelligent machine learning can provide IT teams confidence that the anomaly will be addressed in one of two ways: (1) by scaling up to handle the workload or (2) triggering autonomous correction of the underlying issues that caused the anomaly.   

While AIOps adoption is growing, it is primarily used by large businesses. To help make it more available to small- to mid-size businesses, some AIOps providers have expanded their traditional on-prem offering to provide a software-as-a-service solution. Here are some of the ways small- to mid-size businesses can benefit from a SaaS option: 

  • Accessible: Traditional AIOps solutions are tailored for large enterprises and come with substantial costs and extensive set up. SaaS solutions remove this hurdle, with some even offering a try-before-you-buy option.   
  • Flexibility to scale: Some SaaS solutions provide tiered pricing models to ensure businesses only pay for what they need. Look for a solution that has a full product portfolio of on-prem, hybrid and cloud offerings to enable your organization to seamlessly transition as your needs grow. 
  • Immediate results: SaaS offerings provide simplified installation and setup for businesses with up to 40 servers. Some even provide out-of-the-box support for business applications like SAP and other e-commerce applications to allow customers to plug directly into cloud APIs and start monitoring immediately.

Solutions that minimize downtime should not exclusively be available to large enterprises. By leveraging modern SaaS AIOps solutions, all businesses can have the opportunity to reduce mean-time-to-know (MTTK) and MTTR. 

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