AIOps - The Future of IT Operations

Micro Focus Contributor
Micro Focus Contributor
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speed.jpgIn the digital era, IT organizations that identify and understand patterns in vast and diverse data are best equipped to find, fix and prevent performance problems. But when digital transformation outpaces IT performance management, hybrid and multi-cloud infrastructure creates complexity and comes with a hefty price tag. This is where AIOps comes into the picture.

Gartner describes AIOps platforms as software systems that combine big data and AI or machine learning functionality “to enhance and partially replace all primary IT operations functions, including availability and performance monitoring, event correlation and analysis, and IT service management, and automation.” Put simply, AIOps is the application of machine learning and data science to various IT operations to make them more efficient.

The Inevitable Need for AIOps
Gartner has also predicted that “large enterprise exclusive use of AIOps and digital experience monitoring tools to monitor applications and infrastructure will rise from 5% in 2018 to 30% in 2023.” Businesses are increasingly adopting AIOps, and view it as a practical and necessary element amongst a suite of next-generation IT solutions.

Let’s take a closer look at why businesses are turning to AIOps:

  • Breaking Down Data Silos
    Many organizations report the inability to manage large chunks of data as the key reasons for not monitoring the events and system effectively in their environment. AIOps enables organizations to break down data silos and overcome the existing challenges with full visibility across the IT environment.

    There are multiple AI capabilities, especially with the amount of data available for analysis and monitoring. The best practice is to substantiate data and identify the top occurring problems.

    Data is ingested in the form of logs, event metrics and are taken through a set of algorithms which selects data points. Once the data points are chosen, correlation or set of patterns are identified, inferences are drawn and passed onto a collaborative work environment.

  • Eliminating IT Operational Noise
    If you are a part of an ITOps team, IT operational noise is your number one concern.  IT noise creates severe problems for the business- higher operating costs, performance and availability issues, and risks to enterprise digital initiatives. AIOps makes a tangible difference across the industries. AIOps-powered tools not just reduce IT noise, but eliminate these  by creating correlated incidents that point to the probable root cause.

  • Delivering Seamless Customer Experience
    Ensuring a seamless customer experience is quintessential and delivering a superior user experience with predictive analytics is an important business objective. AIOps makes complex automated decisions by collecting and analyzing data. By leveraging this data, it can predict probable future events that may impact availability and performance before they become an issue. AIOps helps to speed up problem-solving and deployment.

  • Overcoming Monitoring and Analytics Challenges
    The use of a wide range of monitoring tools makes it extremely difficult to arrive at results and quickly correlate and analyze multiple application performance metrics to solve complex emerging problems before they impact end-user experience. As mentioned earlier, data collection is the primary step in enabling AIOps, and this data must be collected and correlated from multiple sources to be effectively analyzed. AIOps and digital experience monitoring deliver a primary, single pane of analysis across all domains underlying the service, thereby reducing the need to use multiple tools for analysis.

    When properly implemented and trained, an AIOps platform reduces the time and attention of IT staff spent on mundane, routine, everyday alerts. IT staff teaches AIOps platforms, which then evolve with the help of algorithms and machine learning, recycling knowledge gained over time to further improve the software's behavior and effectiveness.

Business Benefits of AIOps
The massive increase in the adoption of AIOps shows a pragmatic shift in revolutionizing IT operations. Listed below are several benefits associated with implementing AIOps:

  • Collaboration
    AIOps improves collaboration and workflow activities within IT groups and between IT and other business units. With customized reports and dashboards, teams can understand their tasks and requirements quickly.

  • Improved Business ROI IT Productivity
    Businesses witness improvements by decreasing mean time to repair--preventing outages by predicting incidents and removing repetitive manual tasks with automation. AIOps helps to optimize the overall capacity of your team with increased output and cost reduction.

  • Digital Transformation Success
    Companies face many challenges on their way to digital transformation. As most of the companies are moving towards a digital-centric approach, organizations can add more business value by saving tons of time and effort, and focus on innovation. AIOps adoption can help organizations get end-to-end visibility into infrastructure and applications.

  • Improve Performance Monitoring and Service Delivery
    Leveraging AIOps helps to predict performance issues and forecast resource utilization. It focuses on the most likely source of a problem with probable cause analytics. It helps to identify problems driving incidents with clustering and anomaly detection. Artificial intelligence (AI), machine learning (ML), and automation can lift the burden off the help desk team by assessing the patterns of support tickets, usage patterns, and information regarding user interaction.

Conclusion
AIOps is disrupting IT operations management and will continue to do so moving forward. AIOps is used today to avert problems, cut costs, improve customer experience, and free IT personnel to focus on tech innovations. AIOps elevates the strategic importance and visibility of IT to the business by improving the performance and availability required no matter how complex environments become.

 

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