Introduction 

The AIOps Market size is estimated at USD 27.24 billion in 2024, and is expected to reach USD 79.91 billion by 2029, growing at a CAGR of 24.01% during the forecast period (2024-2029). 

For years, innovation has remained central to enhancing ITOM processes and cost-efficiency. Various monitoring tools providing comprehensive network oversight, immediate alerts, and threshold-based setups to identify anomalies have streamlined ITOM for businesses. Yet, the accelerated pace of change, the influence of groundbreaking technologies and the shift towards digital transformation in organizations are challenging the traditional reactive capacities of separate network monitoring systems. 

The consolidation of ITOM silos has become achievable thanks to the emergence of AI-powered ITOM, known as AIOps. AIOps spearheads intelligent decision-making based on data in contemporary IT setups. Through the fusion of machine learning and expansive data analytics, AIOps facilitates proactive performance monitoring, pattern identification, event correlation, predictive analysis, and improved incident management.  

Adoption Accelerators Of AIOps 

  • IT faces a data deluge: The challenge of deciphering the abundant flow of network metrics and monitoring data generated by deployed monitoring solutions. 
  • The expanding tool complexity: Fragmented and isolated sources of truth arising from endeavours to attain comprehensive visibility across the entire network stack. 
  • Alert fatigue: The necessity to isolate signals from event noise. 
  • Rising demands: Urgency for swift infrastructure problem-solving and consistent service availability, emphasizing the necessity to minimize mean time to discovery (MTTD), mean time to repair (MTTR), ensure a high mean time between failures (MTBF), and reduce mean time to failure (MTTF). 
  • Need for data-driven decisions: Requirement of better data-driven decision-making in the enterprise level. 
  • Proactive network issue prediction: Forecasting problems prior to their interference with network operations. 
  • Enhancing network agility and speed: Helping for heightened network change speeds while delivering improved flexibility. 
  • Automated incident resolution: Automated resolution and response to incidents. 
  • Resource efficiency for cost savings: Efficient utilization of resources leading to cost savings. 

Why to choose UnityOne AIOps ? 

In today’s Hybrid Hybrid Multicloud Management System and digital economy establishing an agile, resilient, and cost-effective IT infrastructure has become essential for enterprises. UnityOne AIOps is crafted to offer a comprehensive approach to scale businesses through technology, aligning current operating models, information capabilities, operational efficiency, and productivity. UnityOne introduces a five-step AIOps solution approach. 

UnityOne AIOps framework incorporates an ideal balance of human input, improving existing operational processes and procedures instead of handling repetitive, high-volume tasks. 

  • Unified Discovery: Automatically scan, discover, consolidate, and identify all the infrastructure components of hybrid, Hybrid Multicloud including physical machines, VMs, databases and infra-applications. This helps organizations for infrastructure assessment and cloud migration. 
  • Unified Monitoring: UnityOne unites all the individual silos of infrastructure management and offers a truly unified IT infrastructure management solution and single pane of glass view. It reduces the complexity of silo-based approach for monitoring, in which each technology tier is monitored independently by a different tool. It eliminates the management of multiple consoles, high volume of alerts and manually comparing metrics from different sources. It offers One-stop visibility of dataflows across all platforms and actionable insight to diagnose performance issues across the entire IT environment of hybrid and Hybrid Multicloud environments, deep diagnostics and actionable insight needed to troubleshoot issues.  
  • Analyze: UnityOne AI/ML Event management solution brings Unified Central Alert management for your entire environment, cut through event noise reduction to create actionable signals, identify service outages and degradations rapidly, remediate service and infrastructure issues accurately and drive continuous improvement in service quality. 
  • Predict: UnityOne AIOps assist in correlate and cluster events with real-time machine learning models, allowing users to reduce noise, and focus on critical issues thereby reducing the total number of incidents. It detects anomalies to predict and proactively optimize resource outages before they occur. It also analyses trends in resource utilization and forecast when additional servers may be needed to accommodate increasing demand. 
  • Execute: UnityOne AIOps platform provides auto-remediation by relying on event-triggers and automated kick-off remediation processes when issues arise. This also includes the automation of day-to-day tasks, for example, provisioning virtual machines, or distributing workloads in real-time. This would reduce the occurrence of manual errors while optimizing systems and processes to prevent issues such as delays, workload failures and outages. 

UnityOne AIOps Is the Key to Operational Transformation  

  • Unified Perspective: A consolidated outlook of the complete IT landscape, enabling the eradication of tool complexities and the proactive identification and resolution of issues. It centralizes data from various monitoring tools, leveraging AI and machine learning to detect anomalies, forecast trends, monitor, track, analyze events, generate reports, and execute necessary actions for issue resolution, fostering enhanced collaboration and efficiency. 
  • Streamlined Operations: Concentrating on recognizing and eradicating repetitive tasks by automating them to generate greater efficiencies. This approach enables IT teams to prioritize new enhancements and developments instead of dedicating time to repetitive tasks. 
  • Faster Root Cause Analysis through Proactive Performance Monitoring: By automating IT operational tasks, this approach decreases the time required to identify the root cause of issues and take proactive measures for resolution, focusing solely on actionable tickets derived from alarms. 

Conclusion 

AIOps isn’t a one-size-fits-all solution. Organizations require a tailored business-specific strategy to effectively implement AIOps and achieve their intended advantages. Beyond just a “modernization” approach, AIOps should represent a “value-centric implementation” within organizations. Our market strategy for AIOps revolves around staying pertinent and thriving in the digital sphere. We provide a comprehensive suite of full-stack solutions spanning from infrastructure discovery and monitoring to AI/ML event management. We are framing our offerings around a persona-driven approach, signalling a substantial departure from traditional methods, and emphasizing AIOps-based transformation themes. This shift also empowers IT Operations to significantly impact today’s digital enterprises by focusing on resolving business problems rather than solely on technology. 

Published On: February 19th, 2024 / 4.8 min read / Views: 29 / Categories: AIOps /

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About the Author: Disha Mukherjee

As a seasoned content strategist at UnitedLayer, Disha brings over 8 years of experience in the B2B IT sector, specializing in hybrid and private cloud solutions. With a strong foundation in digital marketing, social media, and a passion for emerging technologies like AI/ML and big data, she is dedicated to crafting impactful content that drives business growth and technological innovation.

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