AIOps technology is predominantly using cognitive capability for identification, reporting, and troubleshooting of the issues impacting critical applications and infrastructure. In establishing a sustainable business strategy to offer cost effective solutions, organisations are migrating towards digital platforms, hybrid infrastructure and cloud services which integrates entire IT infrastructure of an organization into one single platform resulting in significant cost savings.
Several verticals including BFSI, Telecom, Healthcare are implementing AIOps technology to leverage cognitive capability thereby improving IT operations by identifying root cause analysis and reducing mean-time-to-resolution.
Some of the application areas of AIOps technology are as follows:
- Capacity Management – Increasing deployment of cloud and hybrid infrastructure is creating complexities in effectively planning capacity utilization. AIOps helps in reducing this complexity by analysing machine data and suggest the supported storage, network configuration, and other associated assets for effective usage
- Anomaly Detection– Generation of logs from applications and infrastructure, helps in identification of outliers by using AIOps technology. Hence it can detect any abnormal behaviour in real-time
- Storage Management – Production workload management is dependent on the storage capacity of the organisation thereby making it a critical component. AIOps technology implementation, storage can be proactively managed for effective usage, by leveraging predictive maintenance. It autonomously adds additional volume in case of a reduced IOPS (Input/output Operations Per Second) due to limited storage availability
- Incident Management – AIOps uses predictive maintenance to generate alerts for forthcoming incidents related to organisation’s critical infrastructure, hence reducing outage instances
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AIOps technology is predominately impacted by factors including digital transformation, hybrid infrastructures, cloud migrations, and need for protecting critical infrastructures which may reduce organisation’s profitability. However limited penetration in SMEs and availability of skilled workforce are some of the challenges being face by businesses while implementing this technology. In the coming years, increasing implementation of artificial intelligence and automation will help in convergence of AIOps with RPA. This would enable organizations to shift towards full-scale digital transformation as RPA and AIOps both have their own capacity to resolve challenges associated with digital transformation.
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Conclusively, AIOps which is the convergence of AI and ITOps (IT Operations), will enable organisations to shift from traditional infrastructure management to proactive management. This will have an impact on enterprise’s data centre and cloud infrastructure management. Organizations are increasingly implementing this technology and over 40% of the large organizations are expected to implement this technology by 2022.
– Rahul Kumar Pandey
ICT – Research Analyst