AIOps: A System Detection and Prevention Technology
AIOps technology uses technologies including machine learning and big data to provide predictive insights and automates remedial solutions for the issues detected. Increasing implementation of systems to automate processes, increases the chances of failure and leads to downtime resulting in business loss. Therefore, organisations are implementing this technology to identify issues in advance and take probable action to prevent incidents, resulting in reduced downtime including outages. Additionally, implementation of hybrid architecture, poses challenges for domain centric monitoring tools, thereby generating need for AIOps technology which can provide multi-layer monitoring capability.
AIOps is a combination of several technologies including Big Data, analytics, automation, machine learning and visualisation. Data generated through metrics, log files, incident management systems are organised and categorised using Big Data. Analytics is used to analyse raw data and gain insights with visualisation helping present gained insight in an effective manner. Machine learning helps in improving outcome with every iteration.
AIOps platform allows IT teams to spend significantly less time on regular alerts. It helps in continuous monitoring thereby allowing IT team to work on more complex issues. As this technology can understand cause and effect relationship by analysing historical data, it helps in root cause analysis thereby increasing identification and resolution for problems. This technology enhances the workflow among several business units, by providing centralised reports and dashboards resulting in effective communication among business units irrespective of domain. This technology is integrated with analytics and machine learning, hence requiring a significant amount of data, algorithm learning and time to function autonomously and provide effective results.
The implementation of AIOps is solely dependent on the business need and hence gradual implementation is recommended. Furthermore, selection of implementing model including on-premise installation needs to align with organisation’s requirement. The users need to have good understanding of issues based on which this technology will be trained for best results.
Some of the vendors in the market
– Mr. Rahul Kumar Pandey