Software Development

Why AIOps is the Next Big Thing in IT Operations?

AIOps platform market size is growing exponentially. According to Markets and Markets latest survey, the AIOps market size will reach USD 11.02 billion by 2023 and USD 237 billion by 2025. But, what is AIOps, what it is designed to do, how it is developing, and why AIOps is the next big thing in IT operations? If you are also looking answers for such questions, then your search ends here. Have a look:

The ‘What’ Of AIOps

AIOps is the application of Artificial Intelligence (AI) to IT operations. It is Continuous Integration (CI) and Continuous Deployment (CD) for core IT functions. AIOps combines machine learning, big data analytics, and various AI technologies to automate the challenging IT tasks. Using the IT data collected from algorithm analysis, AIOps check assets and gain visibility into dependencies within or outside of the IT systems. It helps IT Ops and DevOps teams work smarter and faster. It also denotes a shift from siloed data to a more dynamic business environment.

With AIOps, Ops teams can tame the immense complexity and quantity of data. This prevents outages, maintains uptime, and match endless service assurances. By 2022, 40% of all large enterprises will integrate big data and ML functionalities to replace and support monitoring, service desk, and automation methods (Source: Analytics India Mag).

AIOps Benefits

The prime advantage of embracing AIOps is that it provides momentum and agility to the Operations Team. This helps to ensure the uptime of vital services and timely delivery for better customer experience. Other AIOps benefits:

  • Data-Driven Decision Making

AIOps brings key ML techniques to the IT operations and helps with decision making. It enables the data-driven approach and automates responses. Such automated responses eradicate human errors and data errors. AIOps lets the organization focus more on resolution than detection.

  • Event Noise Reduction

Machine learning technology has great learning skills. With AIOps, using ML, the operations team can identify the error pattern and take immediate counteraction against the discrepancy.

  • Immediate Cause Identification

AIOps platform enables deploying correlation analytics. This helps teams to identify errors and its root cause by correlating monitoring data pointers. As a result, a team can resolve issues quickly and efficiently.

  • Predicting Event Warning

Early error detection is as necessary as fixing it. AIOps with advanced analytics can’t only detect the anomalies in the application performance, but also fix it efficiently for better customer experience.

  • Enhanced Customer Experience

AIOps can predict underlying availability and performance issues by collecting and analyzing data. It accelerates deployment and problem-solving processes.

Conclusion

AIOps is here to stay. It can potentially replace the traditional IT approach with streamlined automation and better efficiency. At Successive Digital, we integrate the AIOPs, DevOps, and Agile procedures across the software lifecycles to improve operational efficiency and foster innovation. We deliver applications at the pace of business with comprehensive AIOps and DevOps services.

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