Why Mid to Large Enterprises Need to Align With an AIOps Approach to IT Infra Management

According to Gartner, “AIOps combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.”

Gartner 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.”

AIOps can be used to monitor and manage a wide range of IT infrastructure, including networks, servers, storage, and applications. It can also be used to manage cloud-based infrastructure and services. AIOps can help enterprises improve their IT operations’ efficiency and reduce the cost of IT management. AIOps can also help to improve the quality of service for IT customers and end-users. AIOps platforms use data collected from multiple IT systems and AI and ML algorithms to analyze the data and identify potential issues. The data collected by the AIOps platform is used to generate automatic alerts. The AIOps platform can also provide recommendations for improving the performance of IT systems. AIOps platforms are available from several vendors, each one consisting of essential features to enhance enterprise infrastructure management.

Should mid-large enterprises align with an AIOps approach to IT infra management?

Enterprises must align with an AIOps approach to manage IT Infra for a variety of reasons.

AIOps can help these enterprises improve operational efficiency, better manage risk and compliance, and drive down costs. Operational efficiency is a key benefit of AIOps. By automating and integrating data from disparate systems, AIOps can help enterprises improve their ability to identify and resolve problems quickly and efficiently.

In addition, AIOps can help reduce the number of false positives and negatives generated by monitoring systems, which can help reduce operational costs. AIOps can also help enterprises of all sizes better manage risk and compliance. AIOps can help these enterprises identify and resolve potential risks and compliance issues before they impact the business by providing a more complete and accurate picture of the IT infrastructure.

Finally, AIOps can help drive down costs by automating many tasks associated with managing the IT infrastructure. By reducing the need for manual intervention, AIOps can help enterprises save on labor costs and improve overall efficiency.

AIOps can help move an organization from a proactive to a predictive state by providing a real-time view of the entire IT environment, detecting issues early, and providing recommendations for remediation. Additionally, AIOps can help reduce MTTR and improve SLAs.

AIOps platforms use data from multiple IT data sources, including monitoring, logging, and performance data, to detect anomalies. These anomalies are caused by hardware or software failures, configuration changes, or user errors. AIOps platforms use ML algorithms to detect anomalies, including clustering, outlier detection, and time-series analysis. Once an anomaly is detected, the AIOps platform can generate an alert sent to the appropriate IT staff.

Applying big data analytics and ML to IT operations data helps discover hidden relationships between discrete systems and processes, and all the variables. AIOps helps identify and diagnose problems in real-time to predict and prevent future issues. In addition, AIOps provides valuable insights into the behavior of systems and processes, which can be used to improve the design of future systems.

Traditional capacity planning methods are often based on intuition and experience, which can lead to errors in judgment. On the other hand, AI can provide a more objective and data-driven approach to capacity planning. By analyzing past patterns and trends, AI can help businesses make more accurate predictions about future demand. This enables companies to utilize their resources better and avoid over- or under-capacity. In addition to improving accuracy, AI can help businesses save time and money on capacity planning. By automating the process, enterprises can free up resources that can be better spent on other tasks. AI can also help enterprises to keep track of a more significant number of variables and identify patterns that go unnoticed by a human workforce.

AIOps predictive analytics help forecast the use of resources and performance issues. AI/ ML and automation can make it easier for the service desk by assessing the patterns of support tickets, usage, and customer interaction. It enables anomaly detection and identifies the problems to fix issues proactively.

Enterprises see improvements by decreasing the Mean Time to Repair (MTR), eliminating outages with predictive insights, and removing repetitive manual tasks with automation. AIOps helps optimize the team’s overall capacity with increased output and cost reduction.

Enterprises from all industries are transitioning to digital-first operations. AIOps adds business value with a digital solution that reduces time and labor leaving your teams to focus on other business areas, including innovation and expansion. AIOps enables end-to-end visibility into an enterprise’s applications and infrastructure.

AIOps is disrupting IT operations management like never before. The technology in AIOps takes system availability and performance to a new level regardless of the complexity of operations.

AIOps offers real-time insights from customer activity and predictive analytics that enable data-driven decisions. Understanding customers’ trends help product and service delivery, leading to a richer customer experience.

With the right AIOps platform, IT teams can leverage automation, AI, and ML for cost optimization and improved security. Adopting AIOps can be a game-changer for mid-large enterprises as they embark on their journey towards digital transformation, and leveraging it for better infrastructure management can help streamline business operations even as it improves the bottom line.