ITSM (IT Service Management) AIOps is a combination of IT service management and AI (Artificial Intelligence) operations. ITSM AIOps applies AI techniques to automate and streamline IT service management processes, such as incident management, change management, problem management, and service request management. It can help IT teams to detect and diagnose IT issues faster, predict and prevent incidents, and automate routine tasks.
Why AIOps in ITSM?
AIOps (Artificial Intelligence for IT Operations) is required in ITSM (IT Service Management) to help IT teams cope with the increasing complexity of modern IT environments. Today’s IT infrastructures are made up of multiple technologies, platforms, and applications, and generate massive amounts of data from logs, metrics, events, and other sources. IT teams need to monitor and manage this data in real-time to ensure that IT services are delivered smoothly and effectively.
Predictive AIOps Offerings
Intelligent alerts and Incident management
Provides intelligent alerts by using machine learning algorithms to analyse data and identify patterns that may indicate an incident is about to occur. These engines can also streamline incident management by automatically categorizing incidents, prioritizing them based on their impact and urgency, and suggesting resolutions based on past incidents.
Reduction in event noise
Using machine learning algorithms to analyze data and identify patterns that indicate a real incident, which reduces the number of false alarms and noise in the system. It can also automate the process of event correlation, which reduces the time and effort required by IT staff to manually correlate events and identify their root cause.
Using machine learning algorithms to analyze data and identify anomalies that deviate from normal behavior. This can help to detect security threats, performance issues, and other problems that may impact IT service delivery.
Service Desk Automation
Automating routine tasks, such as incident categorization and prioritization, helps IT staff to focus on more complex issues. It also provides faster and more accurate incident resolution by using machine learning algorithms to analyze data and provide insights that can be used to optimize ITSM processes.
Predictive Analytics and Insights
Using machine learning algorithms to analyze historical data and identify patterns that can be used to predict future incidents and issues. It can also provide insights into ITSM processes and performance, which can be used to optimize IT operations and improve service delivery.
Root Cause Analysis Automation
Leveraging machine learning algorithms to analyze data and identify the underlying cause of incidents helps to reduce the time and effort required by IT staff to manually investigate and identify the root cause of incidents, allowing them to focus on more complex tasks and improving the overall efficiency of ITSM operations.
Predictive Incident Management – Process Flow
CriticalRiver boosts US tech firm with Service Desk Automation and Predictive Insights
Explore how CriticalRiver helped an American network test, measurement, and assurance technology company, by providing expertise in Service Desk Automation and Predictive Actionable Insights.
- 30% increased productivity of IT staff
- ITSM processes optimization
- 10% reduction in noise achieved through automated recommendations