The IT infrastructure is integrated with enormous monitoring tools such as Nagios, Zabbix and more. The goal of the monitoring tool is to allow enterprises to find and resolve problems proactively before it affects the customer experience. These tools monitor servers, networks, applications, and cloud. When any abnormality is found during the monitoring period, these tools will generate events to prevent problems that affect performance. Each monitoring tool generates a siloed stream of data — the same issue will be reported by different monitoring tools.
Enterprises are left manually to correlate the events, remove redundant data and identify the business impact. Even though when the team of staffs involved doing this task, an enormous noise – thousand of events are generated for a single issue that may not impact the business will be generated. This may result in the low mean time to repair, long service outages, and businesses will be overrun by competitors.
What is event management?
Event management is a process that reduces event noise generated by the monitoring tools with the help of Artificial intelligence for IT operations (AIOps). AIOps applies predictive analysis and machine learning techniques that reduce the time and effort to correlate events as it adapts to any evolving IT infrastructure.
Event management captures all the events obtained from existing infrastructure monitoring tools to process through filers to normalize and de-duplicate the events and generate alerts by reducing the event noise.
Integration with monitoring tools
Root cause analysis
Event management correlates alerts with IT services by providing a view of impacted services that help to detect the root causes and prioritizes issues appropriately. It can easily detect the times that have upstream and downstream dependencies. Automated root cause analysis provides service issues and also reduces resolution time.
Detect and prevent service outages
With advanced machine learning algorithms, you can detect the root causes and prevent service outages. The operational metrics that are collected from monitoring tools are used to detect performance that causes service outages.
Alert enrichment reduces the meantime to repair by solving issues by combining all essential information required to address the issue in one console. While opening an alert, details such as description, priority, severity, activity, impacted services and timeline required to solve secondary related issues are provided.
Event management comes with an auto-remediation technique that automates the responses to alerts by providing faster resolution to issues. It can fix or remediate issues by validating, investigating and diagnosing the problem.
Improved service availability
- Reduce service outages by applying advanced machine learning techniques to minimize noise, detect service issues, and provide knowledgeable information for speedy resolution.
Drive value from existing tools
- Aggregates events captured by monitoring tools by integrating them into third party connectors, REST API, etc.
Detect the root causes of service issues
- Transform the events into actionable alerts that pinpoint the root causes of the service issues. The data collected by the alert enrichment technique helps to reduce MTTR (Mean Time to Repair).
Boost employee productivity
- Improves employee productivity by reducing thousands of redundant and inaccurate alerts.
Detect issues beforehand
- IT Ops team can detect issues before it affects business performance and helps to quickly prioritize and detect business-critical problems.
Autointelli AIOps solution – event management and correlation reduces noise level, eliminates performance deterioration, and improves customer experience. It can handle bulk events at ease, auto remediates alerts, and escalates the tougher alerts to the right person for on-time resolution.