In some event correlation tools, this will trigger a response such as a recommendation of further investigation, escalation or automated remediation, allowing IT administrators to better engage in troubleshooting tasks. Once the correlation process is complete, the original volume of events will have been reduced to a handful that require some action. (e.g., events on one device are examined to determine its impact on every device in the network). Root cause analysis: The most complex step of the process, event interdependencies are finally analyzed to determine the root cause of the event.Normalization: Normalization converts the data to a uniform format so the event correlation tool’s AI algorithm interprets it all the same way, regardless of the source.Often, there is only a single issue to address, despite multiple alerts. 100 people receive the same error message, generating100 separate alerts). Duplication can happen for many reasons (e.g. ![]() Deduplication: The tool identifies duplicate events triggered by the same issue.This step may alternately be performed before aggregation. Filtering: Events are filtered by user-defined criteria such as source, timeframe or event level. ![]() ![]() Aggregation: Infrastructure monitoring data is collected from various devices, applications, monitoring tools and trouble ticket systems and fed to the correlator.The entire event correlation process generally plays out in the following steps: Consequently, it’s imperative to maintain strong data quality and set definitive correlation rules, particularly when supporting related tasks such as dependency mapping, service mapping and event suppression. Using AI algorithms, the correlator analyzes these monitoring alerts to correlate events by consolidating them into groups, which are then compared to data about system changes and network topology to identify the cause and ideal solutions of the problems. IT event correlation relies on automation and software tools called event correlators, which receive a stream of monitoring and event management data automatically generated from across the managed environment. In the following sections, we’ll look at how event correlation works, the benefits it offers most organizations, the challenges it addresses and how you can get started using event correlation to better understand your infrastructure data. Ultimately, these techniques enable teams to more easily identify and resolve incidents and outages, conduct performance monitoring and help improve the availability and stability of the infrastructure. Because a typical enterprise processes thousands of events each day, correlating all of them to determine which are relevant represents a significant challenge for IT teams.Īs an answer to this issue, IT event correlation software ingests infrastructure data and uses machine learning to recognize meaningful patterns and relationships. Many of these events are normal and benign but some will signify a problem within the infrastructure. An event is any piece of data that provides insight about a state change in that infrastructure, such as a user login. Using an event correlation tool can help organizations monitor their systems and applications more effectively while improving their uptime and performance.Įnterprise IT infrastructures generate huge volumes of data in various formats, produced by servers, databases, virtual machines, mobile devices, operating systems, applications, sensors and other network components. ![]() IT event correlation automates the process of analyzing IT infrastructure events and identifying relationships between them to detect problems and uncover their root cause.
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