Event Categorization Scheme

An Event Categorization Scheme is a structured system for classifying and organizing events based on characteristics like source, severity, type, and impact.

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What Is Event Categorization Scheme

An Event Categorization Scheme is a structured system for classifying and organizing events based on characteristics like source, severity, type, and impact. It provides a consistent taxonomy that helps teams sort, filter, and prioritize the many events generated by IT systems.

Why Is Event Categorization Scheme Important

Proper categorization helps incident teams quickly identify critical events among the noise. It enables efficient routing to appropriate teams, supports trend analysis, and improves reporting. Categorization also helps automate responses based on event types.

Example Of Event Categorization Scheme

A cloud service provider categorizes events by: infrastructure layer (network, compute, storage), severity (critical, major, minor, informational), service impact (customer-facing, internal only), and geographic region. This scheme helps them route alerts to the right specialist teams.

How To Build Event Categorization Scheme

  • Define key categories relevant to your environment
  • Create a hierarchical structure with primary and secondary classifications
  • Document clear criteria for each category
  • Configure monitoring tools to apply categories automatically
  • Train teams on using the categorization system

Best Practices

  • Keep the scheme simple enough for quick decision-making
  • Include business impact as a key categorization dimension
  • Review and refine categories based on incident patterns

Further reading:

Event Correlation

Event Correlation is the process of analyzing relationships between multiple events to identify patterns, causes, and effects.

Event Deduplication

Event deduplication is the process of identifying and eliminating duplicate incident alerts or events to prevent alert fatigue.

Event Enrichment

Event enrichment is the process of adding context and relevant information to raw event data.