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Incident Types

Incident Types in Harness AI SRE provide a standardized framework for classifying and managing different categories of incidents. By defining incident types, teams can ensure consistent response procedures, appropriate field configurations, and automated workflows tailored to specific incident scenarios.

Overview

Incident Types help you:

  • Standardize incident classification across your organization
  • Define custom fields and default values for different incident categories
  • Establish consistent response procedures and workflows
  • Automate incident creation with pre-configured templates
  • Associate relevant runbooks and response procedures
  • Ensure appropriate escalation paths and team assignments

Key Features

Standardized Classification

  • Custom incident type creation for organization-specific needs
  • Consistent incident handling across teams and services
  • Automated incident routing based on type classification

Response Procedure Configuration

  • Set default values and custom fields to streamline incident creation
  • Configure field validation and requirements (required vs optional) per incident type
  • Associate runbooks with specific incident types for automated response procedures
  • Integrate with monitoring tools and alert rules for automatic incident creation
  • Create standardized workflows combining custom fields and runbook automation

Template Management

  • Pre-configured incident creation forms
  • Standardized incident descriptions and procedures
  • Consistent data collection across incident types
  • Streamlined incident reporting and analysis

Configuration Steps

Follow this interactive guide to create and configure incident types with custom fields and runbook associations.

Best Practices

Incident Type Design

  • Create specific types for different service categories
  • Use clear, descriptive names that teams will understand
  • Align incident types with your organization's service structure
  • Consider severity levels and response time requirements

Field Configuration

  • Include only essential fields to avoid form fatigue
  • Set sensible default values to speed up incident creation
  • Make critical fields required to ensure data completeness
  • Use custom fields sparingly and only when necessary

Runbook Association

  • Link relevant runbooks to automate response procedures
  • Ensure runbooks are up-to-date and tested regularly
  • Consider different runbooks for different severity levels
  • Document runbook usage and maintenance procedures

Workflow Integration

  • Align incident types with your alert rules and monitoring setup
  • Configure automatic incident creation for critical alerts
  • Test incident type configurations with sample scenarios
  • Train teams on proper incident type selection and usage

Common Incident Types

Security Incidents

  • Purpose: Handle security breaches, vulnerabilities, and threats
  • Key Fields: Threat level, affected systems, containment status
  • Runbooks: Security response procedures, forensic analysis

Performance Issues

  • Purpose: Address application and infrastructure performance problems
  • Key Fields: Performance metrics, affected services, user impact
  • Runbooks: Performance troubleshooting, scaling procedures

Infrastructure Outages

  • Purpose: Manage hardware failures, network issues, and service disruptions
  • Key Fields: Affected infrastructure, estimated recovery time, backup status
  • Runbooks: Failover procedures, recovery workflows

Application Errors

  • Purpose: Handle software bugs, deployment issues, and application failures
  • Key Fields: Error messages, affected features, rollback requirements
  • Runbooks: Debugging procedures, rollback workflows

Benefits

  • Consistency: Standardized incident handling across all teams and services
  • Efficiency: Pre-configured fields and workflows reduce response time
  • Automation: Automated incident creation and response procedure execution
  • Visibility: Clear incident categorization for reporting and analysis
  • Compliance: Structured data collection for audit and regulatory requirements
  • Learning: Historical data analysis for continuous improvement

Next Steps