Catalog
method#Reliability#Observability#DevOps#Governance

Incident Handling

Structured process for detecting, prioritizing, escalating and resolving IT and operational incidents.

Incident handling is a structured process for detecting, prioritizing, escalating and resolving IT and operational incidents.
Established
Medium

Classification

  • Medium
  • Organizational
  • Organizational
  • Intermediate

Technical context

Monitoring systems (e.g. Prometheus)Alerting tools (e.g. PagerDuty)Communication platforms (e.g. Slack/Teams)

Principles & goals

Define clear roles and responsibilitiesPrioritize fast but documented initial responseEstablish learning loops through post-incident reviews
Run
Team, Domain, Enterprise

Use cases & scenarios

Compromises

  • Missing escalation leads to prolonged outages
  • Unclear communication causes confusion and duplicated work
  • Insufficient post-incident work prevents sustainable improvements
  • Regular post-incident reviews with clear action plans
  • Keep playbooks short, concise and versioned
  • Tune monitoring alerts for relevance and low noise

I/O & resources

  • Monitoring alerts and logs
  • Playbooks/runbooks
  • Escalation and communication matrix
  • Incident ticket with status timeline
  • Post-incident report and action list
  • Updated playbooks and checklists

Description

Incident handling is a structured process for detecting, prioritizing, escalating and resolving IT and operational incidents. It defines roles, communication channels, playbooks and metrics to reduce downtime and optimize recovery time. The approach integrates monitoring, incident management tools and post-incident reviews across teams and the organization.

✔

  • Reduced downtime and faster recovery
  • Improved cross-team coordination
  • Continuous improvement through structured learning

✖

  • Requires maintenance of playbooks and runbooks
  • Effectiveness depends on monitoring and alert quality
  • May create need for organizational alignment and training

  • MTTR

    Average time from detection to recovery.

  • Number of incidents per month

    Counts incidents within a defined period.

  • Time to first response

    Time from alert to first confirmed response by responsible party.

SRE postmortem after production outage

Documented incident with timeline, root cause analysis and action plan to reduce future outages.

Game-day for team resilience

Simulated outage to validate playbooks, communication channels and recovery times.

Escalation to incident commander

Clearly defined escalation chain with an incident commander for critical, prolonged incidents.

1

Inventory existing alerts and escalation paths

2

Create and test playbooks for critical scenarios

3

Introduce on-call roles, training and game-days

4

Identify automation options and introduce them incrementally

⚠️ Technical debt & bottlenecks

  • Incomplete observability for critical services
  • Outdated playbooks that don't match architecture
  • Manual workarounds that accumulate technical debt
CommunicationToolingTraining
  • Playbooks treated as documentation without testing
  • Full centralization of all decisions for every incident
  • Automatically closing tickets without verification
  • Too many poorly prioritized alerts
  • Unclear escalation levels
  • Lack of stakeholder involvement
On-call management and triage skillsTechnical diagnosis and debuggingCommunication under pressure
Mean Time to Detect (MTTD)Mean Time to Recover (MTTR)Service dependencies and fault tolerance
  • • Available on-call resources
  • • SLA and compliance requirements
  • • Integration capability of monitoring tools