Incidents
An unplanned disruption to IT services that reduces performance or availability, impacting business operations. Detected through user reports or automated monitoring.
What Is an Incident?
An incident is defined as any unplanned interruption to an IT service or a reduction in the quality of that service. The ITIL framework describes incidents as events where a service is not functioning as expected or its performance is degraded, impacting usersβ ability to carry out normal business activities.
Core Characteristics:
| Characteristic | Description |
|---|---|
| Unplanned | Unscheduled events disrupting normal operations |
| Service Impact | Any interruption or quality reduction affects business |
| Detection Methods | User reports, technical staff, automated monitoring |
| Prevention Focus | Can be reported before SLA breach to minimize impact |
Common Incident Examples:
| Category | Examples |
|---|---|
| Infrastructure | Server outages, database crashes, storage failures |
| Network | WAN/LAN disruptions, VPN failures, connectivity issues |
| Applications | Software crashes, error messages, performance degradation |
| Hardware | Printer failures, workstation breakdowns, device malfunctions |
| Security | Malware infections, unauthorized access, data breaches |
Incidents vs. Problems vs. Service Requests
Understanding the distinctions is essential for efficient resource allocation, SLA compliance, and user satisfaction.
Comparison Matrix
| Aspect | Incident | Problem | Service Request |
|---|---|---|---|
| Definition | Unplanned service interruption or quality reduction | Root cause of incidents | Formal request for standard change or access |
| Nature | Something broken or not working | Underlying cause, often hidden | User needs resource or information |
| Urgency | Requires immediate attention | May not be urgent, needs analysis | Follows standard timelines |
| Focus | Rapid restoration | Root cause analysis and permanent fix | Fulfillment per service catalog |
| SLA Metric | Response and resolution time | Time to permanent solution | Fulfillment time |
| Examples | Server crash, network outage | Faulty router causing repeated outages | Password reset, software installation |
| Staff Involved | Service desk, operations | Problem management, specialists | Service desk, fulfillment teams |
| Documentation | Incident ticket with resolution | Problem record with analysis | Request ticket with approval |
Classification Decision Tree
Is it unplanned?
β
Yes β Is service degraded/interrupted?
β
Yes β INCIDENT
β
Multiple similar incidents?
β
Yes β Create PROBLEM record
β
No β Is it a standard request?
β
Yes β SERVICE REQUEST
Why Correct Classification Matters
Impact of Misclassification:
| Issue | Consequence | Solution |
|---|---|---|
| Service Requests as Incidents | Wasted support resources, missed SLAs | Clear classification criteria and training |
| Incidents as Service Requests | Delayed critical issue resolution | Automated priority assessment |
| Incidents as Problems | Service restoration delayed | Focus on rapid restoration first |
| Problems as Incidents | Root cause never addressed | Pattern recognition and analysis |
Incident Management Lifecycle
Complete Process Flow
1. Detection and Logging
β
2. Classification and Categorization
β
3. Prioritization
β
4. Initial Diagnosis
β
5. Escalation (if needed)
β
6. Investigation and Resolution
β
7. Recovery and Validation
β
8. Closure
β
9. Documentation and Review
Stage 1: Detection and Logging
Detection Methods:
| Method | Description | Response Time | Coverage |
|---|---|---|---|
| User Reports | Service desk tickets, calls, emails | Minutes to hours | Known issues |
| Automated Monitoring | System alerts, performance metrics | Seconds to minutes | Infrastructure |
| Proactive Detection | Predictive analytics, anomaly detection | Before impact | Emerging issues |
Logging Requirements:
| Data Element | Purpose | Example |
|---|---|---|
| Timestamp | Track response time | 2025-12-18 14:23:15 |
| Reporter | Contact for updates | jane.smith@company.com |
| Affected Service | Identify scope | Email System |
| Description | Understand issue | βCannot send emails, error 550β |
| Business Impact | Determine priority | 200 users affected |
| Symptoms | Aid diagnosis | Timeout after 30 seconds |
Stage 2: Classification and Prioritization
Priority Matrix:
| Impact β / Urgency β | High Urgency | Medium Urgency | Low Urgency |
|---|---|---|---|
| Critical Impact | Priority 1 (P1) | Priority 2 (P2) | Priority 3 (P3) |
| High Impact | Priority 2 (P2) | Priority 3 (P3) | Priority 4 (P4) |
| Medium Impact | Priority 3 (P3) | Priority 4 (P4) | Priority 5 (P5) |
| Low Impact | Priority 4 (P4) | Priority 5 (P5) | Priority 5 (P5) |
Impact Assessment:
| Level | User Impact | Business Effect | Examples |
|---|---|---|---|
| Critical | 500+ users or entire service | Revenue loss, compliance violation | Core business system down |
| High | 100-500 users or key function | Significant productivity loss | Email system outage |
| Medium | 10-100 users or workaround available | Moderate inconvenience | Single printer failure |
| Low | Individual user, no workaround needed | Minimal impact | Cosmetic software issue |
Urgency Factors:
| Factor | High | Medium | Low |
|---|---|---|---|
| Deadline | Immediate/critical | Within 24 hours | No specific deadline |
| Workaround | None available | Complex workaround | Easy workaround |
| User Type | Executive, external customer | Management, key staff | General staff |
| Time Sensitivity | Peak business hours | Normal hours | Off-hours |
Stage 3: Initial Diagnosis and Triage
Diagnostic Workflow:
Receive Incident
β
Search Knowledge Base
β
βββ Known Issue? β Apply Solution β Test β Close
β
βββ Unknown? β Perform Basic Troubleshooting
β
βββ Resolved? β Document β Close
β
βββ Unresolved? β Escalate to Specialist
First-Line Support Actions:
| Action | Purpose | Tools |
|---|---|---|
| Knowledge Base Search | Find existing solutions | ITSM, Wiki |
| Basic Troubleshooting | Resolve simple issues | Scripts, checklists |
| Information Gathering | Aid escalation | Diagnostic tools |
| Workaround Provision | Temporary relief | KB articles |
Stage 4: Escalation
Escalation Types:
| Type | Trigger | Target | Timeline |
|---|---|---|---|
| Functional | Specialized skills needed | Technical team | Immediate |
| Hierarchical | SLA breach risk | Management | Before breach |
| Automatic | P1/P2 incident | On-call engineers | < 5 minutes |
| Request-based | User demands | Higher authority | As needed |
Escalation Criteria:
| Priority | First Escalation | Second Escalation | Executive Notification |
|---|---|---|---|
| P1 | 15 minutes | 30 minutes | 1 hour |
| P2 | 1 hour | 4 hours | 8 hours |
| P3 | 4 hours | 1 day | N/A |
| P4 | 1 day | 3 days | N/A |
Stage 5: Investigation and Resolution
Resolution Approaches:
| Approach | Description | Use Case | Time |
|---|---|---|---|
| Known Solution | Apply documented fix | Repeated issues | Minutes |
| Workaround | Temporary bypass | Rapid restoration needed | < 1 hour |
| Standard Fix | Common resolution | Typical incidents | Hours |
| Custom Solution | Novel resolution | Unique issues | Hours to days |
| Emergency Change | Infrastructure modification | Critical fixes | Expedited |
Stage 6: Recovery and Validation
Validation Checklist:
- Service functionality restored
- Performance within acceptable parameters
- User confirms resolution
- No secondary issues introduced
- Monitoring shows stable state
- Documentation updated
Stage 7: Closure and Documentation
Closure Requirements:
| Requirement | Purpose | Responsible Party |
|---|---|---|
| User Confirmation | Ensure satisfaction | Service desk |
| Resolution Documentation | Knowledge capture | Resolver |
| Time Logging | SLA tracking | All involved |
| Category/Cause Recording | Trend analysis | Service desk |
| Follow-up Actions | Prevent recurrence | Problem management |
Major Incident Management
Definition and Criteria
Major Incident Characteristics:
| Characteristic | Description |
|---|---|
| Widespread Impact | Affects 500+ users or critical business function |
| Revenue Impact | Direct financial loss or compliance risk |
| Executive Involvement | Requires senior management awareness |
| Media/Public Attention | Potential reputational damage |
| Extended Duration | Likely to exceed standard SLA |
Major Incident Process
Enhanced Workflow:
Major Incident Declared
β
Assemble Incident Response Team
β
Establish Communication Plan
β
β (Parallel Activities) β
β β
Investigation Communication
β β
β β
Resolution Status Updates
β β
Validation Final Notification
β
Post-Incident Review
β
Lessons Learned Documentation
Major Incident Team Roles
| Role | Responsibilities | Skills Required |
|---|---|---|
| Incident Manager | Coordination, decision-making, communication | Leadership, ITSM knowledge |
| Technical Lead | Investigation, resolution planning | Deep technical expertise |
| Communications Lead | Stakeholder updates, messaging | Communication, business acumen |
| Business Liaison | Business impact assessment | Business knowledge |
| Support Specialists | Technical investigation and fixes | Specialized technical skills |
Communication Plan
Stakeholder Update Frequency:
| Priority | Internal Updates | Customer Updates | Executive Updates |
|---|---|---|---|
| P1 | Every 30 minutes | Every hour | Every 2 hours |
| P2 | Every 2 hours | Every 4 hours | Daily |
Communication Templates:
| Template | Purpose | Key Elements |
|---|---|---|
| Initial Notification | Inform of incident | Issue, impact, ETA |
| Status Update | Progress report | Actions taken, current status, next steps |
| Resolution Notice | Closure confirmation | Solution, validation, follow-up |
Automation and AI in Incident Management
Benefits of Automation
| Benefit | Impact | Measurement |
|---|---|---|
| Speed | 60-80% faster resolution | MTTR reduction |
| Consistency | Standardized handling | Quality scores |
| Scalability | 24/7 capacity | Ticket volume handled |
| Cost Efficiency | Reduced labor costs | Cost per ticket |
| Accuracy | Fewer human errors | Error rate |
AI-Powered Use Cases
1. Intelligent Ticket Routing
Incident Detected/Reported
β
AI Classification
- Natural Language Processing
- Historical Pattern Analysis
- Severity Assessment
β
Automatic Routing
- Right team
- Right priority
- Context included
β
Notification Sent
Technologies:
- Natural Language Processing (NLP)
- Machine Learning classification
- Rule-based routing engines
2. Chatbot First-Line Support
Capabilities:
| Capability | Description | Success Rate |
|---|---|---|
| Intent Recognition | Understand user issue | 85-95% |
| Knowledge Base Search | Find relevant articles | 80-90% |
| Guided Troubleshooting | Step-by-step resolution | 60-70% |
| Ticket Creation | Auto-generate for escalation | 95%+ |
| Status Updates | Provide real-time info | 99% |
Example Interaction:
User: "I can't access my email"
Bot: "I'll help you with email access. Let me check a few things:
1. Can you access other systems? [Yes/No]
2. What error message do you see? [Describe]"
β Guides through diagnostics
β Provides solution or escalates
3. Automated Incident Detection
Detection Methods:
| Method | Data Source | Detection Type | Response Time |
|---|---|---|---|
| Threshold Monitoring | Performance metrics | Exceeds limits | < 1 minute |
| Anomaly Detection | ML analysis of patterns | Unusual behavior | 1-5 minutes |
| Log Analysis | System logs | Error patterns | Real-time |
| Synthetic Monitoring | Simulated transactions | Service availability | Continuous |
4. Predictive Incident Management
Approach:
Historical Data Collection
β
Pattern Analysis (ML)
β
Risk Prediction
β
Proactive Action
- Preventive maintenance
- Resource allocation
- Early warning
Benefits:
- Prevent incidents before they occur
- Reduce mean time between failures (MTBF)
- Optimize resource planning
- Improve service availability
Automation Maturity Model
| Level | Description | Automation % | Characteristics |
|---|---|---|---|
| Level 1: Manual | All manual processes | 0-10% | High labor, slow response |
| Level 2: Assisted | Basic automation support | 10-30% | Some routing, alerts |
| Level 3: Partial | Automated triage and routing | 30-50% | Chatbots, auto-routing |
| Level 4: Extensive | AI-driven resolution | 50-70% | Auto-resolution for common issues |
| Level 5: Autonomous | Self-healing systems | 70-90% | Predictive and proactive |
Best Practices
Organizational Best Practices
1. Clear Escalation Policies
| Element | Implementation |
|---|---|
| Criteria | Document when to escalate (time, complexity, impact) |
| Paths | Define escalation hierarchy and contact methods |
| Training | Regular drills and role-playing |
| Authority | Empower responders to make escalation decisions |
2. Knowledge Management
Knowledge Base Structure:
Knowledge Base
βββ Known Errors (Problem Solutions)
βββ Workarounds (Temporary Fixes)
βββ Standard Procedures (Step-by-step)
βββ Troubleshooting Guides (Diagnostic)
βββ FAQs (Common Questions)
Quality Criteria:
- Accurate and tested solutions
- Clear, step-by-step instructions
- Regular updates and validation
- User-friendly language
- Searchable and well-tagged
3. Communication Standards
Communication Principles:
| Principle | Application |
|---|---|
| Timeliness | Update at defined intervals |
| Clarity | Avoid jargon, be specific |
| Completeness | Include impact, actions, timeline |
| Consistency | Use templates and standards |
| Accessibility | Multiple channels (email, SMS, portal) |
Technical Best Practices
4. Monitoring and Detection
Monitoring Coverage:
| Layer | Metrics | Tools |
|---|---|---|
| Infrastructure | CPU, memory, disk, network | Nagios, Zabbix, Datadog |
| Application | Response time, errors, availability | New Relic, AppDynamics |
| Business | Transactions, SLA compliance | Custom dashboards |
| Security | Access attempts, vulnerabilities | SIEM, IDS/IPS |
5. Post-Incident Reviews
Review Process:
Incident Closed
β
Review Meeting (within 48 hours)
β
Analyze:
- Timeline and response
- Root cause
- What went well
- What could improve
β
Action Items:
- Process improvements
- Training needs
- Tool enhancements
β
Document and Share Lessons
Review Questions:
| Category | Questions |
|---|---|
| Detection | How was the incident detected? Could it have been detected earlier? |
| Response | Was escalation timely? Were resources adequate? |
| Communication | Were stakeholders informed appropriately? |
| Resolution | Was the fix effective? Could it have been faster? |
| Prevention | What can prevent recurrence? |
Performance Metrics and KPIs
Key Metrics
| Metric | Definition | Target | Importance |
|---|---|---|---|
| MTTR | Mean Time to Restore/Resolve | < 4 hours | Service restoration speed |
| MTTD | Mean Time to Detect | < 5 minutes | Detection efficiency |
| First Contact Resolution | % resolved at first touch | > 70% | Support effectiveness |
| SLA Compliance | % incidents meeting SLA | > 95% | Service quality |
| Escalation Rate | % requiring escalation | 20-30% | Process efficiency |
| Reopen Rate | % reopened after closure | < 5% | Resolution quality |
| Incident Volume | Total incidents per period | Trend down | Service stability |
Reporting and Dashboards
Executive Dashboard Elements:
| Element | Purpose |
|---|---|
| Critical Incidents | Active P1/P2 incidents |
| SLA Status | At-risk and breached SLAs |
| Trends | Volume, MTTR, category trends |
| Top Issues | Most common incident types |
| Team Performance | Resolution rates by team |
Challenges and Solutions
Common Challenges
| Challenge | Impact | Solution |
|---|---|---|
| Alert Fatigue | Important issues missed | Tune thresholds, consolidate alerts |
| Misclassification | Resource waste, SLA misses | Training, decision trees, automation |
| Communication Gaps | Stakeholder dissatisfaction | Templates, regular updates, tools |
| Knowledge Silos | Inconsistent resolution | Centralized KB, documentation culture |
| Tool Sprawl | Integration complexity | ITSM platform consolidation |
| Staff Burnout | High turnover, errors | Automation, workload management |
Integration Challenges
Common Integration Points:
| System | Integration Purpose | Challenge |
|---|---|---|
| Monitoring Tools | Auto-ticket creation | Alert correlation |
| CMDB | Impact assessment | Data accuracy |
| Communication | Notifications | Multiple channel management |
| Knowledge Base | Solution retrieval | Search relevance |
| Change Management | Change correlation | Process alignment |
Industry Standards and Frameworks
ITIL Framework
ITIL Incident Management Principles:
| Principle | Description |
|---|---|
| Service Restoration | Focus on rapid restoration, not root cause |
| SLA Compliance | Meet agreed service levels |
| Continuous Improvement | Learn from incidents |
| User Focus | Minimize business impact |
NIST Guidelines
NIST Incident Response Lifecycle:
1. Preparation
2. Detection and Analysis
3. Containment, Eradication, and Recovery
4. Post-Incident Activity
Applicable to: Security incidents, cybersecurity events
ISO 20000
Requirements:
- Documented incident management process
- Priority assignment criteria
- SLA compliance tracking
- Continual improvement activities
Real-World Examples
Example 1: E-commerce Platform Outage
Scenario: Payment gateway failure during peak shopping season
Response:
Detection: Automated monitoring alerts within 2 minutes
Classification: P1 - Critical (revenue impact)
Team: Major incident team assembled
Communication: Customer notification, status page update
Investigation: Identified third-party API failure
Workaround: Switched to backup payment provider
Resolution Time: 45 minutes
Post-Incident: Implemented automatic failover
Example 2: Email System Degradation
Scenario: Slow email delivery affecting 2,000 users
Response:
Detection: User reports to service desk
Classification: P2 - High impact
Diagnosis: Database performance issue
Resolution: Database optimization and index rebuild
Communication: Status updates every 2 hours
Resolution Time: 6 hours
Follow-up: Scheduled preventive maintenance
Example 3: Security Incident
Scenario: Ransomware detection on file server
Response:
Detection: Security monitoring alert
Classification: P1 - Critical (security)
Immediate Actions:
1. Network isolation of affected systems
2. Security team mobilization
3. Executive notification
Investigation: Phishing email vector identified
Remediation: Malware removal, system restoration from backup
Resolution Time: 24 hours
Follow-up: Security awareness training, email filtering enhancement
Frequently Asked Questions
Q: Whatβs the difference between an incident and an outage?
A: An outage is a type of incident where a service is completely unavailable. All outages are incidents, but not all incidents are outages (e.g., performance degradation is an incident but not an outage).
Q: How quickly should incidents be logged?
A: Incidents should be logged immediately upon detectionβwithin minutes for critical issues. Automated systems log instantly; manual reports should be logged within 15-30 minutes.
Q: Who can report an incident?
A: Anyoneβend users, IT staff, automated monitoring systems, external partners. All incident sources are valid.
Q: Should workarounds be documented?
A: Yes. Workarounds should be documented in the knowledge base as temporary solutions until permanent fixes are implemented.
Q: How long should incident records be retained?
A: Typically 1-3 years for trend analysis and compliance, though requirements vary by industry and regulation.
Q: What happens if an SLA is breached?
A: Document the breach, notify stakeholders, analyze root cause, and implement corrective actions. Many organizations have escalation or credit policies for SLA breaches.
References
- What are incidents? - Jira Service Management (Atlassian)
- How ITIL Differentiates Problems and Incidents - Global Knowledge
- Automated Incident Management - Workato
- What is Incident Management? - AWS
- Incident Management - ServiceNow Community
- AI for Incident Response - Microtica
- Incident vs Service Request - Freshworks
- Incident Management - IT Process Wiki
- Reduce MTTR With Incident Management Automation - Moveworks
- Using AIOps for Better Incident Management - PagerDuty
- 6 Top Incident Management Use Cases for AI Copilots - BigPanda
- 5 Steps of Incident Management Process - Pulpstream
- 5 Steps of the Incident Management Lifecycle - RSI Security
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