Post-Incident Review Template

Why You Need a Post-Incident Review Template

After every incident, teams face the same challenge: documenting what happened, why it happened, and how to prevent it from happening again. Without structure, these reviews become rambling discussions that miss critical details or devolve into blame sessions.

A post-incident review template solves this by providing consistent structure across all incidents. Teams know exactly what information to gather, how to organize analysis, and where to focus improvement efforts. The result is faster documentation, more complete analysis, and better learning outcomes.

But not all templates are created equal. Some are too rigid, forcing incidents into predefined categories that don’t fit. Others are too vague, providing no real guidance. The best templates balance structure with flexibility—providing enough framework to ensure consistency while allowing teams to adapt based on incident characteristics.

Essential Template Sections

Every effective post-incident review template includes these core sections:

1. Incident Metadata

Start with basic identification and context:

• Incident ID: Unique identifier for reference
• Incident Title: Clear, descriptive name
• Date & Time: When incident started and when it was resolved
• Duration: Total time from detection to resolution
• Severity: Classification (Critical, High, Medium, Low)
• Incident Lead: Person who coordinated response
• Participants: Everyone involved in resolution
• Services Affected: Which systems or capabilities were impacted

This metadata enables pattern analysis across incidents. When you review multiple post-incident reports, consistent metadata reveals trends: Are certain services failing more frequently? Do specific severity levels take longer to resolve? Is one team constantly involved?

2. Executive Summary

A 2-3 sentence overview answering:

• What broke?
• How long was it broken?
• What was the business impact?
• What fixed it?

Example:

The API gateway experienced connection pool exhaustion from 2:14 PM to 3:47 PM on January 15th, causing intermittent request failures affecting approximately 15% of users. The issue was resolved by increasing connection pool limits and implementing rate limiting on high-traffic endpoints.

The executive summary serves stakeholders who need to understand impact without reading technical details. Make it accessible to non-technical audiences while remaining accurate.

3. Impact Assessment

Quantify the incident’s effects:

• Customer Impact: How many users affected? What functionality was unavailable?
• Revenue Impact: Any direct financial loss? Lost transactions?
• Reputation Impact: Did customers complain? Was there negative press?
• Internal Impact: Team productivity lost? Customer support volume increase?

Be honest about impact. Teams sometimes minimize impact to avoid scrutiny, but accurate assessment drives appropriate investment in prevention. If 10,000 customers couldn’t complete checkout for an hour, say so. That context justifies prioritizing the fix.

4. Incident Timeline

The chronological sequence of events from first detection through resolution:

14:14 - Monitoring alerted on elevated API response times (P95 over 2000ms)
14:18 - On-call engineer acknowledged alert, began initial investigation
14:23 - Identified connection pool exhaustion in application logs
14:30 - Paged database team to rule out database performance issues
14:35 - Database team confirmed normal database performance
14:42 - Incident lead deployed emergency connection pool increase (150 → 300)
14:45 - Response times improved but remained elevated
15:10 - Engineering team identified missing rate limiting on /api/v2/bulk endpoint
15:35 - Rate limiting deployed to production
15:47 - Metrics confirmed resolution, monitoring returned to normal

Good timelines include:

• Specific timestamps
• What was observed or decided at each point
• Who took which actions
• Key decision points and why specific approaches were chosen

Accurate timelines are essential for understanding response effectiveness. They reveal where time was lost, where responders made correct decisions quickly, and where confusion or lack of information caused delays.

Platforms like Upstat automatically capture activity timelines with participant actions and threaded discussions, eliminating the need to reconstruct events from scattered Slack messages and memory.

5. Root Cause Analysis

This is the heart of the post-incident review. What actually caused the incident?

Important: Focus on systemic causes, not individual actions. Instead of “Engineer X deployed broken code,” write “Deployment process allowed untested code to reach production.”

Use the “5 Whys” technique:

Problem: API gateway connection pool exhausted

• Why? Too many concurrent connections
• Why? New bulk API endpoint created excessive connections
• Why? No rate limiting was configured on the endpoint
• Why? Rate limiting wasn’t included in API development checklist
• Why? No process exists for reviewing operational requirements during API design

The root cause isn’t the connection pool exhaustion—it’s the missing process for evaluating operational requirements when designing new APIs.

6. Contributing Factors

List everything that made the incident possible or worse:

• Technical factors: Missing monitoring, configuration errors, capacity limits
• Process factors: Inadequate testing, unclear runbooks, missing reviews
• Communication factors: Delayed notifications, unclear responsibilities
• External factors: Unexpected traffic patterns, third-party issues

Most incidents have multiple contributing factors. Document all of them—fixing any one factor might have prevented the incident.

7. What Went Well

This section is critical for blameless culture. What worked during the response?

• Monitoring caught the issue before customers reported it
• Rollback procedure was well-documented and worked correctly
• Team coordination was effective with clear incident lead
• Communication to stakeholders was timely and accurate

Recognizing what went well serves two purposes: it reinforces effective practices, and it balances the conversation to prevent the review from feeling like an endless list of failures.

8. What Went Poorly

Now address failures. Frame these as system gaps, not individual mistakes:

• ❌ Bad: “Sarah took too long to respond to the page”

• ✅ Good: “After-hours escalation policy didn’t account for time zone differences”

• ❌ Bad: “John deployed without testing”

• ✅ Good: “Deployment pipeline didn’t enforce test execution before production rollout”

Focus on fixable system problems. Every “what went poorly” item should point toward a potential improvement.

9. Action Items

Concrete, specific tasks to prevent recurrence:

Each action item needs:

1. Specific description: What exactly will be done?
2. Owner: One person (not a team) responsible for completion
3. Deadline: When it will be done
4. Priority: Must-fix / Should-fix / Nice-to-have

Example action items:

Priority	Action	Owner	Deadline
Must-fix	Implement rate limiting on all /api/v2 endpoints	Platform Team Lead	Jan 30
Must-fix	Add connection pool monitoring with alert at 80% capacity	SRE Team Lead	Feb 5
Should-fix	Update API development checklist to include operational review	Engineering Manager	Feb 15
Nice-to-have	Document bulk API best practices	Documentation Team	March 1

Prioritize ruthlessly. Three critical items completed beat ten nice-to-have items documented but never done.

10. Lessons Learned

Broader insights that apply beyond this specific incident:

• Bulk operations require different operational considerations than individual requests
• Connection pool sizing should account for burst traffic patterns
• New API endpoints need operational review before production deployment

These lessons feed into broader process improvements and help other teams avoid similar issues.

Template Adaptations by Incident Type

Quick Incidents (under 30 minutes)

For minor incidents resolved quickly, use abbreviated format:

• Summary: 1 paragraph covering what, why, fix
• Timeline: Key events only (detected, diagnosed, fixed)
• Root Cause: 1-2 sentences
• Action Items: 1-3 critical items maximum

Don’t over-document simple issues. The template should scale based on incident severity and complexity.

Major Incidents (over 2 hours or high impact)

For serious incidents, expand these sections:

• Detailed Timeline: Include all decision points and why specific approaches were chosen
• Multiple Root Causes: Complex incidents often have several contributing failures
• Extended Impact Analysis: Business impact, customer communication timeline, support ticket volume
• Communication Review: How was incident communicated to stakeholders? What worked? What didn’t?

Near-Miss Incidents

Incidents that almost caused impact but were caught in time still deserve documentation:

• Focus on what prevented impact in “What Went Well”
• Emphasize how detection worked to reinforce good practices
• Document what would have happened to justify prevention work

Near-miss reviews are often harder to prioritize, but they’re opportunities to fix problems before they cause real damage.

Common Template Mistakes

Mistake 1: Too Much Process, Not Enough Content

Templates are frameworks, not checklists to be filled out mechanically. If a section doesn’t apply to your incident, skip it or note “N/A” and explain why.

Mistake 2: Vague Action Items

“Improve monitoring” isn’t an action item. “Add API response time monitoring for /bulk endpoints with alert at P95 over 1000ms” is an action item.

Mistake 3: Blame Hiding in Systems Language

“The deployment process failed due to inadequate testing by the engineer” is still blame. It’s just blame wrapped in process language.

Genuinely blameless language focuses on what systems could prevent the issue: “Deployment pipeline should enforce automated testing before allowing production rollout.”

Mistake 4: Writing for Posterity Instead of Learning

Post-incident reviews aren’t legal documents. They’re learning tools. Write clearly and honestly for an audience of engineers trying to understand what happened, not executives evaluating performance.

Mistake 5: Never Updating the Template

As teams learn what information matters most, templates should evolve. If you consistently skip a section, remove it. If you keep adding ad-hoc information, formalize it as a template section.

Making Templates Stick

Templates only help if teams actually use them. How do you ensure adoption?

Make them accessible. Store templates where engineers naturally look—in your incident management system, shared documentation, or as pre-filled documents in your wiki.

Integrate with workflow. When an incident is declared, automatically create a post-incident review document from the template. Platforms like Upstat maintain incident timelines and participant tracking that serve as natural starting points for post-incident reviews.

Lead by example. Leadership should use the template consistently for all incidents they review. If senior engineers skip the template for “quick incidents,” others will too.

Iterate based on feedback. Ask teams what sections are most valuable and what feels like busywork. Refine the template over time.

Track completion. Measure how many incidents get post-incident reviews and how many action items get completed. If completion rates are low, your template might be too burdensome.

Beyond the Template: Follow-Through Matters More

The best template in the world doesn’t prevent incidents if action items never get implemented.

After documenting incidents:

• Schedule action item reviews in team meetings
• Track completion status visibly
• Escalate overdue items to leadership
• Celebrate completed improvements to reinforce the loop from incident to prevention

Templates structure learning, but follow-through prevents recurrence.

Conclusion: Structure Enables Learning

Post-incident review templates aren’t bureaucracy—they’re leverage. They ensure teams capture the right information, ask the right questions, and focus on systemic improvement rather than individual blame.

The goal isn’t perfect documentation. It’s consistent learning. Templates make that learning systematic, repeatable, and scalable across growing teams.

Your incidents will teach you invaluable lessons about your systems, processes, and organization—but only if you have structure to capture those lessons systematically. A good template is how you turn painful failures into competitive advantages.

The difference between teams that repeat mistakes and teams that continuously improve often comes down to whether they document incidents thoughtfully and act on what they learn.