The Cardboard Incident Story Observatory Tower

Climbing a Paper Staircase to See Reliability Patterns Above the Noise

Reliability work often feels like trying to study the city from street level during a parade. There’s noise, chaos, and conflicting perspectives. Every incident is a cardboard box someone drops into the street: messy, awkward, and easy to step around and forget.

But if you keep those boxes—if you stack them up, label them, and organize them—you slowly build a cardboard observatory tower. Story by story, incident by incident, you climb a paper staircase that lets you see above the noise. Patterns emerge. Blind spots come into view. Reliability stops being a series of fire drills and becomes a practiced, evolving discipline.

This is what good Site Reliability Engineering (SRE) does with incidents.

In this post, we’ll explore how blameless postmortems, premortems, observability, and structured analysis tools help you build that tower—turning every cardboard incident story into another step toward safer, more resilient systems.

From Single Incidents to a Tower of Stories

Most organizations start with a narrow view of incidents:

• Something breaks.
• People scramble to fix it.
• A quick write-up appears (or doesn’t).
• Everyone moves on.

That’s staying at street level. You treat each incident as an isolated event rather than another sheet of narrative cardboard you could add to your tower.

Long-term reliability practice—across domains like aviation, nuclear power, and large-scale internet services from about 1995–2020—shows a consistent lesson:

Systematic, structured analysis of incidents is the main engine of safer, more resilient systems.

The “Cardboard Incident Story Observatory Tower” is a metaphor for that structure:

• Each incident story = A documented postmortem.
• Each story has a consistent shape = Standard templates and data.
• Stories can be compared = Shared metrics like MTTR and recurring cause patterns.
• Stories are easy to share = Collaboration tools like Slack spread the learning.

Climb enough stories, and you start seeing patterns in how and why things fail.

Blameless Postmortems: The Core Building Blocks

At the heart of the tower is the blameless postmortem.

What is a blameless postmortem?

A blameless postmortem is a structured, judgment-free analysis of an incident. Its purpose is learning, not punishment. Instead of “Who messed up?” the core questions are:

• What actually happened, step by step?
• How did the system behave and why?
• What made this failure possible or likely?
• What can we change in the system and process so this is less likely or less harmful next time?

Why blameless matters

Blame distorts data:

• People omit details to protect themselves.
• Risky-but-necessary work goes underground.
• Near-misses never get reported.

Blameless postmortems, by contrast, encourage:

• Honesty about what was tried, what was skipped, and what confused people.
• Curiosity about system behavior instead of moral judgment.
• Systemic thinking about guardrails, tooling, and process.

Over time, each incident is no longer a career risk; it’s another sheet of cardboard added to the tower.

Premortems: Reinforcing the Tower Before It’s Needed

If postmortems are about understanding what did happen, premortems are about exploring what could happen.

What is a premortem?

A premortem is a structured exercise you run during design or planning, where you:

1. Imagine that your new system or feature has spectacularly failed in production.
2. Ask, “What went wrong?” as if the failure already occurred.
3. Brainstorm plausible failure scenarios, contributing factors, and weak spots.

Why premortems complement postmortems

Premortems:

• Transfer learning forward in time. Postmortem insights and patterns are used to anticipate similar failures in new designs.
• Reveal hidden assumptions. “Of course service X will always be up” or “No one would ever misconfigure that flag” get challenged.
• Shape safer architectures. Once imagined, failure paths can be mitigated with circuit breakers, fallbacks, feature flags, or runbooks.

You can think of premortems as pre-labeling boxes and reinforcing them before the incident arrives, so the tower is steadier from the start.

Observability: The Raw Material for Good Stories

You can’t build a reliable tower out of smudged, illegible cardboard. Likewise, you can’t write effective postmortems without solid data.

Why observability is critical

Post-incident analysis depends on high-quality signals from your systems. Tools like:

• Prometheus (metrics and alerts)
• New Relic (APM, traces, dashboards)
• Log aggregation platforms

provide the timelines, metrics, and traces that answer:

• What changed right before the incident started?
• Which components degraded first?
• What did the system think was happening (e.g., error messages, retries, backpressure)?

Without this, postmortems become vague narratives:

“Traffic spiked, the service slowed down, we restarted it, and things got better.”

With observability, you can say:

• “At 10:02, request latency at the edge tripled due to a misconfigured cache purge.”
• “At 10:04, the database hit connection pool exhaustion because the retry policy amplified load.”
• “At 10:08, a manual restart masked the underlying configuration drift.”

These are actionable details you can turn into design changes, alerts, and runbook updates.

MTTR and the Focus on Systems, Not Scapegoats

A key outcome of structured incident analysis is reducing Mean Time to Recovery (MTTR)—how long it takes you to restore service when something breaks.

Shifting the question

Instead of: “Why did Alice push that bad config?”

Ask:

• Why was it possible for a single config change to take down production?
• Why didn’t our observability and alerts highlight the blast radius sooner?
• Why was rollback slow or unclear?
• Why did on-call need 30 minutes to find the right dashboard or runbook?

This systemic focus uncovers reliability levers that actually move MTTR:

• Safer rollout mechanisms (feature flags, canary deploys)
• Better alert routing and clear ownership
• Self-healing patterns where possible
• Well-practiced runbooks and incident response procedures

People will always make mistakes. Good SRE practice ensures individual mistakes can’t easily become prolonged outages.

Templates: Making Every Story Comparable

To build a tower, all your cardboard layers need at least a compatible size and shape. That’s what standardized incident templates provide.

A good postmortem template typically includes:

• Summary: One-paragraph incident overview.
• Impact: What users saw, SLO/SLA breaches, business impact.
• Timeline: Precise sequence of events and actions.
• Root cause(s): Systemic contributing factors, not just the triggering event.
• Detection: How the issue was noticed (alert, customer ticket, luck).
• Response: What responders did, and how effective it was.
• Lessons learned: Insights about architecture, process, or tooling.
• Action items: Concrete, prioritized follow-ups with owners.

Standard templates make incidents:

• Repeatable: Teams know how to run and write them.
• Comparable: You can scan many incidents for recurring patterns.
• Searchable: It’s easier to find similar historical failures.

Over time, you can run meta-analyses:

• “30% of our major incidents involved configuration drift.”
• “Half of our high-severity incidents were detected by customers first.”

Those are tower-level insights—visible only once enough consistent stories have been stacked.

Sharing the Tower: Slack and the Social Side of Reliability

An observatory tower isn’t useful if only a few people climb it. Reliability becomes a team and organization capability when incident learning is easy to share.

Collaboration tools like Slack, Teams, or similar chat platforms are ideal for:

• Announcing new postmortems in a dedicated reliability or #incidents channel.
• Discussing lessons learned across teams (e.g., platform, product, security).
• Highlighting recurring patterns and cross-cutting action items.
• Onboarding new engineers by pointing them to “classic” incidents and their postmortems.

This turns isolated learning into distributed practice. The observatory tower stops being a backroom archive and becomes part of everyday engineering conversation.

Lessons from 25 Years of Reliability Practice

Across high-reliability domains over the past few decades, a few themes consistently show up:

1. Incidents are inevitable; repeated ignorance is optional.
2. Structured, blameless analysis is the difference between repeating failures and evolving past them.
3. High-quality observability transforms fuzzy stories into precise engineering data.
4. Standardization and tooling (templates, runbooks, dashboards) make reliability work scalable.
5. Socialization of learnings through collaboration tools turns individual insights into organizational knowledge.

When you do these things consistently from 1995–2020 or 2020–2045, your systems and your teams steadily become safer and more resilient, even as complexity grows.

Conclusion: Keep Climbing the Paper Staircase

Every incident is a story written on a piece of cardboard. You can throw it away once the fire is out—or you can keep it, label it, and add it to the observatory tower.

Blameless postmortems, enriched by strong observability; premortems that anticipate failure; standardized templates; and open sharing via tools like Slack all work together to create a paper staircase you can reliably climb.

From the top of that tower, the noise of individual outages fades, and patterns of reliability—and fragility—come into focus. That view is how you move from merely surviving incidents to systematically engineering resilience into everything you build.

The cardboard is already there in your organization. The question is: are you stacking it?