The Analog Incident Orchard Map: Planting Paper Trees for Every Failure Pattern in Your System

Modern systems don’t usually fail in brand‑new ways. They fail in familiar, repeatable patterns. The problem is that most teams only recognize those patterns in hindsight, one painful incident at a time.

The Analog Incident Orchard Map is a way to change that: you build a persistent, visual library of your system’s failure patterns. Each pattern becomes a “paper tree” in an orchard you can walk through before, during, and after incidents.

This post walks through how to:

• Map recurring failure modes to systems archetypes (from Donella Meadows and systems thinking)
• Tie those archetypes to concrete engineering examples in your stack
• Ground each “tree” with real reliability data (e.g., IC failure rates from Analog Devices and similar sources)
• Use the orchard to guide proactive resilience work
• Standardize incident documentation around these patterns
• Continuously update and prune the orchard after every incident

Why You Need an Incident Orchard, Not Just a Runbook

Runbooks answer: “What do I do right now?”

An incident orchard answers a deeper question: “What kind of thing is this, and where have we seen it before?”

Most high‑severity incidents in complex systems are not unique. They’re recombinations of a small set of structural patterns:

• Overloaded dependencies
• Feedback loops that get out of control
• Slow drifts that go unnoticed
• Single‑point fragilities hidden behind abstractions

By capturing these as named, documented patterns and organizing them visually, you:

• Recognize incidents earlier (“This looks like our ‘Retry Storm’ tree.”)
• Reuse fixes and mitigations instead of inventing new ones each time
• Communicate faster across teams (“We’re in a ‘Shifting the Burden’ scenario.”)
• Systematically harden your architecture against known traps

The orchard is your map of known traps, not just your list of past accidents.

Step 1: Map Recurring Failures to System Archetypes

Donella Meadows and other systems thinkers catalogued system archetypes: recurring structures that explain why systems behave in predictable ways. Some common ones:

• “Limits to Growth” – Something improves until it hits an unseen constraint.
• “Shifting the Burden” – Quick fixes substitute for real solutions, making the underlying problem worse.
• “Success to the Successful” – Winners get more resources, reinforcing their lead.
• “Tragedy of the Commons” – Shared resources are overused and degraded.

These archetypes show up in engineering all the time.

Example mappings

• Retry Storms → “Escalation / Reinforcing Feedback”
  A downstream service slows; callers retry aggressively; load increases further; the service collapses.

• Alert Fatigue → “Shifting the Burden”
  Instead of fixing noisy systems, you add more alerts and more people on call. People burn out; real issues are missed.

• Database Hotspot → “Limits to Growth”
  Performance scales linearly… until a single partition, index, or connection pool hits its limit and everything slows.

Your task: review past incidents and tag each one with a system archetype that best describes its structure, not just its surface symptoms.

Over time, you’ll see that 70–80% of your incidents are variants of a small set of archetypes. Those repeated combinations become the first trees in your orchard.

Step 2: Turn Each Pattern into a “Paper Tree”

A paper tree is a structured, visual card for a specific failure pattern in your system. Think of it as a persistent “incident species” in your orchard.

Each tree should include:

1. Name and Archetype

   • Example: “Northstar API Retry Storm (Reinforcing Feedback)”

2. System Diagram (Minimal but Specific)

   • A small diagram showing key components, calls, queues, and feedback loops.

3. Typical Triggers

   • “Downstream p95 latency > 700ms for 2 minutes”
   • “Connection pool saturation on service X”

4. Observable Signals

   • Metrics, logs, traces that spike during this pattern.

5. Known Incidents

   • Links to 2–5 postmortems where this pattern occurred.

6. Preventive Controls & Design Strategies

   • Circuit breakers, backoff strategies, capacity planning, etc.

7. Tests & Simulations

   • Chaos experiments, load tests, unit tests that hit this pattern.

8. Reliability Data & Risk Level

   • Real failure rates (hardware, software, network) that influence likelihood and impact.

By keeping trees lightweight but structured, engineers can quickly scan them during design reviews or active incidents.

Step 3: Ground Each Tree in Real Reliability Data

Without data, risk feels abstract. You can make your orchard far more actionable by embedding reliability prediction data into each tree.

Sources include:

• IC and component failure data (e.g., from Analog Devices safety and reliability notes)
• Network and hardware incident stats from your own fleet
• Cloud provider SLAs and historical outages
• Software defect rates from your release/bug trackers

Example: IC failure rates in a power‑sensitive subsystem

Suppose you operate an edge device dependent on a particular ADC (analog‑to‑digital converter) whose reliability data states:

• Failure rate: FIT = 50 (50 failures per billion device‑hours)
• Dominant failure modes: latch‑up at high temperature, ESD damage

Your “Analog Input Drift & Dropout” tree might document:

• Likelihood: Medium in high‑temp deployments; low elsewhere
• Impact: Loss of sensor data → control loop instability → emergency shutdown
• Controls: Thermal derating, watchdog checks on readings, redundant sensing

You don’t need perfect precision—just order‑of‑magnitude grounding. When every tree has:

• A rough frequency (weekly / monthly / yearly / rare)
• A blast radius estimate (local / service / region‑wide)

…your orchard becomes a practical risk register, not just a gallery of past failures.

Step 4: Use the Orchard as a Guide for Proactive Resilience Work

Once you’ve planted a first set of trees, treat the orchard as your backlog of structural resilience work.

For each tree, maintain:

• Preventive controls:
  • E.g., for retry storms: exponential backoff with jitter, circuit breakers, concurrency limits, load shedding.
• Detection improvements:
  • New SLOs, better alerts, health checks targeted at that pattern.
• Design guidelines:
  • "No sync calls to system X in hot paths," or "All cross‑region writes must be idempotent."
• Test catalog:
  • Chaos experiments that deliberately invoke that pattern.

Your reliability roadmap then becomes: Which trees are we hardening this quarter?

Example:

• Q2: Focus on “Limits to Growth” trees (capacity and hotspots).
• Q3: Focus on “Shifting the Burden” trees (alerting, manual ops, tech debt).

This reframes reliability from “random fire‑fighting” into systematic gardening.

Step 5: Standardize Incident Docs Around Orchard Patterns

During a live incident, you want responders to answer fast:

“Which tree are we in?”

To make that possible, standardize incident and postmortem templates around the orchard:

1. Pattern classification field

   • Required: pick an archetype and one existing tree, or mark as “candidate new tree.”

2. Tree checklist

   • If a tree is selected, auto‑populate:
     • Known mitigations
     • Known runbooks
     • Related dashboards

3. Deviation notes

   • Fields capturing how this occurrence differed from previous ones (new trigger, new component, broader blast radius).

4. Update hook

   • After resolution, part of the postmortem is: “Update tree X or create tree Y with what we learned.”

The goal is that an incident commander can say within 15 minutes:

• “This matches the ‘Payment Gateway Cascading Timeout’ tree; follow those mitigations first.”

This speeds triage, focuses communication, and helps teammates share a common mental model of what’s happening.

Step 6: Continuously Update and Prune the Orchard

An orchard is alive. So is your system. You need a regular gardening cycle:

1. After each incident

   • Confirm which tree it matched or create a new one.
   • Record new signals, mitigations, or failure modes.

2. Quarterly orchard review

   • Remove trees that no longer apply (e.g., components fully decommissioned).
   • Split overly broad trees into clearer sub‑patterns.
   • Merge near‑duplicates.

3. Design review integration

   • For any major design, explicitly ask:
     • “Which trees are we touching?”
     • “Which trees might we accidentally create?”

4. Education & onboarding

   • Use the orchard in training: new engineers walk through top trees and the systems archetypes behind them.

Over time, the orchard becomes your institutional memory of how the system fails—and how you’ve learned to prevent and recover from those failures.

How to Start (In One Week)

You don’t need a huge program to begin. In one week, you can:

1. Choose 5–10 impactful incidents from the last year.
2. For each, identify a system archetype.
3. Draft simple paper trees (even on real paper or a whiteboard snapshot):
   • Name, diagram, triggers, signals, mitigations.
4. Pull in at least one piece of real reliability data per tree.
5. Update your incident template to include “Tree / Archetype” and a link to the orchard.

Then iterate. Each new incident either:

• Strengthens an existing tree, or
• Reveals a new pattern that deserves its own place in the orchard.

Conclusion: From Accidents to Patterns, From Patterns to Resilience

Individual incidents are noisy, painful, and often confusing. But taken together, they reveal a surprisingly small set of repeatable structural patterns.

The Analog Incident Orchard Map gives your team a way to:

• Translate abstract systems archetypes into concrete service failure modes
• Ground those patterns in real‑world reliability data
• Use them as a guide for proactive resilience investments
• Standardize incident response and learning around a shared visual map

Instead of treating each outage as an isolated accident, you start to see them as familiar trees in a known orchard. And as you keep planting, pruning, and learning, your system—and your team—becomes steadily more resilient.

Start with a few paper trees. The orchard will grow faster than you think.