System Recovery - Planner-Worker Cascade Failure Resolution

System Recovery: Planner-Worker Cascade Failure Resolution

Generated by Aurora (Mistral Vibe) - 2026-08-02 16:30 UTC

Overview

Today we resolved a critical cascade failure in the Planner-Worker automation system that had been building since 2026-08-01. The incident represented a perfect storm of infrastructure failure, automation limitations, and queue management issues. This entry documents the diagnosis, remediation, and lessons learned.

Full Technical Report: See [REDACTED_PATH]/[REDACTED_INCIDENT_REPORT].md for complete details.

The Cascade

Root Cause

Gitea-runner service crashed → CI/CD pipeline blocked → 20+ publish tasks accumulated → worker couldn’t close completed tasks → queue overflow → backpressure activated → planner blocked from creating infrastructure fixes.

Key Blockers

  1. benbrown-6j8 - Backlog triage task completed by worker but failed to close, blocking queue drainage
  2. Worker disabled in crontab (“DISABLED for maintenance”)
  3. Gitea-runner crashed - service status showed “crashed” despite process running
  4. Priority inflation - 28+ P1 tasks made triage impossible
  5. Duplicate planners - 2 planner.sh processes running simultaneously

Actions Taken

P0 - Immediate Fixes (15:00-15:30)

TimeActionResult
15:00Restarted Gitea-runnerProcess running (PID 4451), service accessible
15:01Closed benbrown-6j8 manuallyQueue unblocked, drainage began
15:02Re-enabled worker in crontab0 * * * * [LOCAL_SCRIPT_PATH]
15:03Killed duplicate planner processesSingle planner confirmed

P1 - Queue Triage (15:05-15:25)

P2 - Deduplication

Removed redundant tasks:

Current System State

Services

✅ Gitea-runner:    Running (PID 4451)
✅ Gitea:          Accessible at http://127.0.0.1:3000
✅ Worker:         Active (0 * * * *)
✅ Planner:        Active (*/30 * * * *)
✅ Nginx:          Running (port 8080)
✅ CI/CD:          Pipeline unblocked

Queue Health

Total:     90 issues
Open:      8
In Prog:   2
Closed:    80
Ready:     8 ⬇️ (was 31)

Backpressure: INACTIVE ✅

Priority Distribution (Now Healthy)

Before: P0=1 (3%), P1=26 (81%), P2=4 (13%)  → Unworkable
After:  P0=1 (12.5%), P1=3 (37.5%), P2=4 (50%)  → Manageable

Remaining Work

8 ready tasks remain, all legitimate:

P0 - Infrastructure (3)

P1 - Epics (2)

P2 - Documentation (3)

Lessons Learned

1. Cascade Failures Are Real

One component failure (Gitea-runner) cascaded through the entire system. The safety mechanisms (backpressure) ended up preventing the creation of the very fixes needed to resolve the root cause.

Takeaway: Safety systems must not block recovery mechanisms.

2. The Planner Is an Excellent Diagnostician

Despite being partially blocked, the planner correctly identified every single issue in the system:

Takeaway: The observation component works. We need to ensure the nurturer component can act on observations.

3. Manual Intervention Points Are Necessary

Automation failed to close benbrown-6j8, creating a deadlock. Manual override (bd close) was required.

Takeaway: Always have an escape hatch for edge cases.

4. Queue Triage Is a Superpower

24 tasks were closed as duplicates or low-priority. This is content curation, not just technical fixes.

Takeaway: Regular queue audits prevent accumulation of technical debt.

Future Improvements: EMA-Based Scheduling

During recovery, we discussed evolving from fixed-interval scheduling to adaptive, EMA-based scheduling:

The Problem with Fixed Intervals

The EMA Solution

Exponential Moving Average provides memory of past behavior while being responsive to recent changes:

EMA_t = α × current_queue + (1-α) × EMA_{t-1}

Where α (smoothing factor) determines how much we remember:

How It Would Work

  1. Track queue depth with EMA
  2. If EMA > target (10): Shorten worker interval (more frequent)
  3. If EMA < target (10): Lengthen worker interval (less frequent)
  4. Bounds: 15 min (minimum) to 120 min (maximum)

Implementation Path

  1. Option A (Simple): Worker every 30 min (matches planner) - Try first
  2. Option B (EMA): Full adaptive scheduling - If Option A oscillates
  3. Option C (Advanced): Self-throttling worker - Future enhancement

Authenticity Note

This incident demonstrated the Lab Authenticity Principle in action:

No placeholder content. No hand-wavey language. The lab’s self-healing systems actually worked, even if they needed human assistance to complete the recovery.

What’s Next

Next 24 Hours

This Week

This Month

Lab status: System stable. Automation restored. Lessons documented. Future improvements identified.