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Debug buttercup

Skill ranbot-ai/awesome-skills/skills/debug-buttercup

Awesome Claude Skills, Tools for Customizing Claude AI workflows

Install
npx -y skills add ranbot-ai/awesome-skills --skill debug-buttercup

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What its author says it does

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All pods run in namespace crs. Use when pods in the crs namespace are in CrashLoopBackOff, OOMKilled, or restarting, multiple services restart simultaneously (cascade failure), or redis is unresponsiv

SKILL.md

5.3 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it

Debug Buttercup

When to Use

  • Pods in the crs namespace are in CrashLoopBackOff, OOMKilled, or restarting
  • Multiple services restart simultaneously (cascade failure)
  • Redis is unresponsive or showing AOF warnings
  • Queues are growing but tasks are not progressing
  • Nodes show DiskPressure, MemoryPressure, or PID pressure
  • Build-bot cannot reach the Docker daemon (DinD failures)
  • Scheduler is stuck and not advancing task state
  • Health check probes are failing unexpectedly
  • Deployed Helm values don't match actual pod configuration

When NOT to Use

  • Deploying or upgrading Buttercup (use Helm and deployment guides)
  • Debugging issues outside the crs Kubernetes namespace
  • Performance tuning that doesn't involve a failure symptom

Namespace and Services

All pods run in namespace crs. Key services:

LayerServices
Infraredis, dind, litellm, registry-cache
Orchestrationscheduler, task-server, task-downloader, scratch-cleaner
Fuzzingbuild-bot, fuzzer-bot, coverage-bot, tracer-bot, merger-bot
Analysispatcher, seed-gen, program-model, pov-reproducer
Interfacecompetition-api, ui

Triage Workflow

Always start with triage. Run these three commands first:

# 1. Pod status - look for restarts, CrashLoopBackOff, OOMKilled
kubectl get pods -n crs -o wide

# 2. Events - the timeline of what went wrong
kubectl get events -n crs --sort-by='.lastTimestamp'

# 3. Warnings only - filter the noise
kubectl get events -n crs --field-selector type=Warning --sort-by='.lastTimestamp'

Then narrow down:

# Why did a specific pod restart? Check Last State Reason (OOMKilled, Error, Completed)
kubectl describe pod -n crs <pod-name> | grep -A8 'Last State:'

# Check actual resource limits vs intended
kubectl get pod -n crs <pod-name> -o jsonpath='{.spec.containers[0].resources}'

# Crashed container's logs (--previous = the container that died)
kubectl logs -n crs <pod-name> --previous --tail=200

# Current logs
kubectl logs -n crs <pod-name> --tail=200

Historical vs Ongoing Issues

High restart counts don't necessarily mean an issue is ongoing -- restarts accumulate over a pod's lifetime. Always distinguish:

  • --tail shows the end of the log buffer, which may contain old messages. Use --since=300s to confirm issues are actively happening now.
  • --timestamps on log output helps correlate events across services.
  • Check Last State timestamps in describe pod to see when the most recent crash actually occurred.

Cascade Detection

When many pods restart around the same time, check for a shared-dependency failure before investigating individual pods. The most common cascade: Redis goes down -> every service gets ConnectionError/ConnectionRefusedError -> mass restarts. Look for the same error across multiple --previous logs -- if they all say redis.exceptions.ConnectionError, debug Redis, not the individual services.

Log Analysis

# All replicas of a service at once
kubectl logs -n crs -l app=fuzzer-bot --tail=100 --prefix

# Stream live
kubectl logs -n crs -l app.kubernetes.io/name=redis -f

# Collect all logs to disk (existing script)
bash deployment/collect-logs.sh

Resource Pressure

# Per-pod CPU/memory
kubectl top pods -n crs

# Node-level
kubectl top nodes

# Node conditions (disk pressure, memory pressure, PID pressure)
kubectl describe node <node> | grep -A5 Conditions

# Disk usage inside a pod
kubectl exec -n crs <pod> -- df -h

# What's eating disk
kubectl exec -n crs <pod> -- sh -c 'du -sh /corpus/* 2>/dev/null'
kubectl exec -n crs <pod> -- sh -c 'du -sh /scratch/* 2>/dev/null'

Redis Debugging

Redis is the backbone. When it goes down, everything cascades.

# Redis pod status
kubectl get pods -n crs -l app.kubernetes.io/name=redis

# Redis logs (AOF warnings, OOM, connection issues)
kubectl logs -n crs -l app.kubernetes.io/name=redis --tail=200

# Connect to Redis CLI
kubectl exec -n crs <redis-pod> -- redis-cli

# Inside redis-cli: key diagnostics
INFO memory          # used_memory_human, maxmemory
INFO persistence     # aof_enabled, aof_last_bgrewrite_status, aof_delayed_fsync
INFO clients         # connected_clients, blocked_clients
INFO stats           # total_connections_received, rejected_connections
CLIENT LIST          # see who's connected
DBSIZE               # total keys

# AOF configuration
CONFIG GET appendonly     # is AOF enabled?
CONFIG GET appendfsync   # fsync policy: everysec, always, or no

# What is /data mounted on? (disk vs tmpfs matters for AOF performance)
kubectl exec -n crs <redis-pod> -- mount | grep /data
kubectl exec -n crs <redis-pod> -- du -sh /data/

Queue Inspection

Buttercup uses Redis streams with consumer groups. Queue names:

QueueStream Key
Buildfuzzer_build_queue
Build Outputfuzzer_build_output_queue
Crashfuzzer_crash_queue
Confirmed Vu

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.