skills/debug-buttercup/SKILL.md
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
npx skillsauth add ranbot-ai/awesome-skills debug-buttercupInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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crs namespace are in CrashLoopBackOff, OOMKilled, or restartingcrs Kubernetes namespaceAll pods run in namespace crs. Key services:
| Layer | Services | |-------|----------| | Infra | redis, dind, litellm, registry-cache | | Orchestration | scheduler, task-server, task-downloader, scratch-cleaner | | Fuzzing | build-bot, fuzzer-bot, coverage-bot, tracer-bot, merger-bot | | Analysis | patcher, seed-gen, program-model, pov-reproducer | | Interface | competition-api, ui |
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
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.Last State timestamps in describe pod to see when the most recent crash actually occurred.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.
# 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
# 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 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/
Buttercup uses Redis streams with consumer groups. Queue names:
| Queue | Stream Key | |-------|-----------| | Build | fuzzer_build_queue | | Build Output | fuzzer_build_output_queue | | Crash | fuzzer_crash_queue | | Confirmed Vu
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