OrbStack Performance Troubleshooting: AI-Optimized Technical Reference
Critical System Failures and Recovery
File Descriptor Leak (High Severity)
- Problem: File descriptor leak bug affects large container setups with heavy bind mounts
- Breaking Point: 8,000+ file descriptors causes system-wide failures
- Root Cause: Each file gets descriptor that doesn't clean up properly
- Affected Versions: Pre-1.6.2
- Quick Diagnostic:
lsof -p $(ps aux | grep OrbStack | head -1 | awk '{print $2}')
- Immediate Fix: Restart OrbStack (temporary)
- Permanent Fix: Upgrade to 1.6.2+
- Prevention: Limit concurrent containers or use named volumes for data-heavy apps
Container Startup Failures After macOS Updates
- Problem: macOS updates break hypervisor APIs regularly
- Pattern: .1 or .2 point releases commonly cause issues
- Example: macOS 14.1.2 broke
com.apple.security.hypervisor
entitlements - Emergency Recovery:
sudo rm -rf ~/Library/Group\ Containers/HUAQ24HBR6.dev.orbstack/data/vz
- Prevention: Check OrbStack releases before updating macOS
- Recovery Time: OrbStack usually patches within days
Memory Leak in Text Editors
- Problem: VS Code, Zed balloon to 20GB+ RAM when opening files from
~/OrbStack/
mount - Avoid: Direct file access from
~/OrbStack/[container]/
- Workaround: Copy files out or edit inside container
- Command:
docker exec -it [container] vim /path/to/file
Performance Specifications and Limits
VirtioFS Performance Metrics
- Optimal Performance: 75-95% of native macOS speed
- Real-World Impact: 5-25% slower than native execution
- Package Installation:
pnpm install
at 88% native speed (vs 40% Docker Desktop) - Large Files: 87% native performance (vs 60% Docker Desktop)
- Database Operations: 76% native speed with proper fsyncing
- Performance Cliff: Thousands of small files cause dramatic slowdowns
Memory Consumption Patterns
- Default Limit: 8GB system memory (dynamic allocation)
- Idle Usage: ~100MB
- Single Rails App: 1-2GB total
- Multiple Microservices: 4-6GB common
- Large Databases: 3-4GB each (Postgres, MongoDB)
- Critical Threshold: 16GB MacBook Pro with 6 containers can exceed available memory
CPU Overhead by Architecture
- Native ARM64: 0-2% overhead vs native
- x86 through Rosetta: 15-30% overhead
- Build Performance: ARM64 Docker builds 2-3x faster than x86
- Database Performance: Postgres ARM64 vs x86 shows 40% performance difference
- Node.js Applications: 30% faster cold start times on native architecture
Resource Requirements and Scaling Limits
File Descriptor Consumption
- Bind Mounts: 10-50 descriptors per mounted directory
- Database Connections: 1-3 descriptors each
- Network Connections: 2 descriptors per active connection
- macOS Default: 256 per process (insufficient)
- Recommended: 4096-8192 descriptors
- Monitor Command:
lsof -p $(pgrep OrbStack) | wc -l
Container Scaling Thresholds
- 8-12 containers: Optimal resource sharing
- 15-20 containers: Noticeable slowdowns from resource competition
- 25+ containers: Single VM becomes bottleneck
- Failure Patterns: Random restarts, OOM kills, network timeouts
Configuration That Works in Production
Corporate Network Compatibility
- Problem: OrbStack inherits macOS network configuration exactly
- VPN Issues: Corporate VPNs that route everything through proxies break networking
- DNS Problems: Split DNS creates inconsistent domain resolution
- Proxy Auto-Config: PAC files add 200ms to every HTTP request
- Certificate Issues: Corporate HTTPS inspection breaks container requests
Network Performance Fixes
# Bypass proxy for containers
docker run --env HTTP_PROXY="" --env HTTPS_PROXY="" [image]
# Use explicit DNS
docker run --dns=1.1.1.1 --dns=8.8.8.8 [image]
# Test connectivity
docker exec -it [container] time curl -I https://google.com
Optimization for File-Heavy Workloads
# Exclude from Spotlight indexing
sudo mdutil -i off ~/OrbStack
# Use named volumes for package caches
docker run -v npm-cache:/root/.npm your-app
# Optimize build context
docker build --cpus="2" .
Critical Warnings and Breaking Points
Single VM Architecture Limitations
- Resource Competition: All containers share same kernel resources
- Cascade Failures: One bad container can affect all others
- Memory Pressure: OOM killer can terminate multiple containers
- I/O Contention: High-throughput containers saturate shared interface
Performance Monitoring Commands
# Real memory pressure
orb exec --machine=default -- free -h
orb exec --machine=default -- cat /proc/pressure/memory
# I/O contention
orb exec --machine=default -- iostat 1 5
orb exec --machine=default -- iotop -ao
Docker Context Issues
- Problem: Context switching between OrbStack and Docker Desktop
- Error: "Cannot connect to Docker daemon" despite OrbStack running
- Fix:
docker context use orbstack
- Reset Alias:
alias docker-reset='docker context use orbstack && docker system prune -f'
When OrbStack Becomes the Bottleneck
Migration Indicators
- Startup Time: Full environment exceeds 2-3 minutes
- Resource Exhaustion: Random container restarts or OOM kills
- Network Issues: Timeouts between containers on localhost
- File Operation Failures: Previously working operations now timeout
Alternative Considerations
- Docker Desktop: Better resource isolation at scale (25+ containers)
- Intel Macs: Docker Desktop may provide better battery life
- Enterprise Networks: Docker Desktop handles corporate networking better
- Development/Production Parity: Performance differences more pronounced with OrbStack
Diagnostic Commands Reference
# Check container architecture
docker inspect [container] | grep Architecture
# Monitor real resource usage
docker system df
orb info
# Debug network performance
docker exec -it [container] time nslookup google.com
docker exec -it [container] ip route
# Find memory usage in containers
docker exec -it [container] ps aux --sort=-%mem
# Check build context size
docker build --no-cache . 2>&1 | grep "Sending build context"
Recovery Procedures
OrbStack Crash Recovery
- Check surviving resources:
docker images
,docker volume ls
- Restart services:
docker compose up -d
- Critical: Ephemeral container data is lost
- Prevention: Use named volumes for persistent data
High CPU Usage (x86 Emulation)
- Identify culprit:
docker stats --no-stream
- Check architecture:
docker inspect [container] | grep Architecture
- Kill problematic container:
docker kill [container] && docker rm [container]
- Prevention: Use
--platform=linux/arm64
flag
Network Connectivity Issues
- Test basic connectivity:
docker exec -it [container] curl -I https://google.com
- Check DNS:
docker exec -it [container] nslookup google.com
- Restart network stack:
orb restart
- VPN Workaround: Restart OrbStack after VPN connection
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