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Labels and Constraints

This guide provides a comprehensive overview of Bacalhau's label and constraint system, which enables fine-grained control over job scheduling and resource allocation.

Understanding Labels and Constraints

Labels in Bacalhau are key-value pairs attached to nodes that describe their characteristics, capabilities, and properties. Constraints are rules you define when submitting jobs to ensure they run on nodes with specific labels.

Label Configuration

Command Line Configuration

Labels are defined when starting a Bacalhau node using the -c Labels flag:

bacalhau serve -c Labels="env=prod,gpu=true,arch=x64"

Configuration File

You can also define labels in a YAML configuration file:

# config.yaml
labels:
  env: prod
  gpu: true
  arch: x64
  region: us-west

Then start the node with:

bacalhau serve --config-file config.yaml

Verifying Labels

Check node labels using:

bacalhau node list

Constraint Operators

Bacalhau supports various operators for precise node selection:

Operator

Example

Description

=

region=us-east

Exact match

!=

env!=staging

Not equal

exists

gpu

Key exists

!

!temporary

Key doesn't exist

in

zone in (a,b,c)

Value in set

gt

mem-gb gt 32

Greater than

lt

cpu-cores lt 16

Less than

Job Submission Patterns

Basic Constraint Usage

Here are common patterns for submitting jobs with constraints:

# Single constraint
bacalhau docker run --constraints "env=prod" alpine

# Multiple constraints
bacalhau docker run \
  --constraints "env=prod" \
  --constraints "gpu=true" \
  nvidia/cuda:11.0-base nvidia-smi

# Data processing with specific architecture requirements
bacalhau docker run \
  --constraints "arch in (x64,arm64)" \
  --constraints "mem-gb gt 16" \
  --constraints "storage-tier!=hdd" \
  my-data-processing-job

# Common failure scenarios
bacalhau docker run --constraints "disk=ssd" alpine echo "failed"  # No SSD nodes
bacalhau docker run --constraints "cpu-cores gt 64" alpine echo "failed"  # Insufficient CPU

Environment-Specific Patterns

# Production workloads
bacalhau run --constraints "env=prod,data-tier=hot" spark-job

# Development/testing
bacalhau run --constraints "env=dev" test-runner

# Geographic requirements
bacalhau run --constraints "region=eu,compliance=gdpr" data-processor

# Multi-zone deployments
bacalhau run --constraints "zone in (us-east-1a,us-east-1b)" ha-service

### Hardware-Specific Patterns

```bash
# GPU workloads
bacalhau run \
  --constraints "gpu-model=a100" \
  --constraints "gpu-count gt 1" \
  llm-training

# High-memory workloads
bacalhau run --constraints "mem-gb gt 64" in-memory-db

### Advanced Resource Patterns

```bash
# Resource requirements
bacalhau docker run \
  --constraints "mem-gb gt 16" \
  --constraints "cpu-cores gt 4" \
  --constraints "gpu-count gt 1" \
  heavy-workload

# Geographic constraints
bacalhau docker run \
  --constraints "region=eu-west" \
  --constraints "zone in (a,b,c)" \
  geo-specific-job

Label Management Best Practices

Naming Conventions

Follow these patterns for consistent label naming:

Use lowercase alphanumeric characters
Separate words with hyphens
Use descriptive prefixes for categorization

Examples:

team-ml-gpu
env-prod-tier1
storage-ssd-nvme

Label Hierarchies

Organize labels hierarchically for better management:

# Parent node
bacalhau serve -c Labels="tier=core,env=prod"

# Specialized child node
bacalhau serve -c Labels="tier=edge,env=prod,gpu=true"

Label Inheritance and Templates

Dynamic Label Assignment

# Timestamped labels for rotation
bacalhau serve -c Labels="deploy-group=$(date +%Y-%m)"

# Environment-based inheritance
bacalhau serve -c Labels="infra-tier=core,env=prod"
bacalhau serve -c Labels="infra-tier=edge,env=prod,gpu=true"

Constraint Composition

# AND logic (all must match)
bacalhau run \
  --constraints "storage=ssd" \
  --constraints "cpu-arch=x64" \
  high-performance-job

# OR logic with value lists
bacalhau run \
  --constraints "zone in (us-east1,us-west2)" \
  multi-region-job

# Exclusion patterns
bacalhau run \
  --constraints "maintenance!=true" \
  time-sensitive-job

Maintenance and Operations

Node Updates

# Exclude maintenance nodes
bacalhau run --constraints "!maintenance" critical-job

Monitoring and Troubleshooting

# List all node labels
bacalhau node list --output json | jq '.[] | .Labels'

# Check job constraint matches
bacalhau job describe JOB_ID --include-events

Security and Compliance

Secure Workload Placement

# Ensure compliance requirements
bacalhau run \
  --constraints "security=hipaa" \
  --constraints "encryption=enabled" \
  sensitive-data-job

# Network isolation
bacalhau run \
  --constraints "network=private" \
  --constraints "public-access=false" \
  internal-job

Advanced Use Cases

Multi-Dimensional Constraints

# Complex GPU requirements
bacalhau run \
  --constraints "gpu-brand=nvidia" \
  --constraints "gpu-mem-gb gt 24" \
  --constraints "gpu-count >= 2" \
  rendering-job

# Security-hardened environments
bacalhau run \
  --constraints "security-profile=hipaa" \
  --constraints "encryption=on" \
  sensitive-data-job

### Resource Optimization

```bash
# Cost-optimized scheduling
bacalhau run \
  --constraints "instance-type=spot" \
  --constraints "cost-tier=low" \
  batch-job

# Performance optimization
bacalhau run \
  --constraints "storage-type=nvme" \
  --constraints "network-speed gt 10" \
  latency-sensitive-job

Multi-team Coordination

# Label deprecation management
bacalhau serve -c Labels="legacy-system=phase-out,retirement-date=2025-Q1"

# Team resource allocation
bacalhau run \
  --constraints "team=(data,research)" \
  --constraints "project=genomics-2024" \
  shared-resource-job

# Validation workflows
bacalhau job validate --constraints "gpu-type=a100" job-spec.yaml

### Capacity Planning

```bash
# Shared resource access
bacalhau run \
  --constraints "team in (research,engineering)" \
  --constraints "project=genomics-2024" \
  shared-resource-job

Troubleshooting Common Issues

No Matching Nodes

If your job fails with no matching nodes:

Check available nodes and their labels:
```
bacalhau node list --output json
```

Verify your constraints aren't too restrictive:

# Instead of
--constraints "mem-gb gt 128"
# Try
--constraints "mem-gb gt 64"

Ensure required nodes are online:

bacalhau node list --labels "required-label=value"

Label Updates Not Taking Effect

Remember that label changes require node restarts. After updating labels:

Gracefully stop the node
Apply new configuration
Restart the node
Verify labels with bacalhau node list

Conclusion

Effective use of Bacalhau's label and constraint system enables precise control over workload placement and resource utilization. Follow these best practices:

Use consistent naming conventions
Document your label taxonomy
Regularly audit and clean up unused labels
Test constraints before production deployment
Monitor constraint patterns for optimization opportunities

For additional support, consult the Bacalhau documentation or community resources.