feat: Advanced Batch Orchestration with Enterprise-grade Error Handling

Overview

Extend the Batch Script Mode to provide sophisticated error handling, advanced orchestration patterns, and workflow management capabilities. This enhancement will transform bssh into a comprehensive cluster orchestration platform while maintaining backward compatibility with simple scripts. The system will support complex deployment patterns, sophisticated error recovery mechanisms, and enterprise-grade workflow management.

Technical Approach

Building upon the batch script foundation, we'll add:

1. Error Handling Framework

• Multi-level error strategies (node, stage, script)
• Error recovery mechanisms with automatic retry and fallback
• Rollback orchestration with state snapshots
• Circuit breaker patterns for failing nodes

2. Orchestration Engine

• Dependency graph execution with topological sorting
• Wave-based execution with configurable parallelism
• Leader election and distributed coordination
• Event-driven workflow transitions

3. Workflow Management System

• State machine-based workflow engine
• Checkpoint and resume capabilities
• Workflow composition and inheritance
• Real-time workflow monitoring and control

4. Dynamic Node Management

• Runtime node addition/removal
• Auto-discovery with health checks
• Load balancing and failover
• Node tagging and dynamic groups

Key Features

Enhanced Error Handling

• Threshold-Based Strategy: Stop if failure rate exceeds percentage/count
• Circuit Breaker: Temporarily exclude failing nodes after repeated failures
• Exponential Backoff: Smart retry with jitter to prevent thundering herd
• Rollback Mechanism: Transaction-like semantics with commit/rollback
• Dead Letter Queue: For permanently failed operations

Advanced Orchestration Patterns

• Canary Deployment: Gradual rollout with validation gates
• Blue-Green Deployment: Zero-downtime deployments with instant rollback
• Rolling Update: Configurable batch sizes and validation between waves
• Dependency Graph: Complex service dependencies with topological execution
• Leader Election: Raft-based consensus for critical operations

Workflow Management

• Checkpointing: Periodic state snapshots for resume capability
• Workflow States: Pending, Running, Paused, Failed, Completed with transitions
• Composition: Template workflows with inheritance and parameterization
• Control Plane: Start, pause, resume, cancel operations with monitoring

Implementation Phases

Phase 1: Enhanced Error Handling Framework

• Create error handling module with multiple strategies
• Implement per-node error tracking with health scores
• Build configurable failure strategies (FailFast, Continue, Threshold)
• Create rollback mechanism with compensating actions
• Implement retry orchestration with various policies

Phase 2: Advanced Orchestration Features

• Build dependency graph executor with topological sorting
• Implement staged execution with wave-based deployment
• Create leader election system using Raft consensus
• Build coordination service for distributed operations
• Add health check framework for continuous validation

Phase 3: Workflow Management System

• Design workflow state machine with transition rules
• Implement checkpoint system with state persistence
• Build workflow patterns (canary, blue-green, rolling)
• Create workflow composition with inheritance
• Add workflow control plane for runtime management

Phase 4: Node-Specific Script Management

• Implement role-based scripts with capabilities
• Build template system with property interpolation
• Create script generation engine for dynamic creation
• Add script distribution with compression and verification

Phase 5: Dynamic Node Management

• Implement node discovery (service discovery, DNS, cloud APIs)
• Build node lifecycle management with onboarding/decommissioning
• Create load balancing strategies (round-robin, weighted, least connections)
• Implement failover mechanism with split-brain prevention

Phase 6: Enhanced Error Reporting and Monitoring

• Build comprehensive reporting with analytics
• Implement detailed logging with correlation IDs
• Create alerting system with escalation
• Add metrics collection for observability

Example: Complex Production Deployment

name: Production Deployment Pipeline
version: 2.0

orchestration:
  error_handling:
    strategy: adaptive
    checkpoint_interval: 5m
    
  node_management:
    discovery:
      method: service_registry
      refresh_interval: 30s
      
workflow:
  - stage: canary_deployment
    nodes: 
      selector: "role=web && canary=true"
      count: 2
    steps:
      - name: deploy_application
        upload: "dist/" to: "/app/new/"
        command: |
          ln -sfn /app/new /app/current
          systemctl restart webapp
          
      - name: validate_canary
        wait: 30s
        validations:
          - http_check:
              url: "http://localhost/health"
              expected_status: 200
          - error_rate:
              threshold: 1%
              duration: 5m
              
  - stage: gradual_rollout
    depends_on: [canary_deployment]
    waves:
      count: 4  # 25% each wave
      delay: 5m
      on_wave_failure: pause
    nodes: "role=web && canary=false"
    steps:
      - name: deploy_wave
        parallel: 10
        command: |
          ln -sfn /app/new /app/current
          systemctl restart webapp

Performance and Scalability Targets

• Support 10,000+ nodes in a single cluster
• Execute 1,000+ parallel operations
• Handle 100+ concurrent workflows
• Process 1M+ operations per hour
• Maintain <100ms operation latency at scale

Security Enhancements

• Script signing and verification
• Role-based access control (RBAC)
• Audit logging for compliance
• Secrets management integration
• Sandboxed execution with resource limits

New Dependencies

# Error handling and resilience
backoff = "0.4"  # Exponential backoff
circuit-breaker = "0.2"  # Circuit breaker pattern

# Orchestration
petgraph = "0.6"  # Dependency graph management
raft = "0.7"  # Leader election

# Workflow management  
rocksdb = "0.22"  # State persistence

# Monitoring
prometheus = "0.13"  # Metrics
opentelemetry = "0.26"  # Tracing

# Security
ring = "0.17"  # Cryptographic signing
jsonwebtoken = "9.3"  # Token validation

Success Criteria

• 99.9% reliability for critical operations
• <1s latency for operation initiation
• Support 100+ concurrent workflows
• Recovery from checkpoint in <30s
• Comprehensive audit trail for compliance
• 90%+ test coverage
• Zero critical security vulnerabilities
• <0.1% failure rate in production

Benefits

1. Enterprise-grade reliability with sophisticated error handling
2. Complex deployment support with orchestration patterns
3. Operational excellence through workflow management
4. Elastic infrastructure with dynamic node management
5. Complete observability with monitoring and alerting
6. Regulatory compliance with audit trails and rollback

Related Work

• Original task document: .claude/tasks/todo/3_enhanced_batch_orchestration.md
• Builds upon: Batch Script Mode (#13)