Claude Code Helper for Foundation 2.0 Project
Project Vision
Foundation 2.0 is evolving into the next-generation distributed BEAM framework - a comprehensive platform that combines enhanced core services, Partisan-powered distribution, deep BEAM primitives, and intelligent features. The goal is to create the definitive framework for building scalable, fault-tolerant distributed applications on the BEAM.
Foundation 2.0 Architecture
Layer 1: Enhanced Core Services (Distributed + Intelligent)
Foundation.Config 2.0 # Distributed configuration with consensus
Foundation.Events 2.0 # Cluster-wide event streaming with correlation
Foundation.Telemetry 2.0 # Intelligent metrics with predictive analytics
Foundation.Error 2.0 # Distributed error correlation and learning
Foundation.ServiceRegistry 2.0 # Cross-cluster service mesh
Foundation.ProcessRegistry 2.0 # Distributed process coordination
Layer 2: BEAM Primitives (Partisan-Optimized)
Foundation.BEAM.Distribution # Partisan topology management (replaces libcluster)
Foundation.BEAM.Channels # Multi-channel communication patterns
Foundation.BEAM.Processes # Process ecosystems with distributed coordination
Foundation.BEAM.Messages # Intelligent message passing optimization
Foundation.BEAM.Schedulers # Cluster-aware scheduler coordination
Foundation.BEAM.Memory # Distributed memory management
Layer 3: Distributed Coordination (Partisan-Native)
Foundation.Distributed.Topology # Dynamic topology management
Foundation.Distributed.Consensus # Raft over Partisan channels
Foundation.Distributed.Context # Request tracing across topologies
Foundation.Distributed.State # CRDTs with Partisan broadcast
Foundation.Distributed.Discovery # Multi-strategy node discovery
Foundation.Distributed.Routing # Intelligent message routing
Key Commands
- Run tests:
mix test
- Run specific test categories:
mix test --only contract
mix test --only smoke
mix test --only integration
mix test --only stress
mix test --only benchmark
- Check deps:
mix deps.get
- Compile:
mix compile
Test Structure
test/contract/
- Contract/behavior compliance teststest/smoke/
- Basic system health teststest/integration/
- Service interaction teststest/stress/
- Load and chaos testingtest/benchmark/
- Performance baselinestest/property/
- Property-based teststest/unit/
- Unit tests
Foundation 2.0 Implementation Plan
Phase 1: Enhanced Core Services (Weeks 1-2)
Objective: Transform Foundation’s solid 1.x services into distributed, intelligent systems while maintaining 100% backward compatibility.
Week 1: Core Service Enhancement
- Foundation.Config 2.0 - Distributed configuration with consensus
- Cluster-wide configuration synchronization
- Conflict resolution mechanisms
- Adaptive configuration learning
- All Foundation 1.x APIs preserved
- Foundation.Events 2.0 - Cluster-wide event streaming
- Distributed event emission across cluster
- Intelligent event correlation
- Predictive event routing
- Pattern detection and anomaly detection
- Foundation.Telemetry 2.0 - Intelligent metrics
- Cluster metrics aggregation
- Predictive monitoring
- Anomaly detection
- Optimization recommendations
Week 2: Registry & Error Enhancement
- Foundation.ServiceRegistry 2.0 - Service mesh capabilities
- Cross-cluster service discovery
- Intelligent routing and load balancing
- Health monitoring and failover
- Foundation.ProcessRegistry 2.0 - Distributed coordination
- Cluster-wide process registration
- Distributed process lookup
- Cross-node supervision
- Foundation.Error 2.0 - Distributed error correlation
- Error pattern learning
- Cascade prediction
- Proactive error detection
Phase 2: Partisan Integration (Weeks 3-5)
Objective: Replace libcluster + Distributed Erlang with Partisan-powered distribution that scales to 1000+ nodes.
Week 3: Partisan Foundation
- Foundation.BEAM.Distribution - Partisan integration core
- Replace Distributed Erlang with Partisan
- Multiple overlay strategies (full-mesh, HyParView, client-server)
- Dynamic topology switching
- Foundation.BEAM.Channels - Multi-channel communication
- Separate channels for different traffic types
- Eliminate head-of-line blocking
- Intelligent channel allocation
Week 4: Enhanced Discovery & Topology
- Foundation.Distributed.Discovery - Multi-strategy node discovery
- Kubernetes, Consul, DNS, static configurations
- Failover between discovery mechanisms
- Backward compatibility with libcluster
- Foundation.Distributed.Topology - Dynamic topology management
- Automatic topology optimization based on cluster size
- Performance-aware topology switching
- Partition tolerance strategies
Week 5: Context & Routing
- Foundation.Distributed.Context - Global context propagation
- Request tracing across network boundaries
- Context flowing through async operations
- Distributed debugging support
- Foundation.Distributed.Routing - Intelligent message routing
- Best-path routing across topologies
- Load-aware message distribution
- Latency optimization
Phase 3: BEAM Primitives & Ecosystems (Weeks 6-8)
Objective: Deep BEAM integration with process ecosystems and distributed patterns.
Week 6: Process Ecosystems
- Foundation.BEAM.Processes - Process ecosystems
- Spawn coordinated process groups
- Cross-node supervision trees
- Process society patterns
- Foundation.Ecosystems.Supervision - Distributed supervision
- Fault isolation across nodes
- Restart strategies for distributed processes
Week 7: Communication & Coordination
- Foundation.BEAM.Messages - Intelligent messaging
- Binary optimization for large data
- Flow control and backpressure
- Message pattern optimization
- Foundation.Distributed.Coordination - Distributed coordination primitives
- Distributed locks and barriers
- Leader election with topology awareness
- Consensus algorithms
Week 8: Advanced BEAM Features
- Foundation.BEAM.Schedulers - Scheduler coordination
- Cluster-aware workload distribution
- Scheduler-aware operations
- Reduction counting optimization
- Foundation.BEAM.Memory - Distributed memory management
- Shared binary caches
- Process heap optimization
- Garbage collection coordination
Phase 4: Intelligent Infrastructure (Weeks 9-10)
Objective: Self-managing, adaptive distributed systems with AI-powered optimization.
Week 9: Adaptive Systems
- Foundation.Intelligence.AdaptiveTopology - Self-optimizing networks
- Learn from message patterns and latency
- Automatic topology reconfiguration
- Performance optimization
- Foundation.Intelligence.PredictiveScaling - Predictive node management
- Workload prediction and scaling
- Resource utilization optimization
Week 10: Self-Healing & Evolution
- Foundation.Intelligence.FailurePrediction - Proactive failure detection
- Pattern recognition for failure prediction
- Preventive measures and mitigation
- Foundation.Intelligence.Healing - Self-healing distributed systems
- Automatic recovery from failures
- System evolution based on load patterns
Competitive Advantages
vs. Traditional BEAM Approaches
- libcluster + Distributed Erlang: ~200 node limit, single TCP, head-of-line blocking
- Foundation 2.0: 1000+ nodes, multiple channels, intelligent routing
Key Differentiators
- 100% Backward Compatibility - All Foundation 1.x APIs work unchanged
- Partisan-Powered Distribution - Superior to Distributed Erlang scaling
- Intelligent Features - AI-powered optimization and prediction
- Process Ecosystems - Deep BEAM integration with coordinated process groups
- Self-Managing Infrastructure - Adaptive, healing distributed systems
Migration Path
# Existing Foundation 1.x code - NO CHANGES REQUIRED
Foundation.Config.get([:ai, :provider])
Foundation.Events.new_event(:test, data)
Foundation.Telemetry.emit_counter([:requests], %{})
# New Foundation 2.0 features - OPTIONAL ENHANCEMENTS
Foundation.Config.set_cluster_wide([:feature], true)
Foundation.Events.emit_distributed(:event, data)
Foundation.Telemetry.enable_predictive_monitoring([:cpu])
Foundation.BEAM.Distribution.switch_topology(:full_mesh, :hyparview)
Current Status
- Foundation 1.x stable with 25 passing tests
- Enhanced documentation architecture complete
- Ready to begin Phase 1: Enhanced Core Services implementation
Success Metrics
- Performance: 3-5x faster cluster formation, 2-10x higher message throughput
- Scalability: Support for 1000+ nodes vs ~200 with traditional approaches
- Reliability: 99.9% uptime during network partitions
- Compatibility: 100% backward compatibility with existing Foundation APIs