Stage 4 Overview: Production Hardening Architecture

Context

You are implementing Stage 4 of the DSPex system, focusing on production hardening and advanced features. This stage transforms the DSPex bridge from a functional prototype into a production-ready system with enterprise-grade reliability, security, and performance.

Critical Architectural Decision

ALL advanced features in Stage 4 are implemented ONLY in the BridgedState backend. This is a key architectural decision that:

1. Keeps the fast path fast - pure Elixir workflows remain simple and performant
2. Adds complexity only where needed - hybrid workflows get enterprise features
3. Ensures clean separation of concerns
4. Allows future distributed backends without changing core logic

Overview

Stage 4 introduces:

• Dependency graphs with cycle detection
• Distributed optimizer coordination
• Fine-grained access control
• Performance analytics and monitoring
• High availability patterns
• Circuit breaker implementations
• Production deployment strategies

Architecture

Production Features Layer (BridgedState Only)
├── Dependency Manager (Graph data structure)
├── Optimizer Coordinator (Distributed locking)
├── Access Control System
├── Analytics Engine
└── HA Manager

BridgedState Backend
├── SessionStore (Enhanced with production features)
├── gRPC Handlers (With circuit breakers)
├── ObserverManager (Enhanced monitoring)
└── Circuit Breaker (Resilience pattern)

Monitoring & Observability
├── Telemetry
├── Metrics
└── Distributed Tracing

Future Distributed Backends
├── Redis/Valkey (For distributed state)
└── Raft/etcd (For consensus)

Implementation Phases

Stage 4 is intentionally large and should be implemented iteratively:

1. First iteration: Dependency Management
2. Second iteration: Optimization Coordination
3. Third iteration: Security & Access Control
4. Fourth iteration: HA & Recovery Patterns

Key Design Principles

1. Distributed-Ready: All components use GenServers initially but are designed to swap in distributed backends (Redis, Raft) without logic changes

2. Operational Maturity: Analytics and HAManager are first-class concerns, not afterthoughts

3. Resilience First: Circuit breakers explicitly protect Elixir from Python-side failures

4. Zero Trust: Complete session isolation with fine-grained permissions

5. Observable by Default: Every operation emits telemetry for monitoring

Success Criteria

1. Dependency graphs prevent circular dependencies
2. Optimizers coordinate without conflicts
3. Access control enforces permissions consistently
4. Analytics provide comprehensive visibility
5. Sessions migrate seamlessly for HA
6. Circuit breakers prevent cascading failures

Files You’ll Need

• /home/home/p/g/n/dspex/docs/specs/unified_grpc_bridge/44_revised_stage4_prod_hardening.md - Full specification
• /home/home/p/g/n/dspex/docs/STAGE_4_ADVANCED_FEATURES.md - Original stage 4 vision

Testing Approach

Each production feature requires:

• Unit tests for core logic
• Integration tests for failure modes
• Performance benchmarks
• Load testing scenarios

Example Implementation Pattern

When implementing any Stage 4 feature, follow this pattern:

defmodule DSPex.Bridge.ProductionFeature do
  @moduledoc """
  Production feature for BridgedState backend only.
  """
  
  use GenServer
  require Logger
  
  # Start with GenServer for single-node
  def start_link(opts) do
    GenServer.start_link(__MODULE__, opts, name: __MODULE__)
  end
  
  # Design API for distributed future
  def operation(key, value, opts \\ []) do
    GenServer.call(__MODULE__, {:operation, key, value, opts})
  end
  
  # Emit telemetry for observability
  defp emit_telemetry(event, measurements, metadata) do
    :telemetry.execute(
      [:dspex, :bridge, :feature | event],
      measurements,
      metadata
    )
  end
  
  # Handle failures gracefully
  defp handle_failure(error, context) do
    Logger.error("Feature failed: #{inspect(error)}", context: context)
    {:error, :service_unavailable}
  end
end

Next Steps

Start with implementing the Dependency Manager (prompt 41), as it forms the foundation for reactive variable updates and optimization coordination.