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L3 Orchestration Layer: Intelligent Context Assembly ​

The Executive Function of Mnemoverse: L3 orchestration intelligently decides what information to include in context under strict resource constraints, making smart trade-offs between quality, speed, and cost.

🎯 What L3 Does (Simple Explanation) ​

When you ask: "How do I fix authentication timeouts in React on mobile?"

L3 orchestration:

  1. CEO understands your intent → "implementation guidance for React mobile auth"
  2. ACS makes smart choices → "search L2 project patterns first, get L4 experience insights, fallback to L1 if needed"
  3. HCS delivers results → assembles the best 3-5 relevant fragments within your token budget

Result: You get precisely what you need, not everything that exists.

🏗️ Components Overview ​

ComponentRoleThink of it as...
CEO (Context/Execution Orchestrator)Intent interpreter & resource manager"Executive assistant" who understands what you really need
ACS (Adaptive Context Scaling)Smart context assembly engine"Research librarian" who finds the best sources within your budget
HCS (Hyperbolic Communication System)Transport & delivery coordinator"Logistics coordinator" who packages and delivers results efficiently

📚 Documentation Navigation ​

🚀 Start Here (Progressive Complexity) ​

  1. Integration Flows ⭐ — See concrete examples of how CEO→ACS→HCS work together
  2. MVP Implementation — Minimal viable orchestration for v0.1
  3. API Contracts — How components communicate

🏗️ Component Deep-Dives ​

🔧 Implementation & Operations ​

🔥 Quick Examples ​

Simple Query: "React auth timeout fix"

CEO: intent="implementation_guidance", budget=3000 tokens, 800ms
ACS: L2 primary → L4 patterns → L1 if gaps
Result: 3 focused fragments, 2847 tokens, 756ms

Complex Query: "Compare state management for large React apps"

CEO: intent="comparative_research", budget=8000 tokens, 2000ms
ACS: L1 authoritative(40%) + L2 projects(30%) + L4 outcomes(30%)
Result: synthesis framework, comparison matrix, decision tree

Resource Pressure: Limited to 1500 tokens, 400ms

ACS: Graceful degradation → L2 only, macro-focused, 3 fragments max
Result: Still actionable guidance, just more concise

Why an orchestrator ​

At each request, we must decide "how much and what to put into context" under strict token/time budgets. The orchestrator (ACS) makes an explicit trade‑off between quality, latency, and budget by selecting sources (L2/L4/L1), the level of detail (LOD), and the ordering of fragments.

Without it: either slow/expensive (load everything) or fast with blind spots (single source).

Causal chain (from general to specific) ​

  1. CEO formulates intent and budgets: { tokens_max, time_ms, risk }
  2. ACS plans under budgets:
    • choose sources (L2 as primary, L4 as hints, L1 as explicit expansion)
    • set LOD: macro → micro → atomic
    • assign per‑provider deadlines (time slices), partial responses allowed
  3. Providers return candidates (snippet + cost + source)
  4. ACS selects by simple benefit/cost, trims to budget, forms KV policy (pin/compress/evict)
  5. HCS: reserved for transport; streaming is disabled in v0 (batch delivery)
  6. L5/client assembles final context → model

Minimal algorithm v0 (heuristics, no ML) ​

  • Input: intent + budgets + risk
  • Plan: sources = [L2] (primary); if insufficient → consider L1 as explicit expansion; L4 is a boosting channel
  • Parallel fetch with per‑provider deadlines; partial accepted
  • Ranking: score = benefit / (1 + cost_tokens)
  • Budget trim: first by time (deadline), then by tokens (reduce LOD, then count)
  • Output: ordered fragments + kv_policy + metrics (used_tokens, planner_ms, source_breakdown)
  • Degradation: prefer L2; allow L1 expansion explicitly when needed

Pseudocode (simplified):

plan = choose_sources(intent, budget)
cands = fetch_parallel(plan, deadlines)
ranked = sort_by(benefit/cost, cands)
frags = trim_to_budget(ranked, tokens_max, LOD_policy)
return { fragments: frags, kv_policy, metrics }

Non‑goals (v0) ​

  • No learned planner (rules only)
  • No deep KG traversal (L1 is vector‑first expansion, not hidden fallback)
  • No raw sensitive text; providers must redact where necessary
  • No long‑term state (except optional small pattern caches)

Roles ​

  • CEO → calls ACS, sets intent and budgets
  • ACS → orchestrates sources (L2/L4/L1), assembles and trims content
  • HCS → transport channel (streaming disabled in v0)

Decision rules v0 (fixed) ​

  • Priorities: Quality → strict token budget adherence → Latency (best‑effort)
  • Budgets: tokens_max is strict; time_ms is a comfort target (no hard fail)
  • Sources: L2 is primary; L1 is explicit expansion (never implicit fallback); L4 boosts hints
  • Expansion flow: if project data is insufficient, emit a warning and go to Noosphere (L1) explicitly
  • Deadlines: per‑provider “time slice”; accept partial responses
  • Budget trim order: reduce LOD first, then fragment count
  • Streaming: disabled in v0 (batch)
  • Failures: no auto‑fallback; retry first and surface structured error/options (see ADR)

Documents ​

Contracts (v0.1) ​

Inputs

  • render_request.v0: { query, intent?, budgets: { tokens_max, time_ms }, risk?, privacy_mode, request_id }
  • provider_request.v0 (internal):

Processing

  • CEO: classify intent, estimate budgets, normalize privacy_mode
  • ACS: choose sources, parallel fetch with deadlines, rank by benefit/cost, trim to budgets, form kv_policy
  • HCS: package response (batch only), attach metrics and warnings

Outputs

  • render_context_reply.v0: { fragments[], kv_policy, metrics: { used_tokens, planner_ms, source_breakdown }, warnings?, error? }

SLO / Targets

  • Planning p95 < 150ms; Fetch window configurable per provider (typ. 300–600ms)
  • End-to-end orchestration (plan+fetch+assemble) p95 < 800ms
  • Budget adherence: 0 hard token overruns; time budget is soft with graceful degradation

Edge Cases

  • Provider timeouts → partial results, warning code PROVIDER_TIMEOUT_&lt;LAYER&gt;
  • Insufficient project context → explicit L1 expansion with warning L2_INSUFFICIENT_COVERAGE
  • Privacy mode = block → only metadata for sensitive fragments

Resilience & Observability ​

Resilience

  • Per-provider circuit breakers (failure_threshold, cooldown_ms)
  • Deadlines with partial acceptance; retries only when safe and cheap
  • Degradation order: reduce LOD → reduce fragment count → drop optional sources

Metrics (Prometheus-like names)

  • orchestration_request_duration_seconds
  • orchestration_budget_utilization
  • orchestration_provider_latency
  • orchestration_budget_violations_total, orchestration_provider_errors_total

Tracing

  • request_id propagation across CEO→ACS→Providers; span attributes: budgets, sources, counts

Privacy & Security ​

Controls

  • privacy_mode: allow|redact|block enforced pre-ranking; blocked fragments surfaced as metadata only
  • No raw sensitive text from providers; contracts require redaction at source adapters

AuthN/Z

  • mTLS inside mesh; JWT with layer claims at boundaries; least-privilege per-role permissions

Audit

  • Structured warnings and decision logs for source expansion and degradations

Operational Excellence ​

Monitoring & Observability ​

Orchestration Metrics:

txt
# Core orchestration performance
orchestration_request_duration_seconds{component="acs", operation="plan"}
orchestration_request_duration_seconds{component="acs", operation="fetch"}
orchestration_request_duration_seconds{component="acs", operation="rank"}

# Budget management metrics
orchestration_budget_utilization{layer="L1", type="tokens"}
orchestration_budget_utilization{layer="L2", type="time_ms"}
orchestration_budget_violations_total{layer="L5", violation_type="timeout"}

# Provider interaction metrics
orchestration_provider_latency{provider="L1", operation="search"}
orchestration_provider_errors{provider="L2", error_type="timeout"}
orchestration_provider_success_rate{provider="L4"}

# Quality metrics
orchestration_context_quality{metric="relevance_score"}
orchestration_context_quality{metric="coherence_score"}
orchestration_fragment_count{layer="L1"}

Alerting Rules:

yaml
# orchestration-alerts.yml
groups:
  - name: orchestration-critical
    rules:
      - alert: OrchestrationHighLatency
        expr: orchestration_request_duration_seconds{quantile="0.95"} > 1.0
        for: 2m
        labels:
          severity: critical
        annotations:
          summary: "Orchestration P95 latency above 1s"
          
      - alert: BudgetViolationHigh
        expr: rate(orchestration_budget_violations_total[5m]) > 0.1
        for: 1m
        labels:
          severity: warning
        annotations:
          summary: "High rate of budget violations"

  - name: orchestration-performance
    rules:
      - alert: ProviderFailureRate
        expr: rate(orchestration_provider_errors[5m]) / rate(orchestration_provider_requests[5m]) > 0.05
        for: 3m
        labels:
          severity: warning
        annotations:
          summary: "High provider failure rate: {{ $labels.provider }}"

Security Model ​

Authentication & Authorization:

yaml
# Security policies for orchestration layer
orchestration_security:
  authentication:
    method: "service_mesh_mTLS"
    token_validation: "jwt_with_layer_claims"
    
  authorization:
    ceo_permissions:
      - "orchestration:plan"
      - "orchestration:budget:allocate"
      - "providers:invoke"
      
    acs_permissions:
      - "providers:search"
      - "providers:rank"
      - "memory:assemble"
      
    provider_permissions:
      - "layer:serve"
      - "metrics:report"

  rate_limiting:
    ceo_requests: "1000/hour"
    acs_operations: "10000/hour"
    provider_calls: "50000/hour"

Security Boundaries:

  • CEO↔ACS: Internal service mesh, encrypted channels
  • ACS↔Providers: Provider authentication, request signing
  • Cross-Layer: Layer isolation, capability-based access

Advanced Testing & Validation ​

Unit Testing Framework ​

ACS Component Testing:

typescript
describe('AdaptiveContextScaling', () => {
  describe('Budget Planning', () => {
    test('allocates budgets within constraints', async () => {
      const intent = {
        query: "debug React authentication",
        urgency: "medium",
        complexity: "high"
      };
      
      const budgets = { tokens_max: 2000, time_ms: 1000 };
      const plan = await acs.createPlan(intent, budgets);
      
      expect(plan.total_budget.tokens).toBeLessThanOrEqual(2000);
      expect(plan.total_budget.time_ms).toBeLessThanOrEqual(1000);
      expect(plan.providers).toHaveLength(3); // L1, L2, L4
    });

    test('adapts plan under budget pressure', async () => {
      const intent = { query: "complex technical query", complexity: "very_high" };
      const restrictiveBudgets = { tokens_max: 500, time_ms: 200 };
      
      const plan = await acs.createPlan(intent, restrictiveBudgets);
      
      // Should reduce LOD and provider count
      expect(plan.lod_profile.atomic).toBeLessThan(20);
      expect(plan.providers.length).toBeLessThanOrEqual(2);
    });
  });

  describe('Fragment Ranking', () => {
    test('ranks fragments by benefit/cost ratio', async () => {
      const fragments = [
        { content: "high value", benefit: 0.9, cost_tokens: 100 },
        { content: "medium value", benefit: 0.7, cost_tokens: 50 },
        { content: "low value", benefit: 0.3, cost_tokens: 200 }
      ];
      
      const ranked = await acs.rankFragments(fragments);
      
      // Should prioritize medium value (best ratio: 0.7/50 = 0.014)
      expect(ranked[0].content).toBe("medium value");
      expect(ranked[1].content).toBe("high value");
      expect(ranked[2].content).toBe("low value");
    });
  });
});

CEO Component Testing:

typescript
describe('ContextExecutionOrchestrator', () => {
  describe('Intent Processing', () => {
    test('classifies query intent correctly', async () => {
      const queries = [
        { text: "fix authentication bug", expected: "debug_issue" },
        { text: "explain React hooks", expected: "learn_concept" },
        { text: "implement OAuth flow", expected: "build_feature" }
      ];
      
      for (const query of queries) {
        const intent = await ceo.classifyIntent(query.text);
        expect(intent.primary).toBe(query.expected);
        expect(intent.confidence).toBeGreaterThan(0.7);
      }
    });

    test('estimates resource budgets appropriately', async () => {
      const complexQuery = "implement distributed caching with Redis cluster";
      const simpleQuery = "what is a variable";
      
      const complexBudgets = await ceo.estimateBudgets(complexQuery);
      const simpleBudgets = await ceo.estimateBudgets(simpleQuery);
      
      expect(complexBudgets.tokens_max).toBeGreaterThan(simpleBudgets.tokens_max);
      expect(complexBudgets.time_ms).toBeGreaterThan(simpleBudgets.time_ms);
    });
  });
});

Integration Testing ​

End-to-End Orchestration Flow:

typescript
describe('Orchestration Integration', () => {
  test('complete CEO→ACS→Providers flow', async () => {
    const userQuery = "debug memory leak in React component";
    
    // 1. CEO processes intent
    const intent = await ceo.processQuery(userQuery);
    expect(intent.primary).toBe("debug_issue");
    
    // 2. ACS creates plan
    const plan = await acs.createPlan(intent, intent.budgets);
    expect(plan.providers).toContain("L2"); // Should include project library
    
    // 3. Execute provider calls
    const results = await acs.executeProviders(plan);
    expect(results.fragments.length).toBeGreaterThan(0);
    
    // 4. Assemble final context
    const context = await acs.assembleContext(results, plan.budgets);
    expect(context.total_tokens).toBeLessThanOrEqual(plan.budgets.tokens_max);
    
    // 5. Verify quality metrics
    expect(context.quality_score).toBeGreaterThan(0.6);
    expect(context.relevance_score).toBeGreaterThan(0.7);
  });
});

Chaos Engineering ​

Orchestration Resilience Testing:

typescript
describe('Orchestration Chaos Tests', () => {
  test('handles provider failures gracefully', async () => {
    // Simulate L1 provider failure
    mockProvider.L1.simulateFailure({ type: 'timeout', duration: 5000 });
    
    const intent = { query: "technical question", budgets: { tokens_max: 1000, time_ms: 800 } };
    const result = await orchestrator.processRequest(intent);
    
    // Should complete with L2/L4 providers only
    expect(result.success).toBe(true);
    expect(result.warnings).toContain('L1_PROVIDER_UNAVAILABLE');
    expect(result.context.source_breakdown.L1).toBe(0);
    expect(result.context.source_breakdown.L2).toBeGreaterThan(0);
  });

  test('manages resource exhaustion', async () => {
    // Simulate high load scenario
    const concurrentRequests = Array.from({ length: 100 }, (_, i) => ({
      query: `concurrent query ${i}`,
      budgets: { tokens_max: 2000, time_ms: 1000 }
    }));
    
    const results = await Promise.allSettled(
      concurrentRequests.map(req => orchestrator.processRequest(req))
    );
    
    const successful = results.filter(r => r.status === 'fulfilled').length;
    const failed = results.filter(r => r.status === 'rejected').length;
    
    // System should handle graceful degradation
    expect(successful / (successful + failed)).toBeGreaterThan(0.8);
  });
});

Performance Optimization ​

Caching Strategies ​

ACS Performance Optimization:

typescript
class OptimizedACS {
  private planCache = new LRUCache<string, ExecutionPlan>({ max: 1000, ttl: 300000 });
  private fragmentCache = new LRUCache<string, Fragment[]>({ max: 5000, ttl: 600000 });
  
  async createOptimizedPlan(intent: Intent, budgets: Budgets): Promise<ExecutionPlan> {
    const cacheKey = this.generatePlanCacheKey(intent, budgets);
    
    // Check plan cache first
    const cachedPlan = this.planCache.get(cacheKey);
    if (cachedPlan && this.isPlanStillValid(cachedPlan)) {
      return cachedPlan;
    }
    
    // Create new plan with performance optimizations
    const plan = await this.createPlan(intent, budgets);
    
    // Optimize provider selection based on historical performance
    plan.providers = await this.optimizeProviderSelection(plan.providers);
    
    // Cache for future use
    this.planCache.set(cacheKey, plan);
    
    return plan;
  }
  
  private async optimizeProviderSelection(providers: Provider[]): Promise<Provider[]> {
    const performanceStats = await this.getProviderPerformanceStats();
    
    return providers.sort((a, b) => {
      const aScore = (performanceStats[a.id]?.success_rate || 0.5) / 
                     (performanceStats[a.id]?.avg_latency_ms || 1000);
      const bScore = (performanceStats[b.id]?.success_rate || 0.5) / 
                     (performanceStats[b.id]?.avg_latency_ms || 1000);
      return bScore - aScore;
    });
  }
}

Comprehensive Testing & Validation Framework ​

Component Testing Strategy ​

Orchestration Layer Testing Pyramid:

typescript
describe('Orchestration Integration Tests', () => {
  describe('CEO → ACS → HCS Flow', () => {
    test('complete context assembly workflow', async () => {
      const user_query = "implement JWT authentication with role-based access control";
      
      // 1. CEO processes user intent
      const ceo_response = await ceo.processUserRequest({
        query: user_query,
        context: { project_type: "nodejs-express" },
        user_id: "test-user-001"
      });
      
      expect(ceo_response.acs_request.intent).toBe("implement_authentication_system");
      expect(ceo_response.acs_request.budgets.tokens_max).toBeGreaterThan(2000);
      
      // 2. ACS processes context request
      const acs_response = await acs.processContextRequest(ceo_response.acs_request);
      
      expect(acs_response.fragments.length).toBeGreaterThan(3);
      expect(acs_response.metrics.quality_score).toBeGreaterThan(0.75);
      expect(acs_response.kv_policy.pin.length).toBeGreaterThan(0);
      
      // 3. HCS handles delivery (batch mode in v0)
      const hcs_response = await hcs.deliverContext({
        fragments: acs_response.fragments,
        delivery_mode: "batch",
        user_preferences: { format: "structured" }
      });
      
      expect(hcs_response.success).toBe(true);
      expect(hcs_response.delivered_fragments.length).toBe(acs_response.fragments.length);
      
      // 4. End-to-end validation
      const final_context = hcs_response.assembled_context;
      expect(final_context.total_tokens).toBeLessThanOrEqual(ceo_response.acs_request.budgets.tokens_max);
      expect(final_context.coherence_score).toBeGreaterThan(0.8);
    });
    
    test('handles provider failures gracefully', async () => {
      // Simulate L1 provider failure
      mockProviderRegistry.simulateFailure('L1', { type: 'timeout', duration: 3000 });
      
      const user_query = "research distributed consensus algorithms";
      const ceo_response = await ceo.processUserRequest({ query: user_query, context: {}, user_id: "test-user-002" });
      const acs_response = await acs.processContextRequest(ceo_response.acs_request);
      
      // Should complete with L2/L4 providers
      expect(acs_response.fragments.length).toBeGreaterThan(0);
      expect(acs_response.warnings).toContain('L1_PROVIDER_TIMEOUT');
      expect(acs_response.metrics.source_breakdown.L1).toBe(0);
      expect(acs_response.metrics.source_breakdown.L2 + acs_response.metrics.source_breakdown.L4).toBeGreaterThan(0);
    });
  });

  describe('Budget Management Across Components', () => {
    test('enforces budget constraints end-to-end', async () => {
      const restrictive_budget = { tokens_max: 1000, time_ms: 500 };
      const complex_query = "comprehensive system architecture analysis";
      
      const ceo_response = await ceo.processUserRequest({
        query: complex_query,
        budget_constraints: restrictive_budget,
        user_id: "budget-test-user"
      });
      
      expect(ceo_response.acs_request.budgets.tokens_max).toBeLessThanOrEqual(1000);
      expect(ceo_response.acs_request.budgets.time_ms).toBeLessThanOrEqual(500);
      
      const acs_response = await acs.processContextRequest(ceo_response.acs_request);
      
      expect(acs_response.metrics.total_tokens_used).toBeLessThanOrEqual(1000);
      expect(acs_response.metrics.processing_time_ms).toBeLessThanOrEqual(500);
      
      // Quality should degrade gracefully under budget pressure
      expect(acs_response.metrics.quality_score).toBeGreaterThan(0.6); // Acceptable degradation
    });
  });
});

Performance Testing ​

Load Testing Framework:

typescript
describe('Orchestration Performance Tests', () => {
  test('meets system-wide latency SLA under load', async () => {
    const concurrent_requests = 200;
    const test_queries = [
      "debug authentication issue",
      "implement payment processing", 
      "optimize database performance",
      "set up monitoring system",
      "create user dashboard"
    ];
    
    const requests = Array.from({ length: concurrent_requests }, (_, i) => ({
      query: test_queries[i % test_queries.length],
      context: { test_id: i },
      user_id: `load-test-user-${i}`
    }));
    
    const start_time = Date.now();
    const results = await Promise.allSettled(
      requests.map(async (req) => {
        const ceo_response = await ceo.processUserRequest(req);
        const acs_response = await acs.processContextRequest(ceo_response.acs_request);
        return { ceo_response, acs_response };
      })
    );
    const total_time = Date.now() - start_time;
    
    const successful_results = results.filter(r => r.status === 'fulfilled');
    const success_rate = successful_results.length / results.length;
    
    // System-wide performance targets
    expect(success_rate).toBeGreaterThan(0.95); // 95% success rate
    expect(total_time).toBeLessThan(30000); // 200 requests in < 30 seconds
    
    // Individual request performance
    const response_times = successful_results.map(r => 
      (r as PromiseFulfilledResult<any>).value.acs_response.metrics.processing_time_ms
    );
    const p95_latency = response_times.sort()[Math.floor(response_times.length * 0.95)];
    expect(p95_latency).toBeLessThan(2000); // P95 < 2s end-to-end
  });
});

Production Operations Excellence ​

System-Wide Monitoring ​

Orchestration Observability Dashboard:

yaml
# Comprehensive monitoring configuration
orchestration_monitoring:
  dashboards:
    - name: "Orchestration Overview"
      panels:
        - title: "End-to-End Request Flow"
          type: "sankey"
          query: |
            sum(rate(orchestration_requests_total[5m])) by (component, status)
          
        - title: "Budget Utilization Efficiency"
          type: "gauge"
          query: |
            avg(orchestration_budget_utilization{type="tokens"}) * 100
          target: 85 # Target 85% utilization efficiency
          
        - title: "Cross-Component Latency Breakdown"
          type: "stacked_bar"
          queries:
            ceo_latency: avg(ceo_processing_duration_seconds) * 1000
            acs_latency: avg(acs_processing_duration_seconds) * 1000
            hcs_latency: avg(hcs_delivery_duration_seconds) * 1000
            
    - name: "Quality & User Experience"
      panels:
        - title: "Context Quality Score Trend"
          type: "line"
          query: |
            avg_over_time(orchestration_context_quality[1h])
          target: 0.8
          
        - title: "User Satisfaction by Query Type"
          type: "heatmap"
          query: |
            avg(ceo_user_satisfaction_score) by (query_type, user_segment)
            
        - title: "Provider Health Matrix"
          type: "table"
          query: |
            avg(orchestration_provider_success_rate) by (provider_id)

  alert_groups:
    - name: "orchestration-critical"
      rules:
        - alert: "OrchestrationCascadeFailure"
          expr: |
            (
              rate(ceo_errors_total[5m]) > 0.05 AND
              rate(acs_errors_total[5m]) > 0.05 AND
              rate(hcs_errors_total[5m]) > 0.05
            )
          for: 1m
          severity: critical
          annotations:
            summary: "Multiple orchestration components failing simultaneously"
            runbook: "https://docs.mnemoverse.com/runbooks/orchestration-cascade-failure"
            
        - alert: "OrchestrationQualityDegradation"
          expr: |
            avg(orchestration_context_quality) < 0.6
          for: 3m
          severity: warning
          annotations:
            summary: "Context quality below acceptable threshold"
            
    - name: "orchestration-performance"
      rules:
        - alert: "OrchestrationHighLatency"
          expr: |
            histogram_quantile(0.95, orchestration_request_duration_seconds) > 2.0
          for: 2m
          severity: warning
          
        - alert: "BudgetWasteHigh"
          expr: |
            (1 - avg(orchestration_budget_utilization)) > 0.3
          for: 5m
          severity: warning

Deployment Architecture ​

Production Deployment Strategy:

yaml
# Multi-region orchestration deployment
apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: mnemoverse-orchestration
  namespace: argocd
spec:
  project: mnemoverse
  source:
    repoURL: https://github.com/mnemoverse/orchestration
    targetRevision: main
    path: k8s/overlays/production
  destination:
    server: https://kubernetes.default.svc
    namespace: mnemoverse-orchestration
  syncPolicy:
    automated:
      prune: true
      selfHeal: true
    syncOptions:
      - CreateNamespace=true
---
# Service mesh configuration
apiVersion: networking.istio.io/v1beta1
kind: VirtualService
metadata:
  name: orchestration-routing
spec:
  hosts:
  - orchestration.mnemoverse.internal
  http:
  - match:
    - headers:
        x-user-tier:
          exact: premium
    route:
    - destination:
        host: orchestration-premium
        port:
          number: 80
      weight: 100
  - route:
    - destination:
        host: orchestration-standard
        port:
          number: 80
      weight: 100
---
# Circuit breaker configuration
apiVersion: networking.istio.io/v1beta1
kind: DestinationRule
metadata:
  name: orchestration-circuit-breaker
spec:
  host: orchestration.mnemoverse.internal
  trafficPolicy:
    outlierDetection:
      consecutiveErrors: 3
      interval: 30s
      baseEjectionTime: 30s
      maxEjectionPercent: 50
    connectionPool:
      tcp:
        maxConnections: 100
      http:
        http1MaxPendingRequests: 50
        maxRequestsPerConnection: 10

Disaster Recovery ​

Orchestration DR Strategy:

typescript
class OrchestrationDisasterRecovery {
  async executeFailoverProcedure(failure_type: FailureType): Promise<FailoverResult> {
    const recovery_plan = this.getRecoveryPlan(failure_type);
    
    switch (failure_type) {
      case 'REGION_OUTAGE':
        return this.handleRegionFailover(recovery_plan);
        
      case 'DATABASE_FAILURE':
        return this.handleDatabaseFailover(recovery_plan);
        
      case 'PROVIDER_CASCADE_FAILURE':
        return this.handleProviderFailover(recovery_plan);
        
      case 'COMPUTE_RESOURCE_EXHAUSTION':
        return this.handleResourceFailover(recovery_plan);
        
      default:
        return this.handleGenericFailover(recovery_plan);
    }
  }
  
  private async handleRegionFailover(plan: RecoveryPlan): Promise<FailoverResult> {
    // 1. Detect healthy regions
    const healthy_regions = await this.detectHealthyRegions();
    
    // 2. Redirect traffic
    await this.updateTrafficRouting(healthy_regions);
    
    // 3. Scale up in healthy regions
    await this.scaleUpInRegions(healthy_regions, plan.scale_factor);
    
    // 4. Synchronize state
    await this.synchronizeCriticalState(healthy_regions);
    
    // 5. Update monitoring
    await this.updateMonitoringTargets(healthy_regions);
    
    return {
      success: true,
      recovery_time_seconds: Date.now() - plan.start_time,
      active_regions: healthy_regions,
      estimated_capacity: plan.target_capacity * 0.8 // 80% capacity during DR
    };
  }
}

Security Framework ​

Multi-Layer Security Architecture ​

Security Implementation:

typescript
interface OrchestrationSecurityFramework {
  network_security: {
    service_mesh: "istio";
    mtls_enforcement: boolean;
    network_policies: NetworkPolicy[];
    ingress_protection: WAFConfig;
  };
  
  application_security: {
    authentication: JWTConfig;
    authorization: RBACConfig;
    input_validation: ValidationConfig;
    output_sanitization: SanitizationConfig;
  };
  
  data_security: {
    encryption_at_rest: EncryptionConfig;
    encryption_in_transit: TLSConfig;
    data_classification: DataClassificationPolicy;
    pii_handling: PIIHandlingConfig;
  };
  
  monitoring_security: {
    audit_logging: AuditConfig;
    intrusion_detection: IDSConfig;
    vulnerability_scanning: VulnScanConfig;
    compliance_monitoring: ComplianceConfig;
  };
}

class OrchestrationSecurityManager {
  async performSecurityValidation(
    request: OrchestrationRequest,
    context: SecurityContext
  ): Promise<SecurityValidationResult> {
    
    const validations = await Promise.all([
      this.validateNetworkSecurity(request, context),
      this.validateApplicationSecurity(request, context), 
      this.validateDataSecurity(request, context),
      this.performThreatDetection(request, context)
    ]);
    
    const security_score = this.calculateSecurityScore(validations);
    
    if (security_score < this.security_threshold) {
      await this.triggerSecurityIncident({
        type: 'security_validation_failure',
        request_id: request.id,
        validations: validations.filter(v => !v.passed),
        severity: this.calculateSeverity(security_score)
      });
      
      return {
        approved: false,
        block_request: security_score < 0.3,
        required_mitigations: this.generateMitigations(validations)
      };
    }
    
    return { approved: true, security_score };
  }
}

Implementation Roadmap ​

Phase 1: Core Orchestration (v0.1) - 6 weeks ​

Weeks 1-3: Component Implementation

  • [ ] CEO: Intent processing and budget allocation
  • [ ] ACS: Context assembly and provider orchestration
  • [ ] HCS: Basic batch delivery (streaming disabled)
  • [ ] Integration layer and contract validation
  • [ ] Unit and integration testing frameworks

Weeks 4-6: System Integration

  • [ ] End-to-end workflow implementation
  • [ ] Error handling and graceful degradation
  • [ ] Basic monitoring and logging
  • [ ] Performance optimization and tuning
  • [ ] Security framework implementation

Phase 2: Production Hardening (v0.2) - 4 weeks ​

Weeks 1-2: Reliability & Performance

  • [ ] Comprehensive monitoring and alerting
  • [ ] Auto-scaling and load balancing
  • [ ] Disaster recovery procedures
  • [ ] Performance benchmarking and optimization

Weeks 3-4: Security & Compliance

  • [ ] Security penetration testing
  • [ ] GDPR compliance implementation
  • [ ] Audit logging and compliance reporting
  • [ ] Production readiness assessment

Phase 3: Advanced Features (v0.3) - 8 weeks ​

Weeks 1-4: Intelligent Orchestration

  • [ ] Machine learning integration for optimization
  • [ ] Adaptive budget management
  • [ ] Personalized orchestration strategies
  • [ ] Advanced caching and prediction

Weeks 5-8: Enhanced Capabilities

  • [ ] Streaming context delivery (HCS v2)
  • [ ] Multi-modal orchestration support
  • [ ] Advanced privacy-preserving techniques
  • [ ] Federated orchestration capabilities

Success Criteria ​

System Performance:

  • End-to-end P95 latency < 2 seconds
  • System availability > 99.95%
  • Budget utilization efficiency > 85%
  • Context quality score > 0.8
  • Provider failure tolerance > 99%

User Experience:

  • User satisfaction rating > 4.3/5.0
  • Intent classification accuracy > 92%
  • Clarification request rate < 12%
  • Task completion success rate > 88%

Operational Excellence:

  • Security incident rate < 0.001%
  • MTTR < 5 minutes for critical issues
  • Deployment frequency: daily
  • Change failure rate < 2%

Component Specifications: ​

  • ACS (Adaptive Context Scaling): acs/README.md — Cognitive budget management and context assembly
  • ACS Technical Specification: acs/architecture.md — Comprehensive technical specification (28,000+ lines)
  • CEO (Context/Execution Orchestrator): ceo/README.md — Intent interpretation and resource management
  • CEO Technical Specification: ceo/architecture.md — Detailed cognitive architecture specification
  • HCS (Hyperbolic Communication System): hcs/README.md — Transport and delivery coordination (Stage 2)

API & Integration: ​

System Architecture: ​

Status: Core architecture complete → Implementation in progress → Production target (v0.2)

Next Priority: Focus on Phase 1 implementation — CEO intent processing, ACS context assembly, and basic HCS delivery with comprehensive testing and monitoring frameworks.