⚡ Verified Failover Architecture

Correctover implements the MAPE-K autonomic loop (Monitor-Analyze-Plan-Execute over Knowledge) for self-healing LLM API calls. This is the technical foundation behind verified failover.

Core Architecture

L1: In-Process Monitoring (0.4µs)

Every LLM API call is intercepted at the SDK level. The monitor collects response metadata and performance metrics before passing them to the analysis engine.

• ✅ Zero additional network hops
• ✅ No gateway proxy required
• ✅ Works in air-gapped and offline environments

L2: CANON Contract Validation Engine (22µs P50)

Correctover's proprietary CANON engine validates every response across 6 dimensions simultaneously, in-process, before the response reaches application code.

CANON validation process:
1. Parse response → extract structure
2. Validate JSON schema (8µs)
3. Check field types (5µs)
4. Measure latency (1µs)
5. Calculate cost (2µs)
6. Verify model identity (3µs)
7. Semantic coherence check (22µs)
Total P50: 22µs | P99: 99µs

L3: Multi-Provider Failover Chain (949ms E2E)

When contract validation fails on the primary provider, Correctover escalates through the configured fallback chain:

Provider 1 (OpenAI gpt-4o)
  ↓ contract fails → validated=False, reason="schema mismatch"
Provider 2 (Anthropic claude-3-opus)
  ↓ contract fails → validated=False, reason="latency > 5s"
Provider 3 (Google gemini-2.0-pro)
  ↓ contract passes ✅
E2E failover time: 949ms
  ├─ DNS resolution: ~20ms
  ├─ Connection setup: ~150ms
  ├─ API call: ~750ms
  └─ Contract validation: ~22µs

The MAPE-K Autonomic Loop

Monitor

Tracks per-provider metrics: response time, error rate, token usage, contract failure rate, and drift indicators. Runs at 0.4µs per record with 177,582 rec/s throughput.

Analyze

Detects patterns: repeated timeouts → circuit breaker opens; schema drift → alert; cost anomalies → budget cap enforced. Analysis runs at 47µs P99 for 1M samples.

Plan

Selects the optimal failover path based on: failure type, provider health scores, cost budgets, latency requirements, and geographic proximity. The plan is re-evaluated per-request.

Execute

Switches provider, sets up new connection, sends request with the same prompt, and applies contract validation to the response. If validated, returns result; if not, escalates to next plan.

Knowledge

The self-healing rule database grows through the MAPE-K flywheel. Started with 62 high-confidence rules, now 84 (62 high-confidence, verified in 70,000+ fault injection scenarios across 7 failure types).

Drift Detection

Real-time monitoring across all 6 dimensions with automatic alerting. Detects:

• 🔍 Schema drift: field types changing between versions
• 🔍 Latency degradation: gradual response time increases
• 🔍 Cost anomalies: unexpected token usage spikes
• 🔍 Model substitution: provider returns different model than billed
• 🔍 Semantic drift: output quality changes over time

Checkpoint: Long-Chain Resilience

For multi-step agent chains, Correctover's Checkpoint feature saves intermediate states at each validated step. If a chain fails mid-execution, it can be resumed from the last validated checkpoint — no need to restart from scratch.