mev-beta/docs/MONITORING_PRODUCTION_READINESS.md

MEV Bot Monitoring & Metrics Infrastructure Survey

Production Deployment Gap Analysis

Date: October 23, 2025
Status: Medium Thoroughness Assessment
Overall Readiness: 65% (Moderate Gaps Identified)

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Executive Summary

The MEV bot has substantial monitoring infrastructure with custom health checking, data integrity monitoring, and basic metrics exposure. However, critical production gaps exist in:

• Prometheus-standard metrics export
• Distributed tracing/observability
• Kubernetes-native probes (readiness/liveness/startup)
• SLO/SLA frameworks
• Production-grade performance profiling

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1. Metrics Collection & Export

CURRENT IMPLEMENTATION: 65% Complete

What's Working:

• Custom Metrics Server (pkg/metrics/metrics.go)

  • JSON metrics endpoint at /metrics
  • Manual Prometheus format at /metrics/prometheus
  • Business metrics: L2 messages, arbitrage opportunities, trades, profits
  • Auth-protected endpoints (127.0.0.1 only)
  • Port configurable via METRICS_PORT env var (default: 9090)

• Metrics Collected:

  • L2 message processing (rate, lag)
  • DEX interactions & swap opportunities
  • Trade success/failure rates & profits
  • Gas costs and profit factors
  • System uptime in seconds

Critical GAPS:

• NO Prometheus client library integration - Manual text formatting instead of prometheus/client_golang
• NO histogram/distribution metrics - Only point-in-time values
• NO custom metric registration - Cannot add new metrics without modifying core code
• NO metric cardinality control - Risk of metric explosion
• NO scrape-friendly format validation - Manual string concatenation prone to syntax errors
• NO metrics retention - Snapshots lost on restart
• NO dimensional/labeled metrics - Cannot slice data by operation, module, or error type

Recommendation:

import "github.com/prometheus/client_golang/prometheus"
import "github.com/prometheus/client_golang/prometheus/promhttp"

// Replace manual metrics with Prometheus client
var (
    l2MessagesTotal = prometheus.NewCounterVec(
        prometheus.CounterOpts{Name: "mev_bot_l2_messages_total"},
        []string{"status"},
    )
    processingLatency = prometheus.NewHistogramVec(
        prometheus.HistogramOpts{
            Name: "mev_bot_processing_latency_seconds",
            Buckets: prometheus.DefBuckets,
        },
        []string{"stage"},
    )
)

// Serve at /metrics using promhttp.Handler()

---

2. Performance Monitoring & Profiling Hooks

CURRENT IMPLEMENTATION: 50% Complete

What's Working:

• Performance Profiler (pkg/security/performance_profiler.go)

  • Operation-level performance tracking
  • Resource usage monitoring (heap, goroutines, GC)
  • Performance classification (excellent/good/average/poor/critical)
  • Alert generation for threshold violations
  • Comprehensive report generation with bottleneck analysis
  • 2,000+ lines of detailed profiling infrastructure

• Profiling Features:

  • Min/max/avg response times per operation
  • Error rate tracking and trend analysis
  • Memory efficiency scoring
  • CPU efficiency calculation
  • GC efficiency metrics
  • Recommendations for optimization

Critical GAPS:

• NO pprof integration - Cannot attach to net/http/pprof for live profiling
• NO CPU profiling endpoint - No /debug/pprof/profile available
• NO memory profiling endpoint - No heap dump capability
• NO goroutine profiling - Cannot inspect goroutine stacks
• NO flamegraph support - No integration with go-torch or pprof web UI
• NO continuous profiling - Manual operation tracking only
• NO profile persistence - Reports generated in-memory, not saved

Implementation Status:

// Currently exists:
pp := NewPerformanceProfiler(logger, config)
tracker := pp.StartOperation("my_operation")
// ... do work ...
tracker.End()
report, _ := pp.GenerateReport()  // Custom report

// MISSING:
import _ "net/http/pprof"
// http://localhost:6060/debug/pprof/profile?seconds=30
// http://localhost:6060/debug/pprof/heap
// http://localhost:6060/debug/pprof/goroutine

Recommendation:

import _ "net/http/pprof"

// In main startup
go func() {
    log.Info("pprof server starting", "addr", ":6060")
    log.Error("pprof error", "err", http.ListenAndServe(":6060", nil))
}()

// Now supports:
// curl http://localhost:6060/debug/pprof/ - profile index
// go tool pprof http://localhost:6060/debug/pprof/profile?seconds=30 - CPU
// go tool pprof http://localhost:6060/debug/pprof/heap - Memory
// go tool pprof http://localhost:6060/debug/pprof/goroutine - Goroutines

---

3. Real-Time Alerting & Dashboard Systems

CURRENT IMPLEMENTATION: 75% Complete

What's Working:

• Alert Handlers (internal/monitoring/alert_handlers.go)

  • Log-based alerts (structured logging)
  • File-based alerts (JSON JSONL format)
  • HTTP webhook support (Slack, Discord, generic)
  • Metrics-based counters
  • Composite handler pattern (multiple handlers)
  • Automatic webhook type detection (Slack vs Discord)
  • Retry logic with exponential backoff (3 retries)

• Monitoring Dashboard (internal/monitoring/dashboard.go)

  • HTML5 responsive dashboard at port 8080 (configurable)
  • Real-time health metrics display
  • Auto-refresh every 30 seconds
  • JSON API endpoints:
    • /api/health - current health status
    • /api/metrics - system metrics
    • /api/history?count=N - historical snapshots
    • /api/alerts?limit=N - alert records
  • Integrity monitoring metrics display
  • Performance classification cards
  • Recovery action tracking

Critical GAPS:

• NO email alerts - Only webhooks/logging
• NO SMS/Slack bot integration - Only generic webhooks
• NO alert aggregation/deduplication - Every alert fires independently
• NO alert silencing/suppression - Cannot silence known issues
• NO correlation/grouping - Similar alerts not grouped
• NO escalation policies - No severity-based notification routing
• NO PagerDuty integration - Cannot create incidents
• NO dashboard persistence - Metrics reset on restart
• NO multi-user access control - No RBAC for dashboard
• NO alert acknowledgment/tracking - No alert lifecycle management
• NO custom dashboard widgets - Fixed layout

Recommendation (Priority: HIGH):

// Add alert correlation and deduplication
type AlertManager struct {
    alerts      map[string]*Alert  // deduplicated by fingerprint
    suppressions map[string]time.Time
    escalations  map[AlertSeverity][]Handler
}

// Add PagerDuty integration
import "github.com/PagerDuty/go-pagerduty"

// Add email support
import "net/smtp"

// Implement alert lifecycle
type Alert struct {
    ID          string
    Status      AlertStatus  // TRIGGERED, ACKNOWLEDGED, RESOLVED
    AckTime     time.Time
    Resolution  string
}

---

4. Health Check & Readiness Probe Implementations

CURRENT IMPLEMENTATION: 55% Complete

What's Working:

• Metrics Health Endpoint (pkg/metrics/metrics.go)

  • /health endpoint returns JSON status
  • Updates last_health_check timestamp
  • Returns HTTP 200 when healthy
  • Simple liveness indicator

• Lifecycle Health Monitor (pkg/lifecycle/health_monitor.go)

  • Comprehensive module health tracking
  • Parallel/sequential health checks
  • Check timeout enforcement
  • Health status aggregation
  • Health trends (improving/stable/degrading/critical)
  • Notification on status changes
  • Configurable failure/recovery thresholds
  • 1,000+ lines of health management

• Integrity Health Runner (internal/monitoring/health_checker.go)

  • Periodic health checks (30s default)
  • Health history tracking (last 100 snapshots)
  • Corruption rate monitoring
  • Validation success tracking
  • Contract call success rate
  • Health trend calculation
  • Warm-up suppression (prevents early false alerts)

Critical GAPS:

• NO Kubernetes liveness probe format - Only JSON, not Kubernetes-compatible
• NO startup probe - Cannot detect initialization delays
• NO readiness probe - Cannot detect degraded-but-running state
• NO individual service probes - Cannot probe individual modules
• NO external health check integration - Only self-checks
• NO health check history export - Cannot retrieve past health data
• NO SLO-based health thresholds - Thresholds hardcoded
• NO health events/timestamps - Only current status
• NO health check dependencies - Cannot define "Module A healthy only if Module B healthy"

Kubernetes Probes Implementation (CRITICAL MISSING):

The application is NOT Kubernetes-ready without these probes:

# MISSING CONFIG - Must be added to deployment
livenessProbe:
  httpGet:
    path: /health/live      # NOT IMPLEMENTED
    port: 9090
  initialDelaySeconds: 30
  periodSeconds: 10

readinessProbe:
  httpGet:
    path: /health/ready     # NOT IMPLEMENTED
    port: 9090
  initialDelaySeconds: 5
  periodSeconds: 5

startupProbe:
  httpGet:
    path: /health/startup   # NOT IMPLEMENTED
    port: 9090
  failureThreshold: 30
  periodSeconds: 10

Recommendation (Priority: CRITICAL):

// Add Kubernetes-compatible probes
func handleLivenessProbe(w http.ResponseWriter, r *http.Request) {
    // Return 200 if process is still running
    // Return 500 if deadlock detected (watchdog timeout)
    status := "ok"
    if time.Since(lastHeartbeat) > 2*time.Minute {
        w.WriteHeader(http.StatusInternalServerError)
        w.Write([]byte(`{"status": "deadlock_detected"}`))
        return
    }
    w.WriteHeader(http.StatusOK)
    w.Write([]byte(`{"status": "` + status + `"}`))
}

func handleReadinessProbe(w http.ResponseWriter, r *http.Request) {
    // Return 200 only if:
    // 1. RPC connection healthy
    // 2. Database healthy
    // 3. All critical services initialized
    // 4. No degraded conditions
    if !isReady() {
        w.WriteHeader(http.StatusServiceUnavailable)
        w.Write([]byte(`{"status": "not_ready", "reason": "..."`))
        return
    }
    w.WriteHeader(http.StatusOK)
    w.Write([]byte(`{"status": "ready"}`))
}

func handleStartupProbe(w http.ResponseWriter, r *http.Request) {
    // Return 200 only after initialization complete
    // Can take up to 5 minutes for complex startup
    if !isInitialized {
        w.WriteHeader(http.StatusServiceUnavailable)
        return
    }
    w.WriteHeader(http.StatusOK)
}

---

5. Production Logging & Audit Trail Systems

CURRENT IMPLEMENTATION: 80% Complete

What's Working:

• Structured Logging (internal/logger/logger.go)

  • Slog integration with JSON/text formats
  • Multiple log levels (debug, info, warn, error)
  • File output with configurable paths
  • Configurable via environment
  • Key-value pair support

• Secure Filter (internal/logger/secure_filter.go)

  • Filters sensitive data (keys, passwords, secrets)
  • Prevents credential leaks in logs
  • Pattern-based filtering
  • Audit-safe output

• Audit Logging (internal/logger/secure_audit.go)

  • Security event logging
  • Transaction tracking
  • Key operation audit trail
  • Configurable audit log file

• Log Rotation (External)

  • scripts/log-manager.sh - comprehensive log management
  • Archiving with compression
  • Health monitoring
  • Real-time analysis
  • Performance tracking
  • Daemon monitoring

Critical GAPS:

• NO audit log integrity verification - Cannot verify logs haven't been tampered
• NO log aggregation client - No ELK/Splunk/Datadog shipping
• NO log correlation IDs - Cannot trace requests across services
• NO log rate limiting - Could be DoS'd with logs
• NO structured event schema validation - Logs could have inconsistent structure
• NO log retention policies - Manual cleanup only
• NO encrypted log storage - Audit logs unencrypted at rest
• NO log signing/verification - No cryptographic integrity proof
• NO compliance logging (GDPR/SOC2)** - No data residency controls

Recommendation (Priority: MEDIUM):

// Add correlation IDs
type RequestContext struct {
    CorrelationID string  // Unique per request
    UserID        string
    Timestamp     time.Time
}

// Add structured audit events
type AuditEvent struct {
    EventType   string                 `json:"event_type"`
    Timestamp   time.Time              `json:"timestamp"`
    Actor       string                 `json:"actor"`
    Resource    string                 `json:"resource"`
    Action      string                 `json:"action"`
    Result      string                 `json:"result"`  // success/failure
    Reason      string                 `json:"reason"`  // if failure
    CorrelationID string                `json:"correlation_id"`
}

// Add log forwarding
import "github.com/fluent/fluent-logger-golang/fluent"

---

Summary Table: Monitoring Readiness

Component	Implemented	Gaps	Priority	Grade
Metrics Export	JSON + basic Prometheus	No prometheus/client_golang, no cardinality control	HIGH	C+
Performance Profiling	Custom profiler, no pprof	No /debug/pprof endpoints, no live profiling	HIGH	C
Alerting	Webhooks + logging	No dedup, no escalation, no PagerDuty	MEDIUM	B-
Dashboards	HTML5 real-time	No persistence, no RBAC, no widgets	MEDIUM	B
Health Checks	Lifecycle + integrity	No K8s probes, no readiness/liveness/startup	CRITICAL	D+
Logging	Structured + secure	No correlation IDs, no aggregation, no integrity	MEDIUM	B
Overall	65% coverage	Critical K8s gaps, incomplete observability	HIGH	C+

---

Implementation Priority Matrix

PHASE 1: Critical (Must have for production K8s)

• Add Kubernetes probe handlers (readiness/liveness/startup) - 3 hours
• Integrate prometheus/client_golang - 4 hours
• Add pprof endpoints - 1 hour
• Implement alert deduplication - 2 hours
• Total: 10 hours - Enables Kubernetes deployment

PHASE 2: High (Production monitoring)

• Add correlation IDs to logging - 3 hours
• Implement log aggregation (Fluent/Datadog) - 4 hours
• Add PagerDuty integration - 2 hours
• Implement alert silencing - 2 hours
• Add metrics retention/export - 3 hours
• Total: 14 hours - Production-grade observability

PHASE 3: Medium (Hardening)

• Add audit log integrity verification - 3 hours
• Implement log encryption at rest - 2 hours
• Add SLO/SLA framework - 4 hours
• Implement health check dependencies - 2 hours
• Add dashboard persistence - 2 hours
• Total: 13 hours - Enterprise-grade logging

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Critical Files to Modify

HIGHEST PRIORITY:
├── cmd/mev-bot/main.go              (Add K8s probes, pprof, Prometheus)
├── pkg/metrics/metrics.go            (Replace with prometheus/client_golang)
└── internal/monitoring/alert_handlers.go  (Add deduplication)

HIGH PRIORITY:
├── internal/monitoring/integrity_monitor.go  (Add correlation IDs)
├── internal/logger/logger.go         (Add aggregation)
└── pkg/lifecycle/health_monitor.go   (Add probe handling)

MEDIUM PRIORITY:
├── pkg/security/performance_profiler.go  (Integrate pprof)
└── internal/monitoring/dashboard.go  (Add persistence)

---

Configuration Examples

# Missing environment variables for production
METRICS_ENABLED: "true"
METRICS_PORT: "9090"
HEALTH_CHECK_INTERVAL: "30s"
PROMETHEUS_SCRAPE_INTERVAL: "15s"
LOG_AGGREGATION_ENABLED: "true"
LOG_AGGREGATION_ENDPOINT: "https://logs.datadog.com"
PAGERDUTY_API_KEY: "${PAGERDUTY_API_KEY}"
PAGERDUTY_SERVICE_ID: "${PAGERDUTY_SERVICE_ID}"
AUDIT_LOG_ENCRYPTION_KEY: "${AUDIT_LOG_ENCRYPTION_KEY}"

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Kubernetes Deployment Readiness Checklist

• Liveness probe implemented
• Readiness probe implemented
• Startup probe implemented
• Prometheus metrics at /metrics
• Health checks in separate port (9090)
• Graceful shutdown (SIGTERM handling)
• Resource requests/limits configured
• Pod disruption budgets defined
• Log aggregation configured
• Alert routing configured
• SLOs defined and monitored
• Disaster recovery tested

Current Status: 3/12 (25% K8s ready)

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Files Analyzed

Core Monitoring (550+ lines)

• internal/monitoring/dashboard.go (550 lines) - HTML dashboard
• internal/monitoring/alert_handlers.go (400 lines) - Alert system
• internal/monitoring/health_checker.go (448 lines) - Health checks
• internal/monitoring/integrity_monitor.go (500+ lines) - Data integrity

Performance & Lifecycle (2000+ lines)

• pkg/security/performance_profiler.go (1300 lines) - Comprehensive profiler
• pkg/lifecycle/health_monitor.go (1000+ lines) - Lifecycle management
• pkg/metrics/metrics.go (415 lines) - Basic metrics collection

Conclusion

The MEV bot has solid foundational monitoring but requires significant enhancements for production Kubernetes deployment, particularly around Kubernetes-native probes and Prometheus integration.