🏥 Monitoring & Health Dashboard

Comprehensive system health, AI metrics, and infrastructure monitoring

All Systems Healthy
🚀 Recent Infrastructure Achievements
✨
Memory v5
Deterministic context loading with proven compliance. Reduced token usage by 97% through efficient memory management.
97% ↓ tokens
📄 ADR-019: Memory v5 Architecture 📄 DETERMINISTIC_PROTOCOL_ENFORCEMENT.md
🐳
Docker Isolation
Multi-project container strategy with agent load sequence validation. Complete isolation between projects.
100% isolated
📄 CONTAINER_ISOLATION_STRATEGY.md 📄 AGENT_LOAD_SEQUENCE.md
🔒
SOC2 Ready
Compliance status tracking with comprehensive audit logging. Currently in Phase 2 implementation.
Phase 2 Active
📄 SOC2_COMPLIANCE_STATUS.md
📊
ADR-008 Monitoring
Comprehensive monitoring system tracking 7 metric categories across all agents and projects.
7 categories
📄 ADR-008: Monitoring System
📋 ADR-008: System Health Metrics
Real-Time
1. Agent Presence & Health
100%
9/9 agents responding within 60s heartbeat
2. Memory System Health
Healthy
HOT: 3.2KB (64% budget) • WARM: 45ms query
3. Queue Activity
3
Inbox: 3 • WIP: 2 • Outbox: 12 (today)
4. Performance
Optimal
Startup: 1.2s • v2.0 avg: 2.4s (-50%)
5. Error Tracking
0
No crashes (24h) • 2 errors (rate: 0.1/hour)
6. Storage Health
42%
8.4GB / 20GB used • Backup: 18h ago ✓
7. Cost Optimization
Success
Tier 2: 97% auto-exit • Token: -97% vs baseline
Overall System Status
Healthy
17/21 validation checks passed
🤖 AI-Specific Health Metrics
Intelligence Layer
Model Optimization Score
94%
Percentage of requests using the appropriate model tier (Haiku vs Sonnet vs Opus) for optimal cost-performance balance.
67% Haiku
28% Sonnet
5% Opus
Context Window Efficiency
76%
Average context window utilization. Measures how effectively we use available context without triggering compaction or overflow.
12 Compactions/day
0 Overflow Incidents
97% v5 Improvement
Agent Collaboration Index
92%
Cross-agent communication effectiveness. Tracks handoff success rate and collaboration quality between agents.
97% Handoff Success
38 Messages/day
8.2 Avg Collaborators
Learning Evolution Rate
8.4
New patterns detected per week. Measures memory improvements and behavioral adaptations from agent learning.
24 Memory Updates
12 Adaptations
6 New Patterns
✨ Memory v5 Health Grid
97% Token Reduction
🔥
HOT Tier
Healthy
64%
Always-loaded context (BRAHMAN_STATUS.txt, ACTIVE_TOPICS.json)
Current Size
3.2KB
Budget
5KB
Files
2
Hit Rate
100%
⚡ Instant Access
🌡️
WARM Tier
Healthy
45ms
On-demand search queries (memory_search.sh, ADRs, agent memories)
Avg Latency
45ms
Threshold
100ms
Queries/min
12
Cache Hit
87%
⚡ 55% Under Threshold
⚡
Load Performance
Optimal
1.2s
Agent wake time including deterministic memory loading
Current
1.2s
v4 Baseline
2.4s
Improvement
50%
Failures
0
⚡ 50% Faster vs v4
📋
Session Metadata
Complete
100%
All sessions have complete metadata (timestamp, role, project)
Sessions
1,247
Missing Data
0
Agents
9
Projects
12
✓ No Pipeline Gaps
💾
SQLite DB Size
Monitoring
6.8MB
conversations.db size (Alert threshold: 10MB for optimal performance)
Current
6.8MB
Threshold
10MB
Growth/day
120KB
Days to Alert
27
✓ Query Performance: Optimal
💰
Token Efficiency
Excellent
97%
Token reduction vs v4 baseline (deterministic loading + tiered memory)
v4 Baseline
42K
v5 Current
1.2K
Saved (30d)
1.8M
$ Savings
$2.4K
🎉 97% Reduction Achieved
🧠 Memory System (v5)
HOT Tier Size
3.2KB
BRAHMAN_STATUS.txt + ACTIVE_TOPICS.json (Budget: 5KB)
WARM Tier Query Latency
45ms
memory_search.sh response time (Threshold: 100ms)
Session Metadata Completeness
100%
All sessions have full metadata (no pipeline gaps)
SQLite Database Size
6.8MB
Query performance still optimal (Alert: >10MB)
📥 Queue Activity & Latency
Task Pickup Latency
2.4m
Average time from inbox → WIP
Task Completion Latency
1.8h
Average time from inbox → outbox
Stuck Tasks
1
Tasks in WIP >24 hours (threshold for alert)
Current Queue Flow
Inbox
3
→
WIP
2
→
Outbox
12
⚡ Agent Performance (v1 vs v2)
Avg Startup Time (v2.0)
1.2s
v1.x baseline: 2.4s (50% improvement)
Token Consumption (v2.0)
847K
v1.x baseline: 28.2M tokens (97% reduction)
Query Latency (v2.0)
45ms
v1.x baseline: 180ms (SQLite vs jq)
💰 Cost Optimization
Tier 2 Auto-Exit Success
97%
Agents exited within 30min idle threshold
Tier 3 Auto-Exit Success
100%
Agents exited within 15min idle threshold
Monthly Cost Savings
$2,847
Memory v5 + auto-exit optimization impact
📊 Data Sources
System Health: studio/monitoring/metrics.db
Agent Presence: presence.db
Memory Metrics: memory/*.md, memory.db
Queue Data: studio/queues/*
Model Usage: conversation logs
Git Data: git log
Real-time updates via:
PostgreSQL LISTEN/NOTIFY + tRPC subscriptions