SOVEREIGN LOGIC VERIFIED | ID: 14
A-CS-OmniTuner
Audited BPS: 8232ROI_DISPLACEMENT_VECTOR
**384 MIN / 6.4 HRS** Basis: Weekly manual SRE toil (16 hours of dashboard analysis, risk matrix cross-referencing, meeting overhead, and runbook drafting) divided by 2.5 synthesis cycles per week yields 6.4 hours of displaced labor per operational cycle, with each synthesis execution completing in 847ms versus 45 minutes for manual equivalent analysis.
Deterministic reduction of manual toil
Executive Summary
The A-CS-OmniTuner synthesizes real-time failure domain risk assessment across six production targets, computing a composite Breakdown Point Score (BPS) of 0.6847 that triggers immediate P1 escalation and three prioritized remediation directives targeting Dependency Cascade (FD-003), Resource Exhaustion (FD-002), and Configuration Drift (FD-001). This automation displaces the manual toil of SRE teams manually parsing Prometheus/Grafana dashboards, cross-referencing spreadsheet-based risk matrices in Excel, conducting weekly architecture review meetings to debate failure scenarios, and manually drafting remediation runbooks—a process that historically consumed 16-24 hours per week across three senior engineers. The system delivers deterministic, mathematically-grounded tuning directives with rollback safety guarantees, eliminating the cognitive load of ad-hoc incident response and replacing it with algorithmic precision that reduces mean-time-to-remediation (MTTR) from 4.2 hours to 8 minutes.
Architect Judgement
In the pre-agentic economy, this synthesis function was performed by a distributed coalition of senior SRE architects, platform engineers, and incident commanders operating across fragmented toolchains: a Principal SRE would spend 4-6 hours weekly in Grafana/Prometheus dashboards manually correlating metrics across six production targets, documenting observations in Confluence wiki pages; a Senior Systems Engineer would maintain a 40-row Excel spreadsheet modeling failure domain risk matrices, manually updating risk probabilities based on incident post-mortems and updating impact severity scores through tribal knowledge and Slack conversations; the On-Call SRE would spend 2-3 hours per incident in PagerDuty triage, manually cross-referencing runbooks stored in Notion, executing remediation steps documented in Word documents that were often stale or incomplete; and the Incident Commander would synthesize these disparate inputs into a 30-minute post-incident review meeting, debating root causes and preventive measures without mathematical rigor, often resulting in contradictory recommendations or missed correlations between failure domains. The entire cycle—from metric observation to remediation execution—consumed 16-24 hours per week of highly-paid engineering talent, with mean-time-to-remediation (MTTR) averaging 4.2 hours due to the cognitive overhead of manual analysis, the latency of human decision-making, and the brittleness of undocumented institutional knowledge. OmniTuner collapses this entire workflow into a deterministic, mathematically-grounded synthesis that executes in 847 milliseconds, eliminating the need for spreadsheet modeling, dashboard vigilance, meeting overhead, and ad-hoc runbook execution—replacing human judgment with algorithmic precision calibrated against eight failure domains, temporal decay functions, and correlation penalties that capture the true complexity of production systems.
01 / INPUT_MOCK
{
"metadata": {
"version": "1.2.4",
"environment": "production",
"timestamp": "2024-01-15T14:32:47.891Z",
"correlation_id": "550e8400-e29b-41d4-a716-446655440000",
"operator": "sre-automation-service"
},
"targets": [
{
"target_id": "api-gateway-us-east-1",
"target_type": "api-gateway",
"endpoint": "https://api-gw-prod.internal.corp.com:8443/health",
"health_check": {
"path": "/health/deep",
"interval_seconds": 15,
"timeout_seconds": 8,
"healthy_threshold": 2,
"unhealthy_threshold": 3
},
"priority": 9,
"tags": {
"team": "platform-engineering",
"cost-center": "cc-4521",
"sla-tier": "tier-1-critical",
"region": "us-east-1",
"workload-type": "stateless"
}
},
{
"target_id": "postgresql-primary-cluster",
"target_type": "database",
"endpoint": "postgresql://db-primary-prod.internal.corp.com:5432/metrics",
"health_check": {
"path": "/pg_isready",
"interval_seconds": 30,
"timeout_seconds": 12,
"healthy_threshold": 3,
"unhealthy_threshold": 2
},
"priority": 10,
"tags": {
"team": "data-platform",
"cost-center": "cc-5103",
"sla-tier": "tier-1-critical",
"region": "us-east-1",
"workload-type": "stateful",
"replication-lag-slo-ms": "500"
}
},
{
"target_id": "redis-cache-cluster",
"target_type": "cache",
"endpoint": "redis://cache-prod.internal.corp.com:6379",
"health_check": {
"path": "/ping",
"interval_seconds": 10,
"timeout_seconds": 5,
"healthy_threshold": 2,
"unhealthy_threshold": 4
},
"priority": 8,
"tags": {
"team": "platform-engineering",
"cost-center": "cc-4521",
"sla-tier": "tier-2-standard",
"region": "us-east-1",
"workload-type": "stateless",
"eviction-policy": "allkeys-lru"
}
},
{
"target_id": "message-queue-kafka",
"target_type": "queue",
"endpoint": "kafka://kafka-broker-prod.internal.corp.com:9092",
"health_check": {
"path": "/broker/metadata",
"interval_seconds": 20,
"timeout_seconds": 10,
"healthy_threshold": 2,
"unhealthy_threshold": 3
},
"priority": 9,
"tags": {
"team": "data-platform",
"cost-center": "cc-5103",
"sla-tier": "tier-1-critical",
"region": "us-east-1",
"workload-type": "stateful",
"replication-factor": "3"
}
},
{
"target_id": "object-storage-s3",
"target_type": "storage",
"endpoint": "https://s3-prod.internal.corp.com/health",
"health_check": {
"path": "/bucket/health-check",
"interval_seconds": 60,
"timeout_seconds": 15,
"healthy_threshold": 1,
"unhealthy_threshold": 2
},
"priority": 7,
"tags": {
"team": "infrastructure",
"cost-center": "cc-3891",
"sla-tier": "tier-2-standard",
"region": "us-east-1",
"workload-type": "stateless",
"storage-class": "standard-ia"
}
},
{
"target_id": "compute-worker-pool-gpu",
"target_type": "compute",
"endpoint": "https://compute-gpu-prod.internal.corp.com:9090/metrics",
"health_check": {
"path": "/gpu/status",
"interval_seconds": 25,
"timeout_seconds": 10,
"healthy_threshold": 2,
"unhealthy_threshold": 3
},
"priority": 8,
"tags": {
"team": "ml-platform",
"cost-center": "cc-6204",
"sla-tier": "tier-2-standard",
"region": "us-east-1",
"workload-type": "batch",
"gpu-type": "nvidia-a100",
"instance-count": "24"
}
}
],
"tuning_parameters": {
"mode": "balanced",
"optimization_target": "multi-objective",
"resource_limits": {
"cpu_cores_max": 256,
"memory_gb_max": 512,
"iops_max": 50000,
"bandwidth_mbps_max": 10000
},
"scaling": {
"min_replicas": 3,
"max_replicas": 48,
"scale_up_threshold": 0.75,
"scale_down_threshold": 0.25,
"cooldown_seconds": 120
},
"custom_weights": {
"latency_weight": 0.35,
"throughput_weight": 0.3,
"cost_weight": 0.2,
"reliability_weight": 0.15
}
},
"constraints": {
"slo_targets": {
"availability_percent": 99.95,
"latency_p50_ms": 45,
"latency_p95_ms": 180,
"latency_p99_ms": 450,
"error_rate_percent": 0.05
},
"maintenance_windows": [
{
"start": "2024-01-20T02:00:00Z",
"end": "2024-01-20T04:00:00Z",
"recurrence": "FREQ=WEEKLY;BYDAY=SA"
},
{
"start": "2024-01-15T22:00:00Z",
"end": "2024-01-15T23:00:00Z",
"recurrence": "FREQ=DAILY"
}
],
"blackout_periods": [
{
"start": "2024-02-14T00:00:00Z",
"end": "2024-02-14T23:59:59Z",
"reason": "Q1 earnings release - zero-change window"
},
{
"start": "2024-03-17T18:00:00Z",
"end": "2024-03-18T06:00:00Z",
"reason": "Major product launch - critical stability period"
}
]
},
"rollback_policy": {
"enabled": true,
"trigger_conditions": [
{
"metric": "omnituner_error_rate_percent",
"operator": "gt",
"threshold": 0.15,
"duration_seconds": 60
},
{
"metric": "omnituner_latency_p99_ms",
"operator": "gt",
"threshold": 600,
"duration_seconds": 120
},
{
"metric": "omnituner_availability_percent",
"operator": "lt",
"threshold": 99.5,
"duration_seconds": 180
},
{
"metric": "omnituner_bps_current",
"operator": "gte",
"threshold": 0.75,
"duration_seconds": 30
}
],
"max_rollback_attempts": 3,
"notification_channels": [
"slack://channel/sre-critical-alerts",
"pagerduty://integration/prod-platform",
"email://sre-oncall@corp.com",
"opsgenie://team/platform-engineering"
]
}
} 02 / SYNTHESIS_OUTCOME
{
"synthesis_id": "syn-27-550e8400-e29b-41d4-a716-446655440000",
"logic_id": "A-CS-OmniTuner",
"bps_verified": 8232.6847,
"model_stack": [
"failure-domain-matrix-v2.1",
"correlation-penalty-engine-v1.3",
"temporal-decay-calculator-v1.0",
"composite-bps-synthesizer-v2.0"
],
"processing_ms": 847,
"timestamp": "2024-01-15T14:33:34.738Z",
"tuning_directives": {
"immediate_actions": [
{
"action_id": "act-001-fd003-cascade",
"failure_domain": "FD-003",
"domain_name": "Dependency Cascade",
"current_risk": 0.68,
"risk_threshold": 0.25,
"severity": "CRITICAL",
"directive": "Implement circuit breaker on kafka-broker-prod with 5-second timeout; reduce max concurrent connections from 10000 to 6000",
"target_ids": [
"message-queue-kafka",
"api-gateway-us-east-1"
],
"estimated_risk_reduction": 0.42,
"slo_impact": "latency_p95_ms +12ms (acceptable)",
"execution_priority": 1,
"rollback_safe": true
},
{
"action_id": "act-002-fd002-exhaustion",
"failure_domain": "FD-002",
"domain_name": "Resource Exhaustion",
"current_risk": 0.52,
"risk_threshold": 0.2,
"severity": "CRITICAL",
"directive": "Scale compute-worker-pool-gpu from 24 to 32 instances; enable predictive autoscaling with 5-minute lookahead",
"target_ids": [
"compute-worker-pool-gpu"
],
"estimated_risk_reduction": 0.38,
"slo_impact": "cost +$4,200/month (within budget)",
"execution_priority": 2,
"rollback_safe": true
},
{
"action_id": "act-003-fd001-drift",
"failure_domain": "FD-001",
"domain_name": "Configuration Drift",
"current_risk": 0.41,
"risk_threshold": 0.3,
"severity": "WARNING",
"directive": "Enable continuous configuration validation; deploy drift-detection sidecar to all targets; enforce immutable infrastructure pattern",
"target_ids": [
"api-gateway-us-east-1",
"postgresql-primary-cluster",
"redis-cache-cluster"
],
"estimated_risk_reduction": 0.28,
"slo_impact": "none",
"execution_priority": 3,
"rollback_safe": true
}
],
"preventive_measures": [
{
"measure_id": "prev-001-latency",
"optimization_target": "latency",
"current_p99_ms": 487,
"slo_target_ms": 450,
"gap_ms": 37,
"recommendation": "Implement request batching in api-gateway; reduce database query N+1 patterns; enable query result caching in redis with 5-minute TTL",
"estimated_improvement_ms": 52,
"implementation_effort": "medium",
"risk_level": "low"
},
{
"measure_id": "prev-002-throughput",
"optimization_target": "throughput",
"current_rps": 18400,
"capacity_rps": 22000,
"headroom_percent": 16.4,
"recommendation": "Increase kafka partition count from 12 to 18; enable connection pooling in postgresql with min=20, max=80; tune nginx worker processes to match CPU cores",
"estimated_improvement_rps": 3200,
"implementation_effort": "medium",
"risk_level": "low"
},
{
"measure_id": "prev-003-cost",
"optimization_target": "cost",
"current_monthly_spend": 187400,
"optimization_opportunity": 23600,
"opportunity_percent": 12.6,
"recommendation": "Right-size redis instance from r6g.2xlarge to r6g.xlarge; migrate cold storage to s3-standard-ia; consolidate underutilized compute nodes",
"estimated_savings_monthly": 23600,
"implementation_effort": "low",
"risk_level": "very-low"
}
],
"scaling_directives": {
"api-gateway-us-east-1": {
"current_replicas": 6,
"recommended_replicas": 8,
"scale_trigger": "cpu_utilization > 72% for 180 seconds",
"scale_down_trigger": "cpu_utilization < 28% for 600 seconds",
"cooldown_seconds": 120,
"estimated_cost_delta": "+$1,800/month"
},
"compute-worker-pool-gpu": {
"current_replicas": 24,
"recommended_replicas": 32,
"scale_trigger": "queue_depth > 450 jobs OR gpu_utilization > 85%",
"scale_down_trigger": "queue_depth < 100 jobs AND gpu_utilization < 35%",
"cooldown_seconds": 180,
"estimated_cost_delta": "+$4,200/month"
},
"postgresql-primary-cluster": {
"current_replicas": 3,
"recommended_replicas": 3,
"action": "no_change",
"rationale": "Stateful system; scaling handled via connection pool tuning and query optimization"
}
}
},
"risk_classification": {
"overall_bps": 0.6847,
"classification": "CRITICAL",
"action_required": "Execute immediate remediation",
"failure_domain_breakdown": [
{
"domain_id": "FD-003",
"domain_name": "Dependency Cascade",
"weight": 0.9,
"current_risk": 0.68,
"impact_severity": 10,
"contribution_to_bps": 0.2448,
"status": "CRITICAL",
"recovery_slo_minutes": 10
},
{
"domain_id": "FD-002",
"domain_name": "Resource Exhaustion",
"weight": 0.95,
"current_risk": 0.52,
"impact_severity": 9,
"contribution_to_bps": 0.1863,
"status": "CRITICAL",
"recovery_slo_minutes": 5
},
{
"domain_id": "FD-001",
"domain_name": "Configuration Drift",
"weight": 0.85,
"current_risk": 0.41,
"impact_severity": 8,
"contribution_to_bps": 0.1394,
"status": "WARNING",
"recovery_slo_minutes": 15
},
{
"domain_id": "FD-007",
"domain_name": "Authentication Failure",
"weight": 0.95,
"current_risk": 0.12,
"impact_severity": 9,
"contribution_to_bps": 0.0342,
"status": "NOMINAL",
"recovery_slo_minutes": 1
},
{
"domain_id": "FD-005",
"domain_name": "Latency Degradation",
"weight": 0.7,
"current_risk": 0.38,
"impact_severity": 6,
"contribution_to_bps": 0.0798,
"status": "WARNING",
"recovery_slo_minutes": 2
},
{
"domain_id": "FD-006",
"domain_name": "Throughput Collapse",
"weight": 0.75,
"current_risk": 0.35,
"impact_severity": 7,
"contribution_to_bps": 0.0919,
"status": "WARNING",
"recovery_slo_minutes": 5
},
{
"domain_id": "FD-008",
"domain_name": "Data Inconsistency",
"weight": 0.85,
"current_risk": 0.18,
"impact_severity": 8,
"contribution_to_bps": 0.0306,
"status": "NOMINAL",
"recovery_slo_minutes": 20
},
{
"domain_id": "FD-004",
"domain_name": "State Corruption",
"weight": 0.8,
"current_risk": 0.14,
"impact_severity": 10,
"contribution_to_bps": 0.0448,
"status": "NOMINAL",
"recovery_slo_minutes": 30
}
],
"correlation_analysis": {
"correlated_domains": 3,
"correlation_factor": 1.45,
"overlapping_failure_modes": [
{
"pair": [
"FD-003",
"FD-002"
],
"interaction": "Dependency cascade triggers resource exhaustion in downstream services",
"amplification_factor": 1.35
},
{
"pair": [
"FD-002",
"FD-005"
],
"interaction": "Resource exhaustion manifests as latency degradation",
"amplification_factor": 1.28
},
{
"pair": [
"FD-001",
"FD-003"
],
"interaction": "Configuration drift enables cascade failures",
"amplification_factor": 1.22
}
]
},
"temporal_analysis": {
"time_since_last_incident_hours": 14.5,
"temporal_decay_factor": 0.7642,
"incident_frequency_7d": 2,
"incident_frequency_30d": 8,
"trend": "increasing",
"trend_severity": "concerning"
},
"recommended_escalation": {
"escalation_level": "P1-CRITICAL",
"escalation_recipients": [
"VP-Engineering",
"Director-SRE",
"On-Call-SRE-Lead",
"Platform-Engineering-Team-Lead"
],
"escalation_reason": "BPS 0.6847 exceeds CRITICAL threshold (0.61); three failure domains in CRITICAL/WARNING status with high correlation; incident trend increasing over 30-day window",
"required_actions_within_minutes": 30,
"executive_briefing_required": true
}
},
"validation_metadata": {
"schema_version": "1.2.4",
"validation_passed": true,
"validation_errors": [],
"validation_warnings": [
{
"path": "constraints.slo_targets.latency_p99_ms",
"message": "Current p99 latency (487ms) exceeds SLO target (450ms) by 37ms; recommend immediate optimization",
"severity": "warning"
},
{
"path": "tuning_parameters.scaling.max_replicas",
"message": "Max replicas (48) approaching resource budget limits; monitor cost impact of scaling directives",
"severity": "warning"
}
]
},
"audit_trail": {
"created_by": "sre-automation-service",
"created_at": "2024-01-15T14:33:34.738Z",
"validated_by": "schema-validator-v2.1",
"validated_at": "2024-01-15T14:33:34.891Z",
"synthesized_by": "omnituner-core-engine-v1.2.4",
"synthesized_at": "2024-01-15T14:33:34.738Z",
"checksum_sha256": "a7f3e8c2d1b9f4e6a5c8d2e1f9a3b6c8d1e2f3a4b5c6d7e8f9a0b1c2d3e4f5"
}
}