Create scenarios.yaml
Browse files- config/scenarios.yaml +150 -0
config/scenarios.yaml
ADDED
|
@@ -0,0 +1,150 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Cache Miss Storm:
|
| 2 |
+
description: "Redis cluster experiencing 80% cache miss rate causing database overload"
|
| 3 |
+
severity: "CRITICAL"
|
| 4 |
+
component: "redis_cache"
|
| 5 |
+
metrics:
|
| 6 |
+
cache_hit_rate: 18.5
|
| 7 |
+
database_load: 92
|
| 8 |
+
response_time_ms: 1850
|
| 9 |
+
affected_users: 45000
|
| 10 |
+
eviction_rate_per_sec: 125
|
| 11 |
+
business_impact:
|
| 12 |
+
revenue_loss_per_hour: 8500
|
| 13 |
+
sla_violation: true
|
| 14 |
+
customer_sat_change: -40
|
| 15 |
+
affected_services:
|
| 16 |
+
- "API Gateway"
|
| 17 |
+
- "User Service"
|
| 18 |
+
- "Payment"
|
| 19 |
+
roi_data:
|
| 20 |
+
hourly_revenue_loss: 8500
|
| 21 |
+
manual_recovery_hours: 1.0
|
| 22 |
+
enterprise_recovery_hours: 0.2
|
| 23 |
+
engineers_required: 4
|
| 24 |
+
engineer_hourly_rate: 150
|
| 25 |
+
estimated_monthly_occurrences: 2
|
| 26 |
+
enterprise_savings_percentage: 0.85
|
| 27 |
+
|
| 28 |
+
Database Connection Pool Exhaustion:
|
| 29 |
+
description: "PostgreSQL connection pool exhausted causing API timeouts"
|
| 30 |
+
severity: "HIGH"
|
| 31 |
+
component: "postgresql_database"
|
| 32 |
+
metrics:
|
| 33 |
+
active_connections: 98
|
| 34 |
+
max_connections: 100
|
| 35 |
+
api_latency_ms: 2450
|
| 36 |
+
error_rate: 15.2
|
| 37 |
+
queue_depth: 1250
|
| 38 |
+
connection_wait_seconds: 45
|
| 39 |
+
business_impact:
|
| 40 |
+
revenue_loss_per_hour: 4200
|
| 41 |
+
affected_services:
|
| 42 |
+
- "API Gateway"
|
| 43 |
+
- "User Service"
|
| 44 |
+
- "Payment Service"
|
| 45 |
+
sla_violation: true
|
| 46 |
+
partner_api_impact: 3
|
| 47 |
+
roi_data:
|
| 48 |
+
hourly_revenue_loss: 4200
|
| 49 |
+
manual_recovery_hours: 0.75
|
| 50 |
+
enterprise_recovery_hours: 0.13
|
| 51 |
+
engineers_required: 2
|
| 52 |
+
engineer_hourly_rate: 150
|
| 53 |
+
estimated_monthly_occurrences: 3
|
| 54 |
+
enterprise_savings_percentage: 0.82
|
| 55 |
+
|
| 56 |
+
Kubernetes Memory Leak:
|
| 57 |
+
description: "Java microservice memory leak causing pod restarts"
|
| 58 |
+
severity: "HIGH"
|
| 59 |
+
component: "java_payment_service"
|
| 60 |
+
metrics:
|
| 61 |
+
memory_usage: 96
|
| 62 |
+
gc_pause_time_ms: 4500
|
| 63 |
+
error_rate: 28.5
|
| 64 |
+
restart_frequency_per_hour: 12
|
| 65 |
+
heap_fragmentation: 42
|
| 66 |
+
business_impact:
|
| 67 |
+
revenue_loss_per_hour: 5500
|
| 68 |
+
session_loss: 8500
|
| 69 |
+
payment_failures_percentage: 3.2
|
| 70 |
+
support_tickets_increase: 300
|
| 71 |
+
roi_data:
|
| 72 |
+
hourly_revenue_loss: 5500
|
| 73 |
+
manual_recovery_hours: 1.5
|
| 74 |
+
enterprise_recovery_hours: 0.25
|
| 75 |
+
engineers_required: 3
|
| 76 |
+
engineer_hourly_rate: 150
|
| 77 |
+
estimated_monthly_occurrences: 1
|
| 78 |
+
enterprise_savings_percentage: 0.79
|
| 79 |
+
|
| 80 |
+
API Rate Limit Storm:
|
| 81 |
+
description: "Third-party API rate limiting causing cascading failures"
|
| 82 |
+
severity: "MEDIUM"
|
| 83 |
+
component: "external_api_gateway"
|
| 84 |
+
metrics:
|
| 85 |
+
rate_limit_hits_percentage: 95
|
| 86 |
+
error_rate: 42.8
|
| 87 |
+
retry_storm: true
|
| 88 |
+
cascade_effect_services: 3
|
| 89 |
+
queue_backlog: 8500
|
| 90 |
+
business_impact:
|
| 91 |
+
revenue_loss_per_hour: 3800
|
| 92 |
+
partner_sla_breach: true
|
| 93 |
+
data_sync_delay_hours: 4
|
| 94 |
+
customer_reports_delay_hours: 6
|
| 95 |
+
roi_data:
|
| 96 |
+
hourly_revenue_loss: 3800
|
| 97 |
+
manual_recovery_hours: 1.25
|
| 98 |
+
enterprise_recovery_hours: 0.17
|
| 99 |
+
engineers_required: 3
|
| 100 |
+
engineer_hourly_rate: 150
|
| 101 |
+
estimated_monthly_occurrences: 4
|
| 102 |
+
enterprise_savings_percentage: 0.85
|
| 103 |
+
|
| 104 |
+
Network Partition:
|
| 105 |
+
description: "Network partition causing split-brain in distributed database"
|
| 106 |
+
severity: "CRITICAL"
|
| 107 |
+
component: "distributed_database"
|
| 108 |
+
metrics:
|
| 109 |
+
partition_detected: true
|
| 110 |
+
write_conflicts: 1250
|
| 111 |
+
data_inconsistency_percentage: 8.5
|
| 112 |
+
replication_lag_seconds: 45
|
| 113 |
+
quorum_lost: true
|
| 114 |
+
business_impact:
|
| 115 |
+
revenue_loss_per_hour: 12000
|
| 116 |
+
data_corruption_risk: true
|
| 117 |
+
recovery_complexity: "HIGH"
|
| 118 |
+
compliance_violation: true
|
| 119 |
+
roi_data:
|
| 120 |
+
hourly_revenue_loss: 12000
|
| 121 |
+
manual_recovery_hours: 2.0
|
| 122 |
+
enterprise_recovery_hours: 0.3
|
| 123 |
+
engineers_required: 5
|
| 124 |
+
engineer_hourly_rate: 150
|
| 125 |
+
estimated_monthly_occurrences: 0.5
|
| 126 |
+
enterprise_savings_percentage: 0.88
|
| 127 |
+
|
| 128 |
+
Storage I/O Saturation:
|
| 129 |
+
description: "Storage system I/O saturation causing application timeouts"
|
| 130 |
+
severity: "HIGH"
|
| 131 |
+
component: "storage_cluster"
|
| 132 |
+
metrics:
|
| 133 |
+
io_utilization: 98
|
| 134 |
+
latency_ms: 450
|
| 135 |
+
throughput_mbps: 1250
|
| 136 |
+
queue_depth: 850
|
| 137 |
+
error_rate: 8.5
|
| 138 |
+
business_impact:
|
| 139 |
+
revenue_loss_per_hour: 6800
|
| 140 |
+
data_processing_delay_hours: 3
|
| 141 |
+
analytics_backlog: true
|
| 142 |
+
reporting_failure: true
|
| 143 |
+
roi_data:
|
| 144 |
+
hourly_revenue_loss: 6800
|
| 145 |
+
manual_recovery_hours: 1.75
|
| 146 |
+
enterprise_recovery_hours: 0.22
|
| 147 |
+
engineers_required: 3
|
| 148 |
+
engineer_hourly_rate: 150
|
| 149 |
+
estimated_monthly_occurrences: 1.5
|
| 150 |
+
enterprise_savings_percentage: 0.83
|