{
  "metadata": {
    "service": {
      "name": "payment-service",
      "type": "api",
      "criticality": "critical",
      "user_facing": true,
      "description": "Handles payment processing and transaction management",
      "team": "payments",
      "environment": "production",
      "dependencies": [
        {
          "name": "user-service",
          "type": "api",
          "criticality": "high"
        },
        {
          "name": "payment-gateway",
          "type": "external",
          "criticality": "critical"
        },
        {
          "name": "fraud-detection",
          "type": "ml",
          "criticality": "high"
        }
      ],
      "endpoints": [
        {
          "path": "/api/v1/payments",
          "method": "POST",
          "sla_latency_ms": 500,
          "expected_tps": 100
        },
        {
          "path": "/api/v1/payments/{id}",
          "method": "GET",
          "sla_latency_ms": 200,
          "expected_tps": 500
        },
        {
          "path": "/api/v1/payments/{id}/refund",
          "method": "POST",
          "sla_latency_ms": 1000,
          "expected_tps": 10
        }
      ],
      "business_metrics": {
        "revenue_per_hour": {
          "metric": "sum(payment_amount * rate(payments_successful_total[1h]))",
          "target": 50000,
          "unit": "USD"
        },
        "conversion_rate": {
          "metric": "sum(rate(payments_successful_total[5m])) / sum(rate(payment_attempts_total[5m]))",
          "target": 0.95,
          "unit": "percentage"
        }
      },
      "infrastructure": {
        "container_orchestrator": "kubernetes",
        "replicas": 6,
        "cpu_limit": "2000m",
        "memory_limit": "4Gi",
        "database": {
          "type": "postgresql",
          "connection_pool_size": 20
        },
        "cache": {
          "type": "redis",
          "cluster_size": 3
        }
      },
      "compliance_requirements": [
        "PCI-DSS",
        "SOX",
        "GDPR"
      ],
      "tags": [
        "payment",
        "transaction",
        "critical-path",
        "revenue-generating"
      ]
    },
    "generated_at": "2026-02-16T14:01:57.572080Z",
    "framework_version": "1.0"
  },
  "slis": [
    {
      "name": "Availability",
      "description": "Percentage of successful requests",
      "type": "ratio",
      "good_events": "sum(rate(http_requests_total{service=\"payment-service\",code!~\"5..\"}))",
      "total_events": "sum(rate(http_requests_total{service=\"payment-service\"}))",
      "unit": "percentage"
    },
    {
      "name": "Request Latency P95",
      "description": "95th percentile of request latency",
      "type": "threshold",
      "query": "histogram_quantile(0.95, rate(http_request_duration_seconds_bucket{service=\"payment-service\"}[5m]))",
      "unit": "seconds"
    },
    {
      "name": "Error Rate",
      "description": "Rate of 5xx errors",
      "type": "ratio",
      "good_events": "sum(rate(http_requests_total{service=\"payment-service\",code!~\"5..\"}))",
      "total_events": "sum(rate(http_requests_total{service=\"payment-service\"}))",
      "unit": "percentage"
    },
    {
      "name": "Request Throughput",
      "description": "Requests per second",
      "type": "gauge",
      "query": "sum(rate(http_requests_total{service=\"payment-service\"}[5m]))",
      "unit": "requests/sec"
    },
    {
      "name": "User Journey Success Rate",
      "description": "Percentage of successful complete user journeys",
      "type": "ratio",
      "good_events": "sum(rate(user_journey_total{service=\"payment-service\",status=\"success\"}[5m]))",
      "total_events": "sum(rate(user_journey_total{service=\"payment-service\"}[5m]))",
      "unit": "percentage"
    },
    {
      "name": "Feature Availability",
      "description": "Percentage of time key features are available",
      "type": "ratio",
      "good_events": "sum(rate(feature_checks_total{service=\"payment-service\",status=\"available\"}[5m]))",
      "total_events": "sum(rate(feature_checks_total{service=\"payment-service\"}[5m]))",
      "unit": "percentage"
    }
  ],
  "slos": [
    {
      "name": "Availability SLO",
      "description": "Service level objective for percentage of successful requests",
      "sli_name": "Availability",
      "target_value": 0.9999,
      "target_display": "99.99%",
      "operator": ">=",
      "time_windows": [
        "1h",
        "1d",
        "7d",
        "30d"
      ],
      "measurement_window": "30d",
      "service": "payment-service",
      "criticality": "critical"
    },
    {
      "name": "Request Latency P95 SLO",
      "description": "Service level objective for 95th percentile of request latency",
      "sli_name": "Request Latency P95",
      "target_value": 100,
      "target_display": "0.1s",
      "operator": "<=",
      "time_windows": [
        "1h",
        "1d",
        "7d",
        "30d"
      ],
      "measurement_window": "30d",
      "service": "payment-service",
      "criticality": "critical"
    },
    {
      "name": "Error Rate SLO",
      "description": "Service level objective for rate of 5xx errors",
      "sli_name": "Error Rate",
      "target_value": 0.001,
      "target_display": "0.1%",
      "operator": "<=",
      "time_windows": [
        "1h",
        "1d",
        "7d",
        "30d"
      ],
      "measurement_window": "30d",
      "service": "payment-service",
      "criticality": "critical"
    },
    {
      "name": "User Journey Success Rate SLO",
      "description": "Service level objective for percentage of successful complete user journeys",
      "sli_name": "User Journey Success Rate",
      "target_value": 0.9999,
      "target_display": "99.99%",
      "operator": ">=",
      "time_windows": [
        "1h",
        "1d",
        "7d",
        "30d"
      ],
      "measurement_window": "30d",
      "service": "payment-service",
      "criticality": "critical"
    },
    {
      "name": "Feature Availability SLO",
      "description": "Service level objective for percentage of time key features are available",
      "sli_name": "Feature Availability",
      "target_value": 0.9999,
      "target_display": "99.99%",
      "operator": ">=",
      "time_windows": [
        "1h",
        "1d",
        "7d",
        "30d"
      ],
      "measurement_window": "30d",
      "service": "payment-service",
      "criticality": "critical"
    }
  ],
  "error_budgets": [
    {
      "slo_name": "Availability SLO",
      "error_budget_rate": 9.999999999998899e-05,
      "error_budget_percentage": "0.010%",
      "budgets_by_window": {
        "1h": "0.4 seconds",
        "1d": "8.6 seconds",
        "7d": "1.0 minutes",
        "30d": "4.3 minutes"
      },
      "burn_rate_alerts": [
        {
          "name": "Availability Burn Rate 2% Alert",
          "description": "Alert when Availability is consuming error budget at 14.4x rate",
          "severity": "critical",
          "short_window": "5m",
          "long_window": "1h",
          "burn_rate_threshold": 14.4,
          "budget_consumed": "2%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 14.4) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 14.4)",
          "annotations": {
            "summary": "High burn rate detected for Availability",
            "description": "Error budget consumption rate is 14.4x normal, will exhaust 2% of monthly budget"
          }
        },
        {
          "name": "Availability Burn Rate 5% Alert",
          "description": "Alert when Availability is consuming error budget at 6x rate",
          "severity": "warning",
          "short_window": "30m",
          "long_window": "6h",
          "burn_rate_threshold": 6,
          "budget_consumed": "5%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 6) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 6)",
          "annotations": {
            "summary": "High burn rate detected for Availability",
            "description": "Error budget consumption rate is 6x normal, will exhaust 5% of monthly budget"
          }
        },
        {
          "name": "Availability Burn Rate 10% Alert",
          "description": "Alert when Availability is consuming error budget at 3x rate",
          "severity": "info",
          "short_window": "2h",
          "long_window": "1d",
          "burn_rate_threshold": 3,
          "budget_consumed": "10%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 3) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 3)",
          "annotations": {
            "summary": "High burn rate detected for Availability",
            "description": "Error budget consumption rate is 3x normal, will exhaust 10% of monthly budget"
          }
        },
        {
          "name": "Availability Burn Rate 10% Alert",
          "description": "Alert when Availability is consuming error budget at 1x rate",
          "severity": "info",
          "short_window": "6h",
          "long_window": "3d",
          "burn_rate_threshold": 1,
          "budget_consumed": "10%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 1) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 1)",
          "annotations": {
            "summary": "High burn rate detected for Availability",
            "description": "Error budget consumption rate is 1x normal, will exhaust 10% of monthly budget"
          }
        }
      ]
    },
    {
      "slo_name": "User Journey Success Rate SLO",
      "error_budget_rate": 9.999999999998899e-05,
      "error_budget_percentage": "0.010%",
      "budgets_by_window": {
        "1h": "0.4 seconds",
        "1d": "8.6 seconds",
        "7d": "1.0 minutes",
        "30d": "4.3 minutes"
      },
      "burn_rate_alerts": [
        {
          "name": "User Journey Success Rate Burn Rate 2% Alert",
          "description": "Alert when User Journey Success Rate is consuming error budget at 14.4x rate",
          "severity": "critical",
          "short_window": "5m",
          "long_window": "1h",
          "burn_rate_threshold": 14.4,
          "budget_consumed": "2%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 14.4) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 14.4)",
          "annotations": {
            "summary": "High burn rate detected for User Journey Success Rate",
            "description": "Error budget consumption rate is 14.4x normal, will exhaust 2% of monthly budget"
          }
        },
        {
          "name": "User Journey Success Rate Burn Rate 5% Alert",
          "description": "Alert when User Journey Success Rate is consuming error budget at 6x rate",
          "severity": "warning",
          "short_window": "30m",
          "long_window": "6h",
          "burn_rate_threshold": 6,
          "budget_consumed": "5%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 6) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 6)",
          "annotations": {
            "summary": "High burn rate detected for User Journey Success Rate",
            "description": "Error budget consumption rate is 6x normal, will exhaust 5% of monthly budget"
          }
        },
        {
          "name": "User Journey Success Rate Burn Rate 10% Alert",
          "description": "Alert when User Journey Success Rate is consuming error budget at 3x rate",
          "severity": "info",
          "short_window": "2h",
          "long_window": "1d",
          "burn_rate_threshold": 3,
          "budget_consumed": "10%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 3) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 3)",
          "annotations": {
            "summary": "High burn rate detected for User Journey Success Rate",
            "description": "Error budget consumption rate is 3x normal, will exhaust 10% of monthly budget"
          }
        },
        {
          "name": "User Journey Success Rate Burn Rate 10% Alert",
          "description": "Alert when User Journey Success Rate is consuming error budget at 1x rate",
          "severity": "info",
          "short_window": "6h",
          "long_window": "3d",
          "burn_rate_threshold": 1,
          "budget_consumed": "10%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 1) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 1)",
          "annotations": {
            "summary": "High burn rate detected for User Journey Success Rate",
            "description": "Error budget consumption rate is 1x normal, will exhaust 10% of monthly budget"
          }
        }
      ]
    },
    {
      "slo_name": "Feature Availability SLO",
      "error_budget_rate": 9.999999999998899e-05,
      "error_budget_percentage": "0.010%",
      "budgets_by_window": {
        "1h": "0.4 seconds",
        "1d": "8.6 seconds",
        "7d": "1.0 minutes",
        "30d": "4.3 minutes"
      },
      "burn_rate_alerts": [
        {
          "name": "Feature Availability Burn Rate 2% Alert",
          "description": "Alert when Feature Availability is consuming error budget at 14.4x rate",
          "severity": "critical",
          "short_window": "5m",
          "long_window": "1h",
          "burn_rate_threshold": 14.4,
          "budget_consumed": "2%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 14.4) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 14.4)",
          "annotations": {
            "summary": "High burn rate detected for Feature Availability",
            "description": "Error budget consumption rate is 14.4x normal, will exhaust 2% of monthly budget"
          }
        },
        {
          "name": "Feature Availability Burn Rate 5% Alert",
          "description": "Alert when Feature Availability is consuming error budget at 6x rate",
          "severity": "warning",
          "short_window": "30m",
          "long_window": "6h",
          "burn_rate_threshold": 6,
          "budget_consumed": "5%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 6) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 6)",
          "annotations": {
            "summary": "High burn rate detected for Feature Availability",
            "description": "Error budget consumption rate is 6x normal, will exhaust 5% of monthly budget"
          }
        },
        {
          "name": "Feature Availability Burn Rate 10% Alert",
          "description": "Alert when Feature Availability is consuming error budget at 3x rate",
          "severity": "info",
          "short_window": "2h",
          "long_window": "1d",
          "burn_rate_threshold": 3,
          "budget_consumed": "10%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 3) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 3)",
          "annotations": {
            "summary": "High burn rate detected for Feature Availability",
            "description": "Error budget consumption rate is 3x normal, will exhaust 10% of monthly budget"
          }
        },
        {
          "name": "Feature Availability Burn Rate 10% Alert",
          "description": "Alert when Feature Availability is consuming error budget at 1x rate",
          "severity": "info",
          "short_window": "6h",
          "long_window": "3d",
          "burn_rate_threshold": 1,
          "budget_consumed": "10%",
          "condition": "((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_short > 1) and ((1 - (sum(rate(http_requests_total{service='payment-service',code!~'5..'})) / sum(rate(http_requests_total{service='payment-service'}))))_long > 1)",
          "annotations": {
            "summary": "High burn rate detected for Feature Availability",
            "description": "Error budget consumption rate is 1x normal, will exhaust 10% of monthly budget"
          }
        }
      ]
    }
  ],
  "sla_recommendations": {
    "applicable": true,
    "service": "payment-service",
    "commitments": [
      {
        "metric": "Availability",
        "target": 0.9989,
        "target_display": "99.89%",
        "measurement_window": "monthly",
        "measurement_method": "Uptime monitoring with 1-minute granularity"
      },
      {
        "metric": "Feature Availability",
        "target": 0.9989,
        "target_display": "99.89%",
        "measurement_window": "monthly",
        "measurement_method": "Uptime monitoring with 1-minute granularity"
      }
    ],
    "penalties": [
      {
        "breach_threshold": "< 99.99%",
        "credit_percentage": 10
      },
      {
        "breach_threshold": "< 99.9%",
        "credit_percentage": 25
      },
      {
        "breach_threshold": "< 99%",
        "credit_percentage": 50
      }
    ],
    "measurement_methodology": "External synthetic monitoring from multiple geographic locations",
    "exclusions": [
      "Planned maintenance windows (with 72h advance notice)",
      "Customer-side network or infrastructure issues",
      "Force majeure events",
      "Third-party service dependencies beyond our control"
    ]
  },
  "monitoring_recommendations": {
    "metrics": {
      "collection": "Prometheus with service discovery",
      "retention": "90 days for raw metrics, 1 year for aggregated",
      "alerting": "Prometheus Alertmanager with multi-window burn rate alerts"
    },
    "logging": {
      "format": "Structured JSON logs with correlation IDs",
      "aggregation": "ELK stack or equivalent with proper indexing",
      "retention": "30 days for debug logs, 90 days for error logs"
    },
    "tracing": {
      "sampling": "Adaptive sampling with 1% base rate",
      "storage": "Jaeger or Zipkin with 7-day retention",
      "integration": "OpenTelemetry instrumentation"
    }
  },
  "implementation_guide": {
    "prerequisites": [
      "Service instrumented with metrics collection (Prometheus format)",
      "Structured logging with correlation IDs",
      "Monitoring infrastructure (Prometheus, Grafana, Alertmanager)",
      "Incident response processes and escalation policies"
    ],
    "implementation_steps": [
      {
        "step": 1,
        "title": "Instrument Service",
        "description": "Add metrics collection for all defined SLIs",
        "estimated_effort": "1-2 days"
      },
      {
        "step": 2,
        "title": "Configure Recording Rules",
        "description": "Set up Prometheus recording rules for SLI calculations",
        "estimated_effort": "4-8 hours"
      },
      {
        "step": 3,
        "title": "Implement Burn Rate Alerts",
        "description": "Configure multi-window burn rate alerting rules",
        "estimated_effort": "1 day"
      },
      {
        "step": 4,
        "title": "Create SLO Dashboard",
        "description": "Build Grafana dashboard for SLO tracking and error budget monitoring",
        "estimated_effort": "4-6 hours"
      },
      {
        "step": 5,
        "title": "Test and Validate",
        "description": "Test alerting and validate SLI measurements against expectations",
        "estimated_effort": "1-2 days"
      },
      {
        "step": 6,
        "title": "Documentation and Training",
        "description": "Document runbooks and train team on SLO monitoring",
        "estimated_effort": "1 day"
      }
    ],
    "validation_checklist": [
      "All SLIs produce expected metric values",
      "Burn rate alerts fire correctly during simulated outages",
      "Error budget calculations match manual verification",
      "Dashboard displays accurate SLO achievement rates",
      "Alert routing reaches correct escalation paths",
      "Runbooks are complete and tested"
    ]
  }
}