claude-flow-novice/monitoring/SLO_DEFINITIONS.md

Claude Flow Novice - Advanced orchestration platform for multi-agent AI workflows with CFN Loop architecture Includes Local RuVector Accelerator and all CFN skills for complete functionality.

# Service Level Objectives (SLO) Definitions

## Overview

Service Level Objectives (SLOs) define the expected performance and reliability targets for the Integration Standardization system. These objectives guide incident response, feature development prioritization, and infrastructure investment decisions.

---

## SLO Framework

### Service Level Indicators (SLIs)

**SLIs** are measurable aspects of service performance:

- Availability (uptime percentage)
- Latency (response time)
- Error Rate (% of failed requests)
- Completeness (% of messages delivered)
- Correctness (% of data corruption)

### Service Level Agreements (SLAs)

**SLAs** are commitments to customers with penalties for non-compliance.

### Service Level Objectives (SLOs)

**SLOs** are internal targets that enable SLA compliance while building reliability.

**Relationship:** SLO ⊃ SLA (SLO is stricter than SLA)

---

## Core SLOs

### 1. Availability SLO

**Definition:** Percentage of time the system is responding to requests.

**Target:** 99.9% uptime

**Measurement Period:** Rolling 30-day window

**Calculation:**
```
Availability = (Total Seconds - Downtime Seconds) / Total Seconds
Expected: 99.9% = max 43.2 minutes downtime per month
```

**Error Budget:** 43.2 minutes per month

**Tracking:**
- Metric: `up{job="integration-standardized"}`
- Query: `avg_over_time(up[30d])`
- Alert: Availability < 99.8% for 10 minutes

**Failure Modes:**
- Service completely down
- All replicas crashed
- Database unreachable
- Network partition

### 2. Latency SLO

**Definition:** Response time for user requests.

**Targets:**
| Percentile | Target | Trigger |
|-----------|--------|---------|
| P50 | 500ms | 750ms |
| P95 | 2s | 3s |
| P99 | 5s | 7.5s |

**Measurement Period:** Continuous (rolling 5-minute windows)

**Calculation:**
```
P50 Latency = 50th percentile response time
P95 Latency = 95th percentile response time
P99 Latency = 99th percentile response time
```

**Error Budget:**
- P99 > 7.5s: -10 points per hour
- P99 > 5s for 30 minutes: Incident declaration

**Tracking:**
- Metric: `http_request_duration_seconds_bucket`
- Query: `histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m]))`
- Alert: P99 > 7.5s for 10 minutes

**Failure Modes:**
- Database query slowdown
- Connection pool exhaustion
- Coordination protocol delays
- Network latency

### 3. Error Rate SLO

**Definition:** Percentage of requests that return errors (5xx status codes).

**Target:** < 0.1% error rate

**Critical Threshold:** > 1% (triggers auto-rollback)

**Measurement Period:** Continuous (rolling 5-minute windows)

**Calculation:**
```
Error Rate = (5xx responses) / (Total responses)
Expected: < 0.1% = max 5 errors per 10,000 requests
```

**Error Budget:** 0.1% per 30-day period

**Tracking:**
- Metric: `http_requests_total{status=~"5.."}`
- Query: `sum(rate(http_requests_total{status=~"5.."}[5m])) / sum(rate(http_requests_total[5m]))`
- Alert: Error rate > 0.1% for 10 minutes

**Failure Modes:**
- Code bugs/exceptions
- Database constraint violations
- Integration point failures
- Resource exhaustion

---

## Integration Point SLOs

### Database Service SLO

**Availability:** 99.95%

**Latency:**
- Read Query P95: < 100ms
- Write Query P95: < 200ms
- Transaction P95: < 500ms

**Error Rate:** < 0.05%

**Metrics:**
```
db_queries_total (labeled by operation type)
db_query_duration_seconds_bucket
db_transaction_duration_seconds_bucket
pg_stat_activity_count
```

**Critical Conditions:**
- Connection pool > 90%
- Replication lag > 30s
- Query failure rate > 1%
- Disk space < 10%

### Coordination Protocol SLO

**Availability:** 99.9%

**Message Delivery Success Rate:** > 99.9%

**Latency:**
- Message delivery P95: < 100ms
- Acknowledgment P95: < 50ms

**Queue Depth:** < 500 messages

**Metrics:**
```
coordination_messages_total
coordination_messages_delivered_total
coordination_protocol_latency_seconds_bucket
redis_queue_size
redis_connected_clients
```

**Critical Conditions:**
- Redis down
- Queue depth > 1000
- Message delivery < 99%
- Latency > 500ms

### Artifact Storage SLO

**Availability:** 99.9%

**Latency:**
- Upload P95: < 2s
- Download P95: < 1s
- List P95: < 500ms

**Error Rate:** < 0.1%

**Metrics:**
```
artifact_storage_operations_total
artifact_storage_errors_total
artifact_storage_latency_seconds_bucket
artifact_storage_backend_available
```

**Critical Conditions:**
- Backend unavailable
- Error rate > 1%
- Latency > 2x baseline
- Storage capacity > 80%

### Metrics Collection SLO

**Delivery Rate:** > 99%

**Latency:** < 1s

**Cardinality Explosion:** < 50k unique metric series

**Metrics:**
```
metrics_collection_total
metrics_collection_errors_total
metrics_collection_latency_seconds_bucket
```

**Critical Conditions:**
- Collection service down
- Delivery < 95%
- Latency > 5s
- Series count > 100k

---

## Non-Functional SLOs

### Security SLO

**Definition:** Vulnerability detection and remediation.

**Targets:**
- Zero critical vulnerabilities in production
- Security validation latency < 100ms
- False positive rate < 0.1%

**Tracking:**
- Vulnerability scans: Daily
- Patch application: Within 48 hours of release
- Penetration testing: Quarterly

### Data Integrity SLO

**Definition:** Data correctness and consistency.

**Targets:**
- Zero data corruption incidents
- Data consistency validation success > 99.99%
- Recovery Time Objective (RTO): < 1 hour

**Metrics:**
```
data_consistency_violations_total
data_corruption_incidents_total
backup_creation_success_rate
```

### Skill Deployment SLO

**Definition:** Integration skill availability and execution.

**Targets:**
- Skill availability: > 99%
- Execution success rate: > 99%
- Average execution time: < 5s

**Metrics:**
```
skill_deployment_status
skill_executions_total
skill_executions_failed_total
skill_execution_duration_seconds_bucket
```

---

## Error Budget Management

### Budget Calculation

```
Total Budget = 100% - SLO Target
Example: 99.9% SLO = 0.1% budget per month

Monthly Budget: 0.1% × 43,200 seconds = 43.2 seconds
Hourly Budget: 0.1% × 3,600 seconds = 3.6 seconds
```

### Budget Tracking

```
Budget Remaining = Total Budget - Consumed Budget

Consumed by:
- Downtime (full availability loss)
- Error rate exceeding SLO
- Latency exceeding SLO (weighted)
```

### Budget Decision Rules

**Sufficient Budget (>25%):**
- Enable risky deployments
- Run chaos engineering experiments
- Perform infrastructure maintenance
- A/B test new features

**Medium Budget (10-25%):**
- Careful deployments only
- No chaos engineering
- Limit infrastructure changes
- Conservative feature rollouts

**Low Budget (<10%):**
- Freeze all non-emergency changes
- Emergency incident focus only
- Enhanced monitoring
- Prepare for manual intervention

**Exhausted Budget:**
- All non-critical work stopped
- Full incident response protocols
- Executive escalation
- Customer communication

---

## SLO Review and Adjustment

### Quarterly Review

**Schedule:** Last week of each quarter

**Participants:** Engineering, DevOps, Product, Leadership

**Assessment:**
- Actual performance vs. SLO target
- Error budget consumption
- Trend analysis
- Customer impact
- Infrastructure capacity

### Review Questions

1. Are we meeting the SLO target?
2. Is the error budget appropriate?
3. Are alerts firing too frequently?
4. Are we over-provisioned or under-provisioned?
5. Should we adjust the SLO?

### Adjustment Criteria

**Increase SLO Target (more stringent) if:**
- Consistently exceeding by >5%
- Customer feedback positive
- Infrastructure capacity available
- Business requirements demand it

**Decrease SLO Target (more lenient) if:**
- Consistently missing by >5%
- Disproportionate infrastructure cost
- Business requirements change
- Customer satisfaction sufficient

---

## Monitoring and Alerting

### SLO Metrics Dashboard

Location: `monitoring/dashboards/integration-overview.json`

**Key Panels:**
- Availability trend (30-day rolling)
- Error rate distribution
- Latency percentiles (P50, P95, P99)
- Error budget consumption
- Integration point health

### Alert Rules

**SLO Violation Alerts:**
```yaml
Alert: AvailabilitySLOViolation
Condition: availability < 99.8%
Duration: 10 minutes
Severity: Warning

Alert: ErrorRateSLOViolation
Condition: error_rate > 0.1%
Duration: 10 minutes
Severity: High

Alert: LatencySLOViolation
Condition: p99_latency > 7.5s
Duration: 10 minutes
Severity: High
```

**Error Budget Alerts:**
```yaml
Alert: ErrorBudgetLow
Condition: consumed_budget > 75%
Duration: 1 minute
Severity: Warning

Alert: ErrorBudgetCritical
Condition: consumed_budget > 90%
Duration: 1 minute
Severity: Critical
```

### Runbooks

**For each SLO violation:**
- `docs/INCIDENT_RESPONSE.md` - General procedures
- `docs/ROLLBACK_RUNBOOK.md` - Rollback procedures
- Integration-specific runbooks (database, coordination, etc.)

---

## SLO Success Criteria

### During Rollout Phases

**Phase 1: Canary (10%)**
- Maintain SLO targets
- Error rate < 0.1%
- Latency increase < 5%
- Go/No-Go decision at 48 hours

**Phase 2: Staged (50%)**
- Maintain SLO targets
- Error rate < 0.1%
- Latency increase < 8%
- Go/No-Go decision at 72 hours

**Phase 3: Full (100%)**
- Maintain SLO targets
- Error rate < 0.1%
- Latency increase < 10%
- Stable for 7 days

### Post-Rollout SLOs

**Weeks 1-4:**
- 99.9% availability
- < 0.1% error rate
- P99 latency < 7.5s
- No critical incidents

**Months 2-3:**
- 99.95% availability
- < 0.05% error rate
- P99 latency < 5s
- < 1 SEV2 incident per month

**Month 4+:**
- 99.95%+ availability
- < 0.05% error rate
- P99 latency < 5s (normalized)
- Capacity planning for growth

---

## Example: SLO Calculation

### Scenario: Monday Error Rate

```
Requests at 10:00: 100,000
Successful: 99,900
Errors: 100
Error Rate: 100/100,000 = 0.1%

SLO Target: < 0.1%
Status: AT THRESHOLD - Alert triggered

Consumed Error Budget:
0.1% for 1 minute = 0.1% / (60 min × 24 hours × 30 days) × 1 min
= 0.1% / 43,200 min × 1 min
= 0.00000231% per minute
= 100 × 0.00000231% = 0.000231% consumed
```

### Scenario: Monthly Budget Tracking

```
Month: November (2,592,000 seconds)
Budget: 0.1% = 2,592 seconds (43.2 minutes)

Events:
Nov 5:  15-minute outage = 900 seconds consumed (budget: 1,692s remaining)
Nov 12: Error rate spike = 10 minutes × 0.1% = 600 seconds consumed (budget: 1,092s remaining)
Nov 25: Maintenance window = 30-minute downtime × 100% = 1,800 seconds (EXCEEDS budget)

Result: SLO VIOLATED on Nov 25
Impact: Error budget exhausted, all non-critical deployments frozen
```

---

## References

- [Google SRE Book - SLOs](https://sre.google/books/)
- Rollout Plan: `docs/ROLLOUT_PLAN.md`
- Incident Response: `docs/INCIDENT_RESPONSE.md`
- Monitoring Dashboards: `monitoring/dashboards/`
- Alert Rules: `monitoring/alerts/`

---

**Last Updated:** 2025-11-16
**Version:** 1.0
**Status:** Active
**Next Review:** 2026-02-16 (Quarterly)