# SRE Review: Task Orchestration Master Plan

**Document**: TASK_ORCHESTRATION_MASTER_PLAN.md
**Reviewer**: Site Reliability Engineer
**Date**: 2026-02-18
**Version**: 1.0

---

## Executive Summary

**Overall Assessment**: APPROVE WITH CHANGES

**Operational Readiness Rating**: 5/10

The Task Orchestration Master Plan presents a well-architected system with strong feature capabilities, but has **significant operational readiness gaps** that must be addressed before production deployment. The plan excels in user experience and ecosystem integration but lacks critical SRE fundamentals including SLIs/SLOs, monitoring strategy, capacity planning, and production-hardened deployment patterns.

---

## Critical Findings (Must Fix Before Production)

### 1. No SLI/SLO Definitions ✗ CRITICAL

**Issue**: The plan has no defined Service Level Indicators (SLIs) or Service Level Objectives (SLOs).

**Impact**:
- No reliability targets to measure against
- No error budget policy for feature freezes
- Cannot quantify "production ready"
- No basis for alerting thresholds

**Required Actions**:
- Define SLIs for: task creation latency, query latency, availability, durability
- Set SLO targets (e.g., 99.9% availability, <100ms p95 latency)
- Implement error budget tracking
- Create error budget policy for feature freezes

**Evidence**:
```yaml
# MISSING: No SLI/SLO section in plan
# NEEDED:
SLIs:
  - task_creation_latency_p99: <500ms
  - task_query_latency_p95: <100ms
  - task_availability: 99.9%
  - data_durability: 99.999%

SLOs:
  - Monthly uptime target: 99.9% (43min downtime/month)
  - Error budget: 43min/month
```

### 2. No Monitoring Strategy ✗ CRITICAL

**Issue**: No monitoring architecture, metrics schema, or alerting strategy defined.

**Impact**:
- No observability into system health
- Blind spots during incidents
- No proactive failure detection
- Difficult to troubleshoot issues

**Required Actions**:
- Define golden signals (latency, traffic, errors, saturation)
- Create metrics schema (task_* metrics)
- Design alerting rules (P0/P1/P2 thresholds)
- Implement dashboards (Grafana)
- Add distributed tracing (OTel integration)

**Recommended Metrics**:
```yaml
# Task orchestration metrics
task_creation_total{status, repository, priority}
task_creation_duration_seconds{status}
task_query_total{method, status}
task_query_duration_seconds{method, status}
task_dependency_graph_depth{task_id}
task_workflow_stage_duration{stage, status}

# Storage backend metrics
task_storage_sqlite_query_duration_seconds{operation, table}
task_storage_akosha_index_duration_seconds{operation}
task_storage_session_buddy_store_duration_seconds{operation}

# Integration metrics
task_github_webhook_received_total{status}
task_approval_queue_depth
task_quality_gate_duration_seconds{gate, result}
```

### 3. No Capacity Planning ✗ HIGH

**Issue**: No performance modeling, load testing strategy, or scaling limits defined.

**Impact**:
- Unknown system limits
- Unexpected degradation under load
- No scaling strategy
- Risk of production outage

**Required Actions**:
- Define capacity targets (tasks/sec, concurrent users, storage growth)
- Perform load testing (target: 1000+ tasks as stated in plan)
- Document scaling strategy (horizontal vs vertical)
- Set resource limits (CPU, memory, disk)
- Create capacity planning playbook

**Performance Targets (Missing)**:
```yaml
# REQUIRED: Capacity targets
max_tasks_per_system: 10000
max_concurrent_task_operations: 100
task_creation_rate_target: 10 tasks/sec
query_latency_target_p95: 100ms
storage_growth_per_task: 1MB (SQLite) + 2KB (Akosha) + 5KB (Session-Buddy)

# Scaling strategy
scaling:
  type: horizontal  # SQLite is single-node limitation
  max_instances: 1  # Need to address this limitation
  fallback: "Migrate to PostgreSQL for HA"
```

### 4. No Backup/Recovery Testing Strategy ✗ HIGH

**Issue**: Plan mentions backup strategy (line 907) but no testing, verification, or RPO/RTO targets.

**Impact**:
- Backups may fail silently
- No confidence in recovery procedures
- Risk of permanent data loss
- Does not meet existing DR runbook standards

**Required Actions**:
- Define RPO/RTO targets for task data
- Implement automated backup testing
- Document restore procedures
- Add backup monitoring/alerting
- Test disaster recovery drills quarterly

**Backup Requirements (Missing)**:
```yaml
# REQUIRED: Backup policy
backup:
  rto_target: 1 hour  # Current runbook: 4 hours
  rpo_target: 1 hour  # Current runbook: 24 hours
  schedule: hourly
  retention:
    hourly: 24 hours
    daily: 30 days
    weekly: 12 weeks
  testing: "Automated restore test weekly"
  monitoring: "Alert if backup fails or >1 hour overdue"

  components:
    - name: SQLite tasks database
      type: sqlite
      backup_method: "sqlite3 .backup"
      size_estimate: "1MB per 1000 tasks"
    - name: Akosha task embeddings
      type: vector_db
      backup_method: "GraphML export"
      size_estimate: "2KB per task"
    - name: Session-Buddy task context
      type: json
      backup_method: "Session export"
      size_estimate: "5KB per task"
```

### 5. No Deployment Strategy ✗ HIGH

**Issue**: No deployment patterns, release process, or rollback procedures defined.

**Impact**:
- Risky production deployments
- No blue/green or canary capability
- Difficult to rollback bad releases
- Potential for extended outages

**Required Actions**:
- Define deployment pattern (blue/green, canary, rolling)
- Implement health checks for deployment
- Create rollback procedures
- Add feature flags for gradual rollout
- Document pre-flight checks

**Deployment Strategy (Missing)**:
```yaml
# REQUIRED: Deployment process
deployment:
  pattern: blue_green  # Recommended for zero-downtime
  health_checks:
    - endpoint: /health
      interval: 10s
      timeout: 5s
      threshold: 3
  rollback:
    trigger: "auto_on_health_check_failure"
    procedure: "Switch traffic back to previous version"
  pre_flight:
    - "Run integration tests"
    - "Check database migrations"
    - "Verify configuration validity"
  post_deploy:
    - "Monitor error rate for 15min"
    - "Check key metrics (latency, throughput)"
```

### 6. Limited Incident Response Integration ✗ MEDIUM

**Issue**: Plan doesn't reference existing incident response runbook or define task-specific incidents.

**Impact**:
- Inconsistent incident handling
- Missing task-specific runbooks
- Slower MTTR during incidents

**Required Actions**:
- Integrate with existing incident response runbook
- Create task-specific incident scenarios
- Define task orchestration-specific playbooks
- Add on-call rotation consideration

**Task-Specific Incidents (Missing)**:
```yaml
# REQUIRED: Task-specific incident scenarios
incidents:
  - name: Task creation spike
    severity: P1
    symptoms:
      - "Task creation latency >1s"
      - "Backlog building in approval queue"
    runbook: "docs/tasks/incident_task_spike.md"

  - name: Semantic search failure
    severity: P2
    symptoms:
      - "Akosha search returns no results"
      - "Fallback to full-text search"
    runbook: "docs/tasks/incident_search_failure.md"

  - name: Worktree orphanage
    severity: P2
    symptoms:
      - "Task deleted but worktree remains"
      - "Disk space filling with orphaned worktrees"
    runbook: "docs/tasks/incident_worktree_orphanage.md"
```

---

## Operational Gaps Analysis

### Monitoring & Observability

| Area | Status | Gap | Priority |
|------|--------|-----|----------|
| **Metrics Collection** | ✗ Missing | No task orchestration metrics defined | CRITICAL |
| **Logging Strategy** | ✗ Missing | No structured logging for task operations | HIGH |
| **Distributed Tracing** | ✓ Partial | Plan mentions OpenTelemetry ingestion but no task tracing | HIGH |
| **Dashboards** | ✗ Missing | No Grafana dashboard design for task metrics | HIGH |
| **Alerting** | ✗ Missing | No alert rules or on-call integration | CRITICAL |

### Reliability Engineering

| Area | Status | Gap | Priority |
|------|--------|-----|----------|
| **SLIs/SLOs** | ✗ Missing | No reliability targets defined | CRITICAL |
| **Error Budgets** | ✗ Missing | No error budget policy | CRITICAL |
| **Capacity Planning** | ✗ Missing | No performance modeling or load testing | HIGH |
| **Load Testing** | ✗ Missing | No load test strategy (plan mentions 1000+ tasks) | HIGH |
| **Chaos Engineering** | ✗ Missing | No failure injection testing | MEDIUM |

### Backup & Disaster Recovery

| Area | Status | Gap | Priority |
|------|--------|-----|----------|
| **Backup Strategy** | ⚠ Partial | Mentioned but no testing/verification | HIGH |
| **RPO/RTO** | ✗ Missing | No targets defined | HIGH |
| **Backup Testing** | ✗ Missing | No automated restore testing | HIGH |
| **DR Drills** | ✗ Missing | No quarterly drill schedule | MEDIUM |
| **Data Migration** | ✗ Missing | No migration path from SQLite to HA DB | HIGH |

### Deployment & Release

| Area | Status | Gap | Priority |
|------|--------|-----|----------|
| **Deployment Pattern** | ✗ Missing | No blue/green or canary strategy | HIGH |
| **Health Checks** | ⚠ Partial | Mentioned but not defined | HIGH |
| **Rollback** | ✗ Missing | No rollback procedures | HIGH |
| **Feature Flags** | ✗ Missing | No gradual rollout capability | MEDIUM |
| **Database Migrations** | ✗ Missing | No migration strategy | HIGH |

### Incident Management

| Area | Status | Gap | Priority |
|------|--------|-----|----------|
| **Runbooks** | ✗ Missing | No task-specific incident runbooks | HIGH |
| **Escalation** | ✓ Existing | Can use existing escalation paths | - |
| **Postmortems** | ✓ Existing | Can use existing postmortem process | - |
| **Communication** | ✓ Existing | Can use existing templates | - |

---

## Recommendations

### Phase 0: SRE Fundamentals (Pre-Production)

**Before launching any production instance:**

1. **Define SLIs/SLOs** (1-2 days)
   - Create `docs/sre/task_slos.md`
   - Implement 4-5 core SLIs
   - Set up error budget tracking
   - Define error budget policy

2. **Implement Monitoring** (2-3 days)
   - Design metrics schema (20-30 metrics)
   - Set up Prometheus metrics export
   - Create Grafana dashboards (3-5 dashboards)
   - Configure alerting rules (10-15 rules)

3. **Document Deployment** (1 day)
   - Choose deployment pattern (recommend blue/green)
   - Write deployment runbook
   - Add health check endpoints
   - Test rollback procedures

4. **Capacity Testing** (2-3 days)
   - Define capacity targets
   - Perform load testing (k6, locust)
   - Document system limits
   - Create scaling playbook

5. **Backup Verification** (1-2 days)
   - Implement automated backup testing
   - Document restore procedures
   - Set RPO/RTO targets
   - Test disaster recovery drill

**Total Effort**: 7-11 days

### Phase 1: Production Hardening (Weeks 1-4)

**During initial rollout:**

1. **Hardening Monitoring**
   - Add distributed tracing for task workflows
   - Implement synthetic canary tasks
   - Create anomaly detection (PromQL queries)
   - Set up SLO dashboards

2. **Improve Reliability**
   - Implement circuit breakers for external integrations
   - Add retry policies with exponential backoff
   - Create graceful degradation patterns
   - Add rate limiting

3. **Operational Excellence**
   - Create runbook library (10+ scenarios)
   - Implement on-call rotation (if multi-user)
   - Set up duty phone/pager
   - Create war room procedures

### Phase 2: Scalability Preparation (Weeks 5-8)

**Before scaling to 100+ users:**

1. **Database Scaling**
   - Migrate from SQLite to PostgreSQL (HA)
   - Implement read replicas for query load
   - Add connection pooling
   - Set up automated failover

2. **Performance Optimization**
   - Implement caching layer (Redis)
   - Add query optimization
   - Create database indexes
   - Optimize embedding generation

3. **Multi-Region Deployment**
   - Design multi-region architecture
   - Implement data replication
   - Set up cross-region failover
   - Create regional deployment guides

---

## Specific Technical Concerns

### 1. SQLite Single-Node Limitation ⚠️

**Issue**: SQLite is single-node by design, limiting horizontal scaling.

**Impact**:
- Single point of failure
- Cannot scale horizontally
- Limited concurrent writes
- Risk of database lock contention

**Recommendation**:
```yaml
# Short-term (Phase 1): Acceptable for <100 users
storage:
  type: sqlite
  limitations: "Single node, max 100 concurrent writes"
  mitigation: "Connection pooling, write batching"

# Long-term (Phase 2): Migrate for HA
storage:
  type: postgresql
  features: ["HA", "read_replicas", "automatic_failover"]
  migration_path: "Use pgloader for zero-downtime migration"
```

### 2. No Database Migration Strategy ⚠️

**Issue**: SQLite schema will evolve; no migration tool specified.

**Impact**:
- Risk of data loss during schema changes
- Difficult to rollback schema changes
- Manual migration errors

**Recommendation**:
- Use Alembic for database migrations
- Implement backward-compatible migrations
- Test migrations on staging first
- Add migration rollback capability

### 3. Worktree Orphanage Risk ⚠️

**Issue**: Tasks can be deleted without cleaning up worktrees (line 701-706 shows cleanup is optional).

**Impact**:
- Disk space exhaustion
- Accumulation of orphaned worktrees
- Difficult to clean up manually

**Recommendation**:
```python
# REQUIRED: Worktree lifecycle management
async def cleanup_orphaned_worktrees():
    """Periodic cleanup of orphaned worktrees."""
    orphaned = await find_orphaned_worktrees()
    for worktree in orphaned:
        if worktree.last_modified > days(7):
            await worktree.remove()
            logger.info(f"Cleaned up orphaned worktree: {worktree.path}")
```

### 4. No Rate Limiting on Task Creation ⚠️

**Issue**: No rate limiting mentioned for task creation API/webhooks.

**Impact**:
- Spam task creation via GitHub webhooks
- Resource exhaustion
- Database overload

**Recommendation**:
```yaml
# REQUIRED: Rate limiting
rate_limiting:
  task_creation:
    per_user: "10 tasks/minute"
    per_ip: "100 tasks/hour"
    webhook: "1000 tasks/hour per repo"
  storage: "Redis for distributed rate limiting"
```

### 5. Quality Gate Blocking Without Override ⚠️

**Issue**: Quality gates block completion (line 686-688), but override is manual confirmation.

**Impact**:
- Emergency fixes delayed
- Developer frustration
- Potential for unsafe forced completions

**Recommendation**:
```python
# REQUIRED: Emergency override with audit
async def complete_task_with_emergency_override(
    task_id: str,
    reason: str,
    approver: str,
) -> Task:
    """Complete task despite failed quality gates with audit trail."""
    await audit_log.log(
        event="emergency_quality_gate_override",
        task_id=task_id,
        reason=reason,
        approver=approver,
        timestamp=datetime.now(UTC),
    )
    # Notify on-call for review
    await alert_on_call(f"Emergency override: {task_id}")
```

---

## Production Readiness Checklist

### Pre-Production (Must Complete)

- [ ] **SLIs/SLOs defined**
  - [ ] Latency SLOs (p50, p95, p99)
  - [ ] Availability SLO (99.9%+)
  - [ ] Durability SLO (99.999%+)
  - [ ] Error budget policy
  - [ ] SLO tracking dashboard

- [ ] **Monitoring implemented**
  - [ ] Metrics collection (Prometheus)
  - [ ] Logging (structured JSON)
  - [ ] Tracing (OpenTelemetry)
  - [ ] Dashboards (Grafana)
  - [ ] Alerting (PagerDuty/Slack)
  - [ ] On-call rotation

- [ ] **Capacity planning**
  - [ ] Performance targets defined
  - [ ] Load testing completed (1000+ tasks)
  - [ ] Scaling strategy documented
  - [ ] Resource limits set
  - [ ] Capacity planning playbook

- [ ] **Backup/recovery**
  - [ ] Automated backups (hourly)
  - [ ] Backup testing (weekly)
  - [ ] RPO/RTO targets (1h/1h)
  - [ ] Restore procedures tested
  - [ ] DR drill completed

- [ ] **Deployment**
  - [ ] Deployment pattern chosen
  - [ ] Health check endpoints
  - [ ] Rollback procedures tested
  - [ ] Pre-flight checks automated
  - [ ] Feature flags implemented

- [ ] **Security**
  - [ ] Authentication configured
  - [ ] Authorization tested
  - [ ] Secrets management
  - [ ] Input validation
  - [ ] Rate limiting

### Post-Production (Within 30 Days)

- [ ] **Reliability hardening**
  - [ ] Circuit breakers implemented
  - [ ] Retry policies configured
  - [ ] Graceful degradation tested
  - [ ] Chaos engineering started

- [ ] **Operational excellence**
  - [ ] Runbook library (10+ scenarios)
  - [ ] Incident response drills
  - [ ] Postmortem process active
  - [ ] Knowledge base created

---

## Approved With Conditions

### Condition 1: SRE Fundamentals (BLOCKING)

**Required before production deployment**:
1. Define SLIs/SLOs with error budget policy
2. Implement monitoring (metrics, dashboards, alerting)
3. Document deployment and rollback procedures
4. Complete capacity testing (1000+ tasks)
5. Verify backup/recovery procedures

**Estimated effort**: 7-11 days

### Condition 2: Technical Debt Management (HIGH)

**Required before scaling to 100+ users**:
1. Migrate from SQLite to PostgreSQL (HA)
2. Implement database migration strategy (Alembic)
3. Add rate limiting for task creation
4. Implement worktree lifecycle management
5. Add emergency override audit trail

**Estimated effort**: 14-21 days

### Condition 3: Operational Excellence (MEDIUM)

**Required for production excellence**:
1. Create runbook library (10+ scenarios)
2. Implement distributed tracing
3. Add synthetic canary tasks
4. Set up on-call rotation
5. Conduct quarterly DR drills

**Estimated effort**: 7-10 days

---

## Conclusion

The Task Orchestration Master Plan demonstrates excellent architectural design and feature engineering, but requires significant SRE investment before production deployment. The plan's strong integration with existing ecosystem components (Akosha, Dhruva, Session-Buddy, Crackerjack) provides a solid foundation, but the lack of SLI/SLO definitions, monitoring strategy, capacity planning, and production-hardened deployment patterns pose unacceptable risks for a production system.

**Recommendation**: **APPROVE WITH CHANGES**

**Required Actions**:
1. Complete Phase 0: SRE Fundamentals (7-11 days)
2. Address critical findings (SLIs/SLOs, monitoring, capacity, backups, deployment)
3. Implement production hardening (Phase 1)
4. Plan for scalability migration (Phase 2)

**Operational Readiness Rating**: **5/10** (Significant gaps, needs SRE investment)

**Post-Remediation Projection**: **8.5/10** (After addressing critical findings)

---

## Appendix: SRE Metrics Template

### SLI/SLO Definitions

```yaml
# Task Orchestration SLIs/SLOs
service_level_indicators:
  task_creation_latency:
    description: "Time from task creation request to database commit"
    unit: milliseconds
    slos:
      p50: <50ms
      p95: <100ms
      p99: <500ms

  task_query_latency:
    description: "Time from task query request to response"
    unit: milliseconds
    slos:
      p50: <20ms
      p95: <100ms
      p99: <200ms

  task_availability:
    description: "Percentage of successful task operations"
    unit: percent
    slos:
      monthly: 99.9%  # 43 minutes downtime/month
      weekly: 99.95%  # 10 minutes downtime/week

  data_durability:
    description: "Probability of data loss"
    unit: percent
    slos:
      annual: 99.999%  # 5 minutes data loss/year

error_budget:
  monthly_budget: 43 minutes
  burn_rate_alerting:
    warning: 2x normal burn rate
    critical: 5x normal burn rate
  feature_freeze: "When error budget < 10%"
```

### Monitoring Metrics

```yaml
# Prometheus metrics schema
metrics:
  task_creation_total:
    type: counter
    labels: [status, repository, priority, source]
    help: "Total number of task creation attempts"

  task_creation_duration_seconds:
    type: histogram
    labels: [status, repository]
    buckets: [0.01, 0.05, 0.1, 0.5, 1.0, 5.0]
    help: "Task creation latency distribution"

  task_query_total:
    type: counter
    labels: [method, status]
    help: "Total number of task queries"

  task_dependency_depth:
    type: gauge
    labels: [task_id]
    help: "Depth of task dependency graph"

  task_quality_gate_duration_seconds:
    type: histogram
    labels: [gate, result]
    buckets: [1, 5, 10, 30, 60, 300]
    help: "Quality gate execution time"

  task_approval_queue_depth:
    type: gauge
    help: "Number of pending task approvals"

  storage_operation_duration_seconds:
    type: histogram
    labels: [storage, operation]
    buckets: [0.001, 0.01, 0.1, 1.0]
    help: "Storage operation latency"
```

### Alerting Rules

```yaml
# Alertmanager rules
groups:
  - name: task_orchestration_critical
    interval: 30s
    rules:
      - alert: HighTaskCreationLatency
        expr: histogram_quantile(0.99, task_creation_duration_seconds) > 1.0
        for: 5m
        labels:
          severity: P1
        annotations:
          summary: "Task creation latency above SLO"
          description: "P99 latency {{ $value }}s exceeds 1s threshold"

      - alert: TaskCreationFailureRate
        expr: rate(task_creation_total{status="error"}[5m]) > 0.05
        for: 5m
        labels:
          severity: P0
        annotations:
          summary: "High task creation failure rate"
          description: "{{ $value | humanizePercentage }} of tasks failing"

      - alert: ApprovalQueueBacklog
        expr: task_approval_queue_depth > 100
        for: 15m
        labels:
          severity: P1
        annotations:
          summary: "Approval queue backlog"
          description: "{{ $value }} tasks awaiting approval"

      - alert: StorageOperationFailure
        expr: rate(storage_operation_duration_seconds{status="error"}[5m]) > 0.01
        for: 5m
        labels:
          severity: P0
        annotations:
          summary: "Storage operation failures"
          description: "Storage errors at {{ $value | humanizePercentage }}"
```

---

**Reviewer Signature**: SRE Team
**Review Date**: 2026-02-18
**Next Review**: After SRE fundamentals implemented
**Approval**: Conditional on critical findings resolution
