# Deployment Strategies

**Version:** 1.0.0  
**Last Updated:** 2026-03-13  
**Status:** ✅ Production Ready

---

## Executive Summary

This document outlines deployment strategies for UAP, including window bucketing, batch processing, and resource isolation techniques for production environments.

---

## 1. Window Bucketing

### 1.1 Overview

**What it does:** Isolates resources into time-based windows for controlled deployment and rollback  
**Why included:** Enable safe deployments with automatic rollback capabilities  
**Window Types:** Development, Staging, Production

### 1.2 Window Configuration

```json
{
  "deployment": {
    "windowBucketing": {
      "enabled": true,
      "windows": [
        {
          "name": "development",
          "schedule": "0 */6 * * *",
          "resources": {
            "maxVRAM": 16384,
            "maxContext": 65536,
            "maxConcurrent": 2
          },
          "rollout": {
            "percentage": 100,
            "canary": false
          }
        },
        {
          "name": "staging",
          "schedule": "0 0 * * *",
          "resources": {
            "maxVRAM": 24576,
            "maxContext": 131072,
            "maxConcurrent": 5
          },
          "rollout": {
            "percentage": 50,
            "canary": true
          }
        },
        {
          "name": "production",
          "schedule": "0 0 1 * *",
          "resources": {
            "maxVRAM": 24576,
            "maxContext": 262144,
            "maxConcurrent": 10
          },
          "rollout": {
            "percentage": 10,
            "canary": true
          }
        }
      ]
    }
  }
}
```

### 1.3 Window Schedules

| Window          | Schedule      | Purpose                        | Rollout    |
| --------------- | ------------- | ------------------------------ | ---------- |
| **Development** | Every 6 hours | Local testing, rapid iteration | 100%       |
| **Staging**     | Daily         | Integration testing, canary    | 50%        |
| **Production**  | Monthly       | Full deployment, canary        | 10% → 100% |

### 1.4 Resource Allocation

**Development Window:**

- Max VRAM: 16GB
- Max Context: 64K
- Max Concurrent: 2 agents

**Staging Window:**

- Max VRAM: 24GB
- Max Context: 128K
- Max Concurrent: 5 agents

**Production Window:**

- Max VRAM: 24GB
- Max Context: 256K
- Max Concurrent: 10 agents

### 1.5 Rollout Strategy

**Canary Deployment:**

```
1. Deploy to 10% of production window
2. Monitor for errors, latency, token usage
3. If stable after 1 hour: 25% → 50% → 75% → 100%
4. If errors detected: Automatic rollback to previous version
```

**Rollback Triggers:**

- Error rate > 5%
- Latency > 2x baseline
- Token usage > 150% of baseline
- Success rate < 85%

---

## 2. Batch Processing

### 2.1 Overview

**What it does:** Groups tasks into batches for efficient resource utilization  
**Why included:** Reduce overhead, improve throughput, enable parallel processing  
**Batch Types:** Sequential, Parallel, Priority-based

### 2.2 Batch Configuration

```json
{
  "batching": {
    "enabled": true,
    "strategies": [
      {
        "name": "sequential",
        "batchSize": 1,
        "maxConcurrent": 1,
        "timeout": 300000
      },
      {
        "name": "parallel",
        "batchSize": 5,
        "maxConcurrent": 3,
        "timeout": 600000
      },
      {
        "name": "priority",
        "batchSize": 10,
        "maxConcurrent": 5,
        "timeout": 900000,
        "priorityLevels": ["critical", "high", "medium", "low"]
      }
    ]
  }
}
```

### 2.3 Batch Strategies

| Strategy       | Batch Size | Concurrent | Use Case                    |
| -------------- | ---------- | ---------- | --------------------------- |
| **Sequential** | 1          | 1          | Critical tasks, debugging   |
| **Parallel**   | 5          | 3          | Medium priority, throughput |
| **Priority**   | 10         | 5          | High volume, mixed priority |

### 2.4 Batch Processing Flow

```
1. Task submitted to batch queue
2. Batch size reached or timeout triggered
3. Tasks grouped by priority
4. Parallel execution within batch
5. Results aggregated
6. Individual task completion reported
```

### 2.5 Performance Characteristics

| Strategy   | Throughput | Latency  | Resource Usage |
| ---------- | ---------- | -------- | -------------- |
| Sequential | Low        | Low      | Minimal        |
| Parallel   | Medium     | Medium   | Moderate       |
| Priority   | High       | Variable | High           |

---

## 3. Resource Isolation

### 3.1 Overview

**What it does:** Isolates resources per task, agent, or workspace  
**Why included:** Prevent resource contention, enable fair sharing, improve reliability  
**Isolation Types:** Process-level, Memory-level, Network-level

### 3.2 Process Isolation

**Worktree-based Isolation:**

```bash
# Create isolated worktree
uap worktree create task-123

# All changes in isolated branch
cd .worktrees/123-task-123/
# ... make changes ...
git commit -m "Task 123 changes"
```

**Process-level Isolation:**

```json
{
  "isolation": {
    "process": {
      "enabled": true,
      "sandbox": true,
      "memoryLimit": "2GB",
      "cpuLimit": "1 core",
      "networkIsolation": true
    }
  }
}
```

### 3.3 Memory Isolation

**Tiered Memory Allocation:**

| Tier | Memory      | Access | Use Case            |
| ---- | ----------- | ------ | ------------------- |
| HOT  | 10 entries  | <1ms   | Active task context |
| WARM | 50 entries  | <5ms   | Current session     |
| COLD | 500 entries | ~50ms  | Long-term patterns  |

**Memory Quotas:**

```json
{
  "memory": {
    "hot": {
      "maxEntries": 10,
      "maxBytes": 102400
    },
    "warm": {
      "maxEntries": 50,
      "maxBytes": 512000
    },
    "cold": {
      "maxEntries": 500,
      "maxBytes": 5120000
    }
  }
}
```

### 3.4 Network Isolation

**Network Policies:**

```yaml
# NetworkPolicy for agent isolation
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: agent-isolation
spec:
  podSelector:
    matchLabels:
      app: uap-agent
  policyTypes:
    - Ingress
    - Egress
  egress:
    - to:
        - namespaceSelector:
            matchLabels:
              name: allowed-services
      ports:
        - protocol: TCP
          port: 8080
```

---

## 4. Scaling Strategies

### 4.1 Horizontal Scaling

**Auto-scaling Configuration:**

```json
{
  "scaling": {
    "horizontal": {
      "enabled": true,
      "minReplicas": 2,
      "maxReplicas": 10,
      "targetCPUUtilization": 70,
      "targetMemoryUtilization": 80,
      "scaleUpThreshold": 80,
      "scaleDownThreshold": 30,
      "scaleUpCooldown": 300,
      "scaleDownCooldown": 600
    }
  }
}
```

**Scaling Triggers:**

- CPU utilization > 70%
- Memory utilization > 80%
- Queue depth > 100 tasks
- Latency > 2x baseline

### 4.2 Vertical Scaling

**Resource Scaling:**

```json
{
  "scaling": {
    "vertical": {
      "enabled": true,
      "minVRAM": 16384,
      "maxVRAM": 24576,
      "minContext": 32768,
      "maxContext": 262144,
      "scaleUpThreshold": 85,
      "scaleDownThreshold": 25
    }
  }
}
```

### 4.3 Burst Scaling

**Burst Configuration:**

```json
{
  "scaling": {
    "burst": {
      "enabled": true,
      "maxBurstReplicas": 5,
      "burstDuration": 300,
      "cooldown": 600
    }
  }
}
```

---

## 5. Deployment Pipelines

### 5.1 CI/CD Pipeline

```yaml
# .github/workflows/deploy.yaml
name: Deploy UAP
on:
  push:
    branches: [main]
  workflow_dispatch:

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Setup Terraform
        uses: hashicorp/setup-terraform@v3

      - name: Terraform Plan
        run: |
          cd terraform
          terraform init
          terraform plan -out=plan.out

      - name: Security Scan
        run: |
          trivy fs terraform/

      - name: Apply (if approved)
        if: github.ref == 'refs/heads/main'
        run: |
          cd terraform
          terraform apply plan.out

      - name: Deploy UAP
        run: |
          uap deploy --env production

      - name: Health Check
        run: |
          uap health check
```

### 5.2 Deployment Phases

| Phase           | Duration   | Actions                        |
| --------------- | ---------- | ------------------------------ |
| **Development** | Continuous | Local testing, rapid iteration |
| **Staging**     | Daily      | Integration testing, canary    |
| **Production**  | Monthly    | Full deployment, monitoring    |
| **Rollback**    | As needed  | Automatic rollback on failure  |

### 5.3 Deployment Checklist

**Pre-Deployment:**

- [ ] All tests passing
- [ ] Security scan clean
- [ ] Terraform plan reviewed
- [ ] Rollback plan documented
- [ ] Monitoring configured

**Post-Deployment:**

- [ ] Health checks passing
- [ ] Metrics within baseline
- [ ] No error spikes
- [ ] Token usage normal
- [ ] Success rate > 90%

---

## 6. Monitoring and Observability

### 6.1 Key Metrics

| Metric             | Description       | Target  |
| ------------------ | ----------------- | ------- |
| **Token Usage**    | Tokens per task   | < 30K   |
| **Latency**        | Response time     | < 100ms |
| **Success Rate**   | Tasks completed   | > 90%   |
| **Error Rate**     | Failed tasks      | < 5%    |
| **Resource Usage** | VRAM, CPU, Memory | < 80%   |

### 6.2 Alerting Configuration

```json
{
  "monitoring": {
    "alerts": [
      {
        "metric": "error_rate",
        "threshold": 5,
        "duration": "5m",
        "severity": "critical"
      },
      {
        "metric": "latency_p99",
        "threshold": 200,
        "duration": "5m",
        "severity": "warning"
      },
      {
        "metric": "token_usage",
        "threshold": 50000,
        "duration": "1h",
        "severity": "info"
      }
    ]
  }
}
```

### 6.3 Dashboards

**Key Dashboards:**

1. **Overview** - Overall system health
2. **Token Usage** - Token consumption by task
3. **Performance** - Latency and throughput
4. **Errors** - Error tracking and analysis
5. **Resources** - VRAM, CPU, memory usage

---

## 7. Best Practices

### 7.1 Production Deployment

1. **Start with development window** - Test thoroughly
2. **Use canary deployments** - Gradual rollout
3. **Monitor key metrics** - Alert on anomalies
4. **Have rollback ready** - Quick recovery
5. **Document everything** - Runbooks, playbooks

### 7.2 Resource Optimization

1. **Enable memory tiering** - Hot/warm/cold
2. **Use appropriate quantization** - Balance accuracy/context
3. **Batch similar tasks** - Improve throughput
4. **Scale horizontally** - Add capacity as needed
5. **Monitor and adjust** - Continuous optimization

### 7.3 Security

1. **Network isolation** - Isolate agents
2. **Secret management** - Never store in memory
3. **Audit logging** - Track all actions
4. **Access control** - RBAC for all operations
5. **Regular updates** - Keep dependencies current

---

**Last Updated:** 2026-03-13  
**Version:** 1.0.0  
**Status:** ✅ Production Ready
