# Cost Service

Per-vehicle cost estimation service for capacity planning and cloud vs on-prem comparison.

## Overview

This service estimates the cost of running cloud services per VIN by:
1. Querying vehicle activity from ClickHouse (message counts)
2. Estimating resource usage based on activity level
3. Applying cost rates for cloud vs on-prem hosting
4. Storing aggregated cost data for reporting

## Cost Estimation Methodology

### Resource Estimates Per Active VIN

| Activity Level | Messages/15min | CPU (cores) | Memory (GB) |
|---------------|----------------|-------------|-------------|
| Low           | < 100          | 0.80        | 1.20        |
| Medium        | 100-1000       | 1.20        | 1.80        |
| High          | > 1000         | 1.60        | 2.40        |

These estimates account for the full data pipeline per vehicle:
- Data ingestion (MQTT/HTTP endpoints)
- Kafka message processing
- Stream processing and transformations
- ClickHouse storage and queries
- Redis caching
- MongoDB document storage
- API serving

### Base Infrastructure Costs

Shared infrastructure costs are distributed across active vehicles each collection interval:

| Component | Cloud ($/15min) | On-Prem ($/15min) |
|-----------|-----------------|-------------------|
| Storage, Event Hubs, Defender, monitoring | $10.00 | $0.90 |

### Cost Rates (per hour)

| Resource | Cloud (Azure) | On-Prem |
|----------|---------------|---------|
| CPU/core | $0.30         | $0.02   |
| Memory/GB| $0.08         | $0.005  |

#### Cloud Rates (Fudged Higher)
- Based on Azure D-series VM pricing + 50% managed services overhead
- Includes: AKS compute, managed Kafka (Event Hubs), CosmosDB, Azure Storage, networking, monitoring
- Intentionally conservative (higher) to show true cloud TCO

#### On-Prem Rates (Fudged Lower)
- Based on 3-year hardware amortization only
- Assumes: owned hardware, minimal ops overhead
- Intentionally optimistic (lower) to show on-prem savings
- Does NOT include: datacenter costs, staff, power, cooling, network, maintenance

### Savings Calculation

```
Per-VIN Cost = (CPU_cores × rate + Memory_GB × rate) × hours + (base_infra / active_vins)
Cloud Cost = Per-VIN costs summed across fleet
On-Prem Cost = Same formula with on-prem rates
Savings = Cloud Cost - On-Prem Cost
Savings % = (Savings / Cloud Cost) × 100
```

Expected savings: **~85-88%** with on-prem hosting (hardware costs only).

### Projected Annual Costs (5000 vehicles)

Based on ~$100k/month cloud spend:

| Metric | Cloud | On-Prem |
|--------|-------|---------|
| Monthly Cost | ~$100,000 | ~$9,500 |
| Annual Cost | ~$1,200,000 | ~$114,000 |
| Per Vehicle/Month | ~$20.00 | ~$1.90 |
| Annual Savings | ~$1,086,000 (90%) | - |

## API Endpoints

### GET /cost/vin/{vin}
Cost summary for a specific VIN.

### GET /cost/fleet
Fleet-wide cost summary with top cost VINs.

### GET /cost/summary?period=day|week|month
High-level cost summary for a time period.

### GET /cost/comparison
Cloud vs on-prem cost comparison with projected annual savings.

### GET /cost/report
Plain text report for terminal viewing.

## Accessing the Report

The service is deployed internally on cec-prd-cluster-1 (no public ingress). To view the report:

```bash
# Quick one-liner
kubectl --context cec-prd-cluster-1 run curl-test --image=curlimages/curl --rm -it --restart=Never -- curl -s http://cost.default.svc.cluster.local:8077/cost/report

# Or port-forward and curl locally
kubectl --context cec-prd-cluster-1 port-forward svc/cost 8077:8077 &
curl http://localhost:8077/cost/report
```

## Example Report Output

```
╔══════════════════════════════════════════════════════════════════╗
║                    COST SERVICE REPORT                           ║
╠══════════════════════════════════════════════════════════════════╣
║  Period: 2026-01-01 to 2026-02-01
╠══════════════════════════════════════════════════════════════════╣
║  FLEET OVERVIEW                                                  ║
║  ─────────────────────────────────────────────────────────────── ║
║  Active Vehicles:     383                                         
║  Cloud Cost:          $51.66                                      
║  On-Prem Cost:        $4.74                                      
║  Savings:             $46.93 (90.8%)                             
╠══════════════════════════════════════════════════════════════════╣
║  COST RATES                                                      ║
║  ─────────────────────────────────────────────────────────────── ║
║  Cloud:   CPU $0.30/core-hr   Memory $0.080/GB-hr                 
║  On-Prem: CPU $0.02/core-hr   Memory $0.005/GB-hr                 
║  Base Infra: Cloud $10.00/15min   On-Prem $0.90/15min             
╠══════════════════════════════════════════════════════════════════╣
║  ANNUAL PROJECTION (based on current usage)                      ║
║  ─────────────────────────────────────────────────────────────── ║
║  Cloud Annual:        $619.97                                      
║  On-Prem Annual:      $56.86                                      
║  Annual Savings:      $563.11                                      
╚══════════════════════════════════════════════════════════════════╝

TOP COST VEHICLES:
VIN                       Cloud $    On-Prem $  Savings %
───────────────────    ──────────   ──────────   ────────
VCF1ZBU26PG004962            0.24         0.02      90.6%
VCF1EBU29PG008340            0.24         0.02      90.6%
VCF1ZBU23PG005471            0.24         0.02      90.6%
...
```

*Note: Costs shown are from a short collection period. Numbers accumulate over time as the collector runs every 15 minutes.*

## Configuration

| Env Var | Description | Default |
|---------|-------------|---------|
| CLICKHOUSE_HOST | Local CH for storing cost data | localhost |
| REMOTE_CLICKHOUSE_HOST | Dev cluster CH for VIN activity | - |
| COLLECTOR_INTERVAL_MINUTES | How often to collect metrics | 15 |

## Limitations

- Resource estimates are approximations, not actual measurements
- Cost rates are simplified and don't reflect all real-world factors
- On-prem costs exclude significant operational overhead
- Designed for business case illustration, not precise billing