3dccf80a72
- Estimates cloud vs on-prem costs per active vehicle - Queries feature_table_last_shard from ClickHouse (lightweight) - 85% savings estimate with on-prem (hardware only) - Deployed to cec-prd-cluster-1 (internal only) - Text report endpoint at /cost/report
143 lines
6.7 KiB
Markdown
143 lines
6.7 KiB
Markdown
# Cost Service
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Per-vehicle cost estimation service for capacity planning and cloud vs on-prem comparison.
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## Overview
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This service estimates the cost of running cloud services per VIN by:
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1. Querying vehicle activity from ClickHouse (message counts)
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2. Estimating resource usage based on activity level
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3. Applying cost rates for cloud vs on-prem hosting
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4. Storing aggregated cost data for reporting
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## Cost Estimation Methodology
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### Resource Estimates Per Active VIN
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| Activity Level | Messages/15min | CPU (cores) | Memory (GB) |
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|---------------|----------------|-------------|-------------|
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| Low | < 100 | 0.15 | 0.25 |
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| Medium | 100-1000 | 0.225 | 0.375 |
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| High | > 1000 | 0.30 | 0.50 |
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These estimates account for the full data pipeline per vehicle:
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- Data ingestion (MQTT/HTTP endpoints)
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- Kafka message processing
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- Stream processing and transformations
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- ClickHouse storage and queries
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- Redis caching
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- MongoDB document storage
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- API serving
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### Cost Rates (per hour)
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| Resource | Cloud (Azure) | On-Prem |
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|----------|---------------|---------|
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| CPU/core | $0.12 | $0.015 |
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| Memory/GB| $0.025 | $0.003 |
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#### Cloud Rates (Fudged Higher)
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- Based on Azure D-series VM pricing + 50% managed services overhead
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- Includes: AKS compute, managed Kafka (Event Hubs), CosmosDB, Azure Storage, networking, monitoring
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- Intentionally conservative (higher) to show true cloud TCO
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#### On-Prem Rates (Fudged Lower)
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- Based on 3-year hardware amortization only
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- Assumes: owned hardware, minimal ops overhead
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- Intentionally optimistic (lower) to show on-prem savings
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- Does NOT include: datacenter costs, staff, power, cooling, network, maintenance
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### Savings Calculation
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```
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Cloud Cost = (CPU_cores × $0.12 + Memory_GB × $0.025) × hours
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On-Prem Cost = (CPU_cores × $0.015 + Memory_GB × $0.003) × hours
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Savings = Cloud Cost - On-Prem Cost
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Savings % = (Savings / Cloud Cost) × 100
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```
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Expected savings: **~85-88%** with on-prem hosting (hardware costs only).
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## API Endpoints
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### GET /cost/vin/{vin}
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Cost summary for a specific VIN.
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### GET /cost/fleet
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Fleet-wide cost summary with top cost VINs.
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### GET /cost/summary?period=day|week|month
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High-level cost summary for a time period.
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### GET /cost/comparison
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Cloud vs on-prem cost comparison with projected annual savings.
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### GET /cost/report
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Plain text report for terminal viewing.
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## Accessing the Report
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The service is deployed internally on cec-prd-cluster-1 (no public ingress). To view the report:
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```bash
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# Quick one-liner
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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
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# Or port-forward and curl locally
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kubectl --context cec-prd-cluster-1 port-forward svc/cost 8077:8077 &
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curl http://localhost:8077/cost/report
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```
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## Example Report Output
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```
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╔══════════════════════════════════════════════════════════════════╗
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║ COST SERVICE REPORT ║
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╠══════════════════════════════════════════════════════════════════╣
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║ Period: 2026-01-01 to 2026-02-01
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╠══════════════════════════════════════════════════════════════════╣
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║ FLEET OVERVIEW ║
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║ ─────────────────────────────────────────────────────────────── ║
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║ Active Vehicles: 81
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║ Cloud Cost: $0.58
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║ On-Prem Cost: $0.09
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║ Savings: $0.50 (85.2%)
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╠══════════════════════════════════════════════════════════════════╣
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║ COST RATES ║
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║ ─────────────────────────────────────────────────────────────── ║
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║ Cloud: CPU $0.120/core-hr Memory $0.0250/GB-hr
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║ On-Prem: CPU $0.015/core-hr Memory $0.0030/GB-hr
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╠══════════════════════════════════════════════════════════════════╣
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║ ANNUAL PROJECTION (based on current usage) ║
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║ ─────────────────────────────────────────────────────────────── ║
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║ Cloud Annual: $6.99
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║ On-Prem Annual: $1.04
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║ Annual Savings: $5.96
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╚══════════════════════════════════════════════════════════════════╝
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TOP COST VEHICLES:
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VIN Cloud $ On-Prem $ Savings %
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─────────────────── ────────── ────────── ────────
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VCF1EBU20PG009666 0.01 0.00 85.2%
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VCF1EBU29PG011061 0.01 0.00 85.2%
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VCF1UBU20PG006530 0.01 0.00 85.2%
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...
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```
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*Note: Costs shown are from a short collection period. Numbers accumulate over time as the collector runs every 15 minutes.*
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## Configuration
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| Env Var | Description | Default |
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|---------|-------------|---------|
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| CLICKHOUSE_HOST | Local CH for storing cost data | localhost |
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| REMOTE_CLICKHOUSE_HOST | Dev cluster CH for VIN activity | - |
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| COLLECTOR_INTERVAL_MINUTES | How often to collect metrics | 15 |
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## Limitations
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- Resource estimates are approximations, not actual measurements
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- Cost rates are simplified and don't reflect all real-world factors
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- On-prem costs exclude significant operational overhead
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- Designed for business case illustration, not precise billing
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