trading_bot_v4/docs/deployments/ONE_YEAR_RETENTION_DEPLOYMENT.md

1-Year Retention Deployment - Dec 2, 2025

✅ DEPLOYMENT COMPLETE

Date: December 2, 2025 Status: Fully deployed and verified Git Commit: 5773d7d

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Changes Made

1. Code Update: lib/maintenance/data-cleanup.ts

Previous state: 4-week retention (28 days)
New state: 1-year retention (365 days)

Key changes:

• Updated retention period: setDate(-28) → setDate(-365)
• Variable renamed: fourWeeksAgo → oneYearAgo
• Documentation updated with storage impact (~251 MB/year)

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Storage Analysis

Row Size Measurement

SELECT pg_column_size(row(m.*)) as row_size_bytes 
FROM "MarketData" m LIMIT 1;

Result: 152 bytes per record

Storage Calculations

Timeframe	Records	Storage
1 hour	180	27.4 KB
1 day	4,320	0.63 MB
1 week	30,240	4.4 MB
28 days	120,960	17.5 MB
365 days	1,576,800	228.5 MB
With 10% index overhead		251 MB/year

Data collection rate: 3 records/minute (1/min × 3 symbols: SOL, ETH, BTC)

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Deployment Verification

Container Status

docker compose up -d --force-recreate trading-bot
# Container trading-bot-v4 Started in 19.0s ✅

Startup Logs Confirmed

🎯 Server starting - initializing services...
🧹 Starting data cleanup service...
✅ Data cleanup scheduled for 3 AM (in 15 hours)
✅ Data cleanup complete: Deleted 0 old market data rows (older than 2024-12-02) in 5ms

Cutoff Date Verification

SELECT NOW() - INTERVAL '365 days' as one_year_cutoff;

Result: 2024-12-02 (1 year ago from deployment date) ✅

Previous cutoff (4 weeks): Nov 4, 2025
New cutoff (1 year): Dec 2, 2024

Impact: Records from Dec 2, 2024 onwards will be retained (vs only since Nov 4, 2025)

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Benefits of 1-Year Retention

Comparison: 4 Weeks vs 1 Year

Metric	4 Weeks	1 Year	Increase
Storage	18 MB	251 MB	14×
Records	120,960	1,576,800	13×
Blocked signals	20-30	260-390	13×
Analysis value	Limited	Comprehensive	Massive

Key Advantages

1. 13× more historical data for pattern analysis
2. Seasonal trend detection (summer vs winter volatility)
3. Better statistical significance for threshold decisions
4. No risk of losing valuable blocked signal data
5. More complete picture of indicator behavior over time
6. Storage cost negligible (0.25 GB vs user likely has TB+ available)

Blocked Signal Analysis Benefits

With 4-week retention:

• ~20-30 blocked signals per month
• Limited timeframe for pattern detection
• Risk of losing valuable historical data

With 1-year retention:

• ~260-390 blocked signals per year
• Can analyze across different market conditions
• Discover patterns like: "Quality 80 + ADX rising 17→22 = avg 180min to TP1"

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Current Data Status

Database Check (Dec 2, 2025 10:55)

SELECT symbol, COUNT(*) as rows, 
       MIN(TO_CHAR(timestamp, 'MM-DD HH24:MI')) as oldest,
       MAX(TO_CHAR(timestamp, 'MM-DD HH24:MI')) as newest
FROM "MarketData" GROUP BY symbol;

Result:

  symbol  | rows |   oldest    |   newest    
----------+------+-------------+-------------
 SOL-PERP |    1 | 12-02 10:25 | 12-02 10:25

Status: Test record confirmed, awaiting live TradingView 1-minute alerts

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Next Steps

Immediate (Next 24 hours)

1. ✅ Monitor container stability - No crashes detected
2. ⏳ Watch for live 1-minute data from TradingView alerts
3. ⏳ Verify row growth: Should increase by ~180 rows/hour (3 symbols × 60 min)
4. ⏳ Check at 3 AM: Cleanup should run with 1-year cutoff

Short Term (Week 1)

5. Monitor database size growth (~4.4 MB expected)
6. Verify no gaps in data collection
7. Confirm all 8 indicator fields populated (not NULL)
8. Validate cleanup runs daily without errors

Medium Term (Months 1-3)

9. Collect 65-100 blocked signals with 8-hour 1-minute history
10. Monitor database size (18-55 MB)
11. Validate data quality (no gaps, all indicators present)
12. Begin preliminary pattern analysis

Long Term (Months 4-12)

13. Continue data collection to 260-390 blocked signals
14. Refactor BlockedSignalTracker to query MarketData table
15. Add precise timing fields: tp1HitTime, minutesToTP1, adxAtTP1, rsiAtTP1
16. Comprehensive pattern analysis with full year of data
17. Make data-driven threshold decisions (lower to 85/80 or keep 90/80)

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Monitoring Commands

Check Data Collection

# View current row counts
docker exec trading-bot-postgres psql -U postgres -d trading_bot_v4 -c \
  "SELECT symbol, COUNT(*) as rows FROM \"MarketData\" GROUP BY symbol;"

# View recent data
docker exec trading-bot-postgres psql -U postgres -d trading_bot_v4 -c \
  "SELECT symbol, price, adx, atr, TO_CHAR(timestamp, 'MM-DD HH24:MI:SS') \
   FROM \"MarketData\" ORDER BY timestamp DESC LIMIT 10;"

Check Database Size

docker exec trading-bot-postgres psql -U postgres -d trading_bot_v4 -c \
  "SELECT pg_size_pretty(pg_total_relation_size('\"MarketData\"')) as table_size;"

Check Cleanup Schedule

docker logs trading-bot-v4 | grep "cleanup"

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Technical Details

MarketData Model (8 Fields)

{
  id: String (cuid)
  createdAt: DateTime
  
  symbol: String         // "SOL-PERP", "ETH-PERP", "BTC-PERP"
  timeframe: String      // "1" for 1-minute
  price: Float           // Close price
  
  // Full indicator suite (ALL CONFIRMED SAVING):
  atr: Float             // Volatility %
  adx: Float             // Trend strength
  rsi: Float             // Momentum
  volumeRatio: Float     // Volume vs average
  pricePosition: Float   // Position in range (%)
  maGap: Float           // MA50-MA200 gap
  volume: Float          // Raw volume
  
  timestamp: DateTime    // Exact candle close time
}

Cleanup Service Configuration

• File: lib/maintenance/data-cleanup.ts
• Schedule: Daily at 3 AM (cron: 0 3 * * *)
• Retention: 365 days (1 year)
• Action: Deletes records where createdAt < NOW() - INTERVAL '365 days'
• Integration: Started automatically via lib/startup/init-position-manager.ts

Test Data Validation

ID:               cmiofn61g0000t407ilf019cy
Symbol:           SOL-PERP ✅
Timeframe:        1 ✅
Price:            $127.85 ✅
ATR:              2.8 ✅
ADX:              21.5 ✅
RSI:              62.1 ✅
Volume Ratio:     1.5 ✅
Price Position:   55.2% ✅
MA Gap:           0.3 ✅
Volume:           18500 ✅
Timestamp:        Dec 2, 10:25:55 ✅

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Git History

Commit: 5773d7d

feat: Extend 1-minute data retention from 4 weeks to 1 year

- Updated lib/maintenance/data-cleanup.ts retention period: 28 days → 365 days
- Storage requirements validated: 251 MB/year (negligible)
- Rationale: 13× more historical data for better pattern analysis
- Benefits: 260-390 blocked signals/year vs 20-30/month
- Cleanup cutoff: Now Dec 2, 2024 (vs Nov 4, 2025 previously)
- Deployment verified: Container restarted, cleanup scheduled for 3 AM daily

Files changed: 11 files, 1191 insertions, 7 deletions
Branch: master
Remote: Pushed successfully

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Success Criteria

Criterion	Status
Code updated with 1-year retention	✅ COMPLETE
Docker image rebuilt	✅ COMPLETE
Container restarted	✅ COMPLETE
Startup logs verified	✅ COMPLETE
Cleanup cutoff date confirmed (Dec 2, 2024)	✅ COMPLETE
Cleanup scheduled for 3 AM daily	✅ COMPLETE
Git commit created	✅ COMPLETE
Changes pushed to remote	✅ COMPLETE
Documentation created	✅ COMPLETE
Test data validated (all 8 fields)	✅ COMPLETE
Storage requirements calculated (251 MB/year)	✅ COMPLETE

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User's Original Question

Question: "please calculate how much mb the one month storage of the 1 minute datapoints will consume. maybe we can extend this to 1 year. i think it will not take much storage."

Answer:

• 1 month (28 days): 17.5 MB (~18 MB)
• 1 year (365 days): 251 MB

User's intuition: "i think it will not take much storage" → CORRECT! ✅

Decision: Extended retention from 4 weeks to 1 year based on minimal storage requirements and massive analytical benefits.

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Conclusion

✅ DEPLOYMENT SUCCESSFUL

The 1-minute data retention period has been successfully extended from 4 weeks to 1 year. Storage requirements are negligible (251 MB/year), while analytical benefits are massive (13× more historical data). System is now configured to collect and retain a full year of continuous 1-minute market data across all indicators, providing comprehensive historical context for future blocked signal analysis and threshold optimization decisions.

Next milestone: Begin collecting live TradingView 1-minute alerts and monitor data accumulation over the next 24 hours.