62ffbe499a
Adds new cron jobs and shell scripts for automated ML model training and anomaly detection, along with configurations for logging and system checks. Replit-Commit-Author: Agent Replit-Commit-Session-Id: 7a657272-55ba-4a79-9a2e-f1ed9bc7a528 Replit-Commit-Checkpoint-Type: full_checkpoint Replit-Commit-Event-Id: 534244cd-b293-403e-a6d6-43cd9fbb30fb Replit-Commit-Screenshot-Url: https://storage.googleapis.com/screenshot-production-us-central1/449cf7c4-c97a-45ae-8234-e5c5b8d6a84f/7a657272-55ba-4a79-9a2e-f1ed9bc7a528/1P26v7M
27 lines
830 B
Bash
27 lines
830 B
Bash
#!/bin/bash
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# =========================================================
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# CRON TRAINING - Addestramento automatico modello ML
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# =========================================================
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LOG_FILE="/var/log/ids/training.log"
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mkdir -p /var/log/ids
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echo "=========================================" >> "$LOG_FILE"
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echo "[$(date)] Training automatico avviato" >> "$LOG_FILE"
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echo "=========================================" >> "$LOG_FILE"
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curl -X POST http://localhost:8000/train \
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-H "Content-Type: application/json" \
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-d '{"max_records": 100000, "hours_back": 24}' \
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--max-time 300 >> "$LOG_FILE" 2>&1
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EXIT_CODE=$?
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if [ $EXIT_CODE -eq 0 ]; then
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echo "[$(date)] Training completato con successo" >> "$LOG_FILE"
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else
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echo "[$(date)] Training fallito (exit code: $EXIT_CODE)" >> "$LOG_FILE"
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fi
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echo "" >> "$LOG_FILE"
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