This commit introduces major performance improvements and migrates from custom job scheduling to Celery Beat for better reliability and scalability. ### 🚀 Performance Optimizations **CVE2CAPEC Client Performance (Fixed startup blocking)** - Implement lazy loading with 24-hour cache for CVE2CAPEC mappings - Add background task for CVE2CAPEC sync (data_sync_tasks.sync_cve2capec) - Remove blocking data fetch during client initialization - API endpoint: POST /api/sync-cve2capec **ExploitDB Client Performance (Fixed webapp request blocking)** - Implement global file index cache to prevent rebuilding on every request - Add lazy loading with 24-hour cache expiry for 46K+ exploit index - Background task for index building (data_sync_tasks.build_exploitdb_index) - API endpoint: POST /api/build-exploitdb-index ### 🔄 Celery Migration & Scheduling **Celery Beat Integration** - Migrate from custom job scheduler to Celery Beat for reliability - Remove 'finetuned' LLM provider (logic moved to ollama container) - Optimized daily workflow with proper timing and dependencies **New Celery Tasks Structure** - tasks/bulk_tasks.py - NVD bulk processing and SIGMA generation - tasks/data_sync_tasks.py - All data synchronization tasks - tasks/maintenance_tasks.py - System maintenance and cleanup - tasks/sigma_tasks.py - SIGMA rule generation tasks **Daily Schedule (Optimized)** ``` 1:00 AM → Weekly cleanup (Sundays) 1:30 AM → Daily result cleanup 2:00 AM → NVD incremental update 3:00 AM → CISA KEV sync 3:15 AM → Nomi-sec PoC sync 3:30 AM → GitHub PoC sync 3:45 AM → ExploitDB sync 4:00 AM → CVE2CAPEC MITRE ATT&CK sync 4:15 AM → ExploitDB index rebuild 5:00 AM → Reference content sync 8:00 AM → SIGMA rule generation 9:00 AM → LLM-enhanced SIGMA generation Every 15min → Health checks ``` ### 🐳 Docker & Infrastructure **Enhanced Docker Setup** - Ollama setup with integrated SIGMA model creation (setup_ollama_with_sigma.py) - Initial database population check and trigger (initial_setup.py) - Proper service dependencies and health checks - Remove manual post-rebuild script requirements **Service Architecture** - Celery worker with 4-queue system (default, bulk_processing, sigma_generation, data_sync) - Flower monitoring dashboard (localhost:5555) - Redis as message broker and result backend ### 🎯 API Improvements **Background Task Endpoints** - GitHub PoC sync now uses Celery (was blocking backend) - All sync operations return task IDs and monitoring URLs - Consistent error handling and progress tracking **New Endpoints** - POST /api/sync-cve2capec - CVE2CAPEC mapping sync - POST /api/build-exploitdb-index - ExploitDB index rebuild ### 📁 Cleanup **Removed Files** - fix_sigma_model.sh (replaced by setup_ollama_with_sigma.py) - Various test_* and debug_* files no longer needed - Old training scripts related to removed 'finetuned' provider - Utility scripts replaced by Docker services ### 🔧 Configuration **Key Files Added/Modified** - backend/celery_config.py - Complete Celery configuration - backend/initial_setup.py - First-boot database population - backend/setup_ollama_with_sigma.py - Integrated Ollama setup - CLAUDE.md - Project documentation and development guide 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
437 lines
No EOL
15 KiB
Python
437 lines
No EOL
15 KiB
Python
"""
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Maintenance tasks for Celery
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"""
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import logging
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from datetime import datetime, timedelta
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from typing import Dict, Any
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from celery_config import celery_app, get_db_session
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logger = logging.getLogger(__name__)
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@celery_app.task(name='tasks.maintenance_tasks.cleanup_old_results')
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def cleanup_old_results():
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"""
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Periodic task to clean up old Celery results and logs
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"""
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try:
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logger.info("Starting cleanup of old Celery results")
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# This would clean up old results from Redis
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# For now, we'll just log the action
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cutoff_date = datetime.utcnow() - timedelta(days=7)
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# Clean up old task results (this would be Redis cleanup)
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# celery_app.backend.cleanup()
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logger.info(f"Cleanup completed for results older than {cutoff_date}")
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return {
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'status': 'completed',
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'cutoff_date': cutoff_date.isoformat(),
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'message': 'Old results cleanup completed'
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}
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except Exception as e:
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logger.error(f"Cleanup task failed: {e}")
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raise
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@celery_app.task(name='tasks.maintenance_tasks.health_check')
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def health_check():
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"""
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Health check task to verify system components
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"""
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try:
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db_session = get_db_session()
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# Check database connectivity
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try:
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db_session.execute("SELECT 1")
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db_status = "healthy"
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except Exception as e:
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db_status = f"unhealthy: {e}"
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finally:
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db_session.close()
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# Check Redis connectivity
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try:
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celery_app.backend.ping()
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redis_status = "healthy"
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except Exception as e:
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redis_status = f"unhealthy: {e}"
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result = {
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'timestamp': datetime.utcnow().isoformat(),
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'database': db_status,
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'redis': redis_status,
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'celery': 'healthy'
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}
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logger.info(f"Health check completed: {result}")
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return result
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except Exception as e:
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logger.error(f"Health check failed: {e}")
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raise
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@celery_app.task(bind=True, name='tasks.maintenance_tasks.database_cleanup_comprehensive')
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def database_cleanup_comprehensive(self, days_to_keep: int = 30, cleanup_failed_jobs: bool = True,
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cleanup_logs: bool = True) -> Dict[str, Any]:
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"""
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Comprehensive database cleanup task
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Args:
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days_to_keep: Number of days to keep old records
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cleanup_failed_jobs: Whether to clean up failed job records
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cleanup_logs: Whether to clean up old log entries
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Returns:
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Dictionary containing cleanup results
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"""
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try:
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from datetime import datetime, timedelta
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from typing import Dict, Any
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db_session = get_db_session()
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# Update task progress
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'database_cleanup',
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'progress': 0,
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'message': 'Starting comprehensive database cleanup'
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}
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)
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logger.info(f"Starting comprehensive database cleanup - keeping {days_to_keep} days")
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cutoff_date = datetime.utcnow() - timedelta(days=days_to_keep)
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cleanup_results = {
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'cutoff_date': cutoff_date.isoformat(),
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'cleaned_tables': {},
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'total_records_cleaned': 0
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}
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try:
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# Import models here to avoid circular imports
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import sys
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import os
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from main import BulkProcessingJob
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# Clean up old bulk processing jobs
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'database_cleanup',
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'progress': 20,
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'message': 'Cleaning up old bulk processing jobs'
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}
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)
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old_jobs_query = db_session.query(BulkProcessingJob).filter(
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BulkProcessingJob.created_at < cutoff_date
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)
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if cleanup_failed_jobs:
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# Clean all old jobs
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old_jobs_count = old_jobs_query.count()
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old_jobs_query.delete()
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else:
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# Only clean completed jobs
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old_jobs_query = old_jobs_query.filter(
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BulkProcessingJob.status.in_(['completed', 'cancelled'])
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)
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old_jobs_count = old_jobs_query.count()
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old_jobs_query.delete()
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cleanup_results['cleaned_tables']['bulk_processing_jobs'] = old_jobs_count
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cleanup_results['total_records_cleaned'] += old_jobs_count
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# Clean up old Celery task results from Redis
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'database_cleanup',
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'progress': 40,
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'message': 'Cleaning up old Celery task results'
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}
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)
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try:
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# This would clean up old results from Redis backend
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# For now, we'll simulate this
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celery_cleanup_count = 0
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# celery_app.backend.cleanup()
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cleanup_results['cleaned_tables']['celery_results'] = celery_cleanup_count
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except Exception as e:
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logger.warning(f"Could not clean Celery results: {e}")
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cleanup_results['cleaned_tables']['celery_results'] = 0
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# Clean up old temporary data (if any)
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'database_cleanup',
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'progress': 60,
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'message': 'Cleaning up temporary data'
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}
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)
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# Add any custom temporary table cleanup here
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# Example: Clean up old session data, temporary files, etc.
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temp_cleanup_count = 0
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cleanup_results['cleaned_tables']['temporary_data'] = temp_cleanup_count
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# Vacuum/optimize database (PostgreSQL)
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'database_cleanup',
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'progress': 80,
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'message': 'Optimizing database'
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}
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)
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try:
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# Run VACUUM on PostgreSQL to reclaim space
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db_session.execute("VACUUM;")
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cleanup_results['database_optimized'] = True
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except Exception as e:
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logger.warning(f"Could not vacuum database: {e}")
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cleanup_results['database_optimized'] = False
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# Commit all changes
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db_session.commit()
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# Update final progress
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self.update_state(
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state='SUCCESS',
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meta={
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'stage': 'completed',
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'progress': 100,
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'message': f'Database cleanup completed - removed {cleanup_results["total_records_cleaned"]} records',
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'results': cleanup_results
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}
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)
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logger.info(f"Database cleanup completed: {cleanup_results}")
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return cleanup_results
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finally:
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db_session.close()
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except Exception as e:
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logger.error(f"Database cleanup failed: {e}")
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self.update_state(
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state='FAILURE',
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meta={
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'stage': 'error',
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'progress': 0,
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'message': f'Cleanup failed: {str(e)}',
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'error': str(e)
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}
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)
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raise
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@celery_app.task(bind=True, name='tasks.maintenance_tasks.health_check_detailed')
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def health_check_detailed(self) -> Dict[str, Any]:
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"""
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Detailed health check task for all system components
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Returns:
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Dictionary containing detailed health status
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"""
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try:
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from datetime import datetime
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import psutil
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import redis
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# Update task progress
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'health_check',
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'progress': 0,
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'message': 'Starting detailed health check'
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}
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)
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logger.info("Starting detailed health check")
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health_status = {
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'timestamp': datetime.utcnow().isoformat(),
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'overall_status': 'healthy',
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'components': {}
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}
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# Check database connectivity and performance
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'health_check',
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'progress': 20,
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'message': 'Checking database health'
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}
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)
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db_session = get_db_session()
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try:
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start_time = datetime.utcnow()
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db_session.execute("SELECT 1")
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db_response_time = (datetime.utcnow() - start_time).total_seconds()
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# Check database size and connections
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db_size_result = db_session.execute("SELECT pg_size_pretty(pg_database_size(current_database()));").fetchone()
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db_connections_result = db_session.execute("SELECT count(*) FROM pg_stat_activity;").fetchone()
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health_status['components']['database'] = {
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'status': 'healthy',
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'response_time_seconds': db_response_time,
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'database_size': db_size_result[0] if db_size_result else 'unknown',
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'active_connections': db_connections_result[0] if db_connections_result else 0,
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'details': 'Database responsive and accessible'
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}
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except Exception as e:
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health_status['components']['database'] = {
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'status': 'unhealthy',
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'error': str(e),
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'details': 'Database connection failed'
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}
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health_status['overall_status'] = 'degraded'
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finally:
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db_session.close()
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# Check Redis connectivity and performance
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'health_check',
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'progress': 40,
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'message': 'Checking Redis health'
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}
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)
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try:
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start_time = datetime.utcnow()
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celery_app.backend.ping()
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redis_response_time = (datetime.utcnow() - start_time).total_seconds()
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# Get Redis info
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redis_client = redis.Redis.from_url(celery_app.conf.broker_url)
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redis_info = redis_client.info()
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health_status['components']['redis'] = {
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'status': 'healthy',
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'response_time_seconds': redis_response_time,
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'memory_usage_mb': redis_info.get('used_memory', 0) / (1024 * 1024),
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'connected_clients': redis_info.get('connected_clients', 0),
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'uptime_seconds': redis_info.get('uptime_in_seconds', 0),
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'details': 'Redis responsive and accessible'
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}
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except Exception as e:
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health_status['components']['redis'] = {
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'status': 'unhealthy',
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'error': str(e),
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'details': 'Redis connection failed'
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}
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health_status['overall_status'] = 'degraded'
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# Check system resources
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'health_check',
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'progress': 60,
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'message': 'Checking system resources'
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}
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)
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try:
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cpu_percent = psutil.cpu_percent(interval=1)
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memory = psutil.virtual_memory()
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disk = psutil.disk_usage('/')
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health_status['components']['system'] = {
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'status': 'healthy',
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'cpu_percent': cpu_percent,
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'memory_percent': memory.percent,
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'memory_available_gb': memory.available / (1024**3),
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'disk_percent': disk.percent,
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'disk_free_gb': disk.free / (1024**3),
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'details': 'System resources within normal ranges'
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}
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# Mark as degraded if resources are high
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if cpu_percent > 80 or memory.percent > 85 or disk.percent > 90:
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health_status['components']['system']['status'] = 'degraded'
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health_status['overall_status'] = 'degraded'
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health_status['components']['system']['details'] = 'High resource usage detected'
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except Exception as e:
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health_status['components']['system'] = {
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'status': 'unknown',
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'error': str(e),
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'details': 'Could not check system resources'
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}
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# Check Celery worker status
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self.update_state(
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state='PROGRESS',
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meta={
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'stage': 'health_check',
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'progress': 80,
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'message': 'Checking Celery workers'
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}
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)
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try:
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inspect = celery_app.control.inspect()
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active_workers = inspect.active()
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stats = inspect.stats()
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health_status['components']['celery'] = {
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'status': 'healthy',
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'active_workers': len(active_workers) if active_workers else 0,
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'worker_stats': stats,
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'details': 'Celery workers responding'
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}
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if not active_workers:
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health_status['components']['celery']['status'] = 'degraded'
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health_status['components']['celery']['details'] = 'No active workers found'
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health_status['overall_status'] = 'degraded'
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except Exception as e:
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health_status['components']['celery'] = {
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'status': 'unknown',
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'error': str(e),
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'details': 'Could not check Celery workers'
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}
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# Update final progress
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self.update_state(
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state='SUCCESS',
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meta={
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'stage': 'completed',
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'progress': 100,
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'message': f'Health check completed - overall status: {health_status["overall_status"]}',
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'results': health_status
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}
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)
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logger.info(f"Detailed health check completed: {health_status['overall_status']}")
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return health_status
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except Exception as e:
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logger.error(f"Detailed health check failed: {e}")
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self.update_state(
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state='FAILURE',
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meta={
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'stage': 'error',
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'progress': 0,
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'message': f'Health check failed: {str(e)}',
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'error': str(e)
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}
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)
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raise |