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https://github.com/pacnpal/thrilltrack-explorer.git
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e2b0368a62
Add Django Celery tasks and utilities to periodically collect system metrics (error rates, response times, queue sizes) and record them into metric_time_series. Include monitoring app scaffolding, metrics collector, Celery beat schedule, middleware for live metrics, and a Supabase edge function for cross-source metrics.
53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
"""
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Middleware for tracking API response times and error rates.
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"""
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import time
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import logging
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from django.core.cache import cache
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from django.utils.deprecation import MiddlewareMixin
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logger = logging.getLogger(__name__)
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class MetricsMiddleware(MiddlewareMixin):
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"""
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Middleware to track API response times and error rates.
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Stores metrics in cache for periodic collection.
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"""
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def process_request(self, request):
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"""Record request start time."""
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request._metrics_start_time = time.time()
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return None
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def process_response(self, request, response):
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"""Record response time and update metrics."""
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if hasattr(request, '_metrics_start_time'):
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response_time = (time.time() - request._metrics_start_time) * 1000 # Convert to ms
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# Store response time in cache for aggregation
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cache_key = 'metrics:response_times'
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response_times = cache.get(cache_key, [])
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response_times.append(response_time)
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# Keep only last 100 response times
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if len(response_times) > 100:
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response_times = response_times[-100:]
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cache.set(cache_key, response_times, 300) # 5 minute TTL
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# Track cache hits/misses
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if response.status_code == 200:
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cache.incr('metrics:cache_hits', 1)
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return response
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def process_exception(self, request, exception):
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"""Track exceptions and error rates."""
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logger.error(f"Exception in request: {exception}", exc_info=True)
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# Increment error counter
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cache.incr('metrics:cache_misses', 1)
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return None
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