Monitoring

Sentry

Sentry captures errors and exceptions across Django, Celery, and Redis.

Configuration

import sentry_sdk
from sentry_sdk.integrations.logging import LoggingIntegration
from sentry_sdk.integrations.django import DjangoIntegration
from sentry_sdk.integrations.celery import CeleryIntegration
from sentry_sdk.integrations.redis import RedisIntegration

sentry_sdk.init(
    dsn=env("SENTRY_DSN"),
    integrations=[
        LoggingIntegration(
            level=logging.INFO,         # Breadcrumbs from INFO
            event_level=logging.ERROR,  # Events from ERROR
        ),
        DjangoIntegration(),
        CeleryIntegration(),
        RedisIntegration(),
    ],
    environment=env("SENTRY_ENVIRONMENT", default="production"),
    traces_sample_rate=env.float("SENTRY_TRACES_SAMPLE_RATE", default=0.0),
)

Integrations

Integration	What it captures
`DjangoIntegration`	Unhandled exceptions in views, middleware errors
`CeleryIntegration`	Task failures, retries, timeouts
`RedisIntegration`	Redis connection errors
`LoggingIntegration`	Python logging as breadcrumbs (INFO+) and events (ERROR+)

Performance Monitoring

Set SENTRY_TRACES_SAMPLE_RATE to enable transaction tracing:

SENTRY_TRACES_SAMPLE_RATE=0.1  # Sample 10% of requests

Leave at 0.0 in production unless actively debugging performance — tracing adds overhead.

Environment Variables

Variable	Default	Description
`SENTRY_DSN`	—	Sentry project DSN
`DJANGO_SENTRY_LOG_LEVEL`	`INFO`	Minimum log level for breadcrumbs
`SENTRY_ENVIRONMENT`	`production`	Environment tag
`SENTRY_TRACES_SAMPLE_RATE`	`0.0`	Transaction sample rate (0.0 - 1.0)

Flower

Flower provides a real-time web dashboard for Celery monitoring.

What it shows

Active, completed, and failed tasks
Worker status and resource usage
Task execution time and rate
Task details (arguments, result, traceback)
Broker (Redis) connection status

Access

Environment	URL	Auth
Local	`http://localhost:5555`	None
Production	`https://yourdomain.com:5555`	Basic auth

Production Auth

CELERY_FLOWER_USER=admin
CELERY_FLOWER_PASSWORD=your-secure-password

Flower is exposed via Traefik on a separate entrypoint (port 5555).

Logging

Django's logging is configured in base.py. Key loggers:

Logger	Level	Purpose
`django`	`INFO`	Django framework messages
`django.request`	`ERROR`	HTTP 4xx/5xx responses
`backend.documents.tasks`	`INFO`	Document ingestion pipeline
`backend.chat`	`INFO`	Chat/agent operations
`celery`	`INFO`	Task execution lifecycle

In production, Sentry captures all ERROR-level log entries as events and INFO-level entries as breadcrumbs for context.

Health Checks

Application

# Django system check
docker compose exec django python manage.py check

# Database connectivity
docker compose exec django python manage.py check --database default

# API responding
curl -s http://localhost:8000/api/schema/ | head -1

Celery

# Ping workers
docker compose exec django celery -A config.celery_app inspect ping

# Check active tasks
docker compose exec django celery -A config.celery_app inspect active

# Check scheduled tasks
docker compose exec django celery -A config.celery_app inspect scheduled

Database

# PostgreSQL shell
docker compose exec postgres psql -U $POSTGRES_USER -d $POSTGRES_DB

# Check pgvector extension
SELECT * FROM pg_extension WHERE extname = 'vector';

# Check table sizes
SELECT relname, pg_size_pretty(pg_total_relation_size(relid))
FROM pg_stat_user_tables ORDER BY pg_total_relation_size(relid) DESC;

Redis

# Redis CLI
docker compose exec redis redis-cli

# Check memory usage
redis-cli INFO memory

# Check connected clients
redis-cli INFO clients

On this page