Logit.io
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Django Logging

Use Logit.io to easily manage Django logs and react promptly to error alerts.

log management
FilebeatLogstashFluentdSyslogWinlogbeat
Ship
Parse
Index
Search
Alert
Live log stream
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
+ 12.4k events/s ingested
! 3 severity alerts fired
+ OpenSearch query 37ms

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Efficient and reliable logging is the first step towards obtaining visibility into the inner workings of your applications and infrastructure.

Django is one of the leading web application frameworks for Python, however, manually managing and analyzing massive Django log files isn't realistic as this can be excessively time-consuming and hard to scale alongside the rest of your organisation's operations.

Real-Time Performance Monitoring

Django logging with Logit.io provides full visibility into your applications and infrastructure. Simplified real-time monitoring ensures you stay on top of performance stats, error rate, latency, and swift insights to enable your team to make the right decision during a limited window of time.

Conduct faster root-cause analysis and trace Django performance issues to the exact code line. Intercept errors and prevent spikes in data and costly downtime. Optimise performance, deliver noteworthy customer experiences, and reduce the average time to repair using a single centralised logging tool.

Easily collect all Django logs using Syslog as soon as they're generated into the Logit.io cloud-native logging platform. Our platform provides your data with a single location to eliminate the risk of losing critical data due to the pitfalls of logging across distributed systems.

FilebeatLogstashFluentdSyslogWinlogbeat
Ship
Parse
Index
Search
Alert
Live log stream
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
+ 12.4k events/s ingested
! 3 severity alerts fired
+ OpenSearch query 37ms

Logging as a Service (LaaS) with Django

Logging as a Service is a cloud-based model for managing log files coming from various endpoints such as applications, servers, devices, and users. LaaS allows you to monitor the changes, security audits, and any other reports from a single platform built upon the best features available from the Elastic Stack, Grafana & OpenSearch.

With all data being monitored in a centralised and compliant system, your engineering team can save time and energy that would otherwise go into manually tracing and monitoring each application, server, and device.

Django data forwarded into our LaaS platform gets processed, parsed, and enriched to allow for accurate log monitoring and alert configuration. Additionally, Logit.io's LaaS can streamline the process of visualizing Django log files.

With Logit.io, you can choose where to store your Django log files in the US, the UK or our other various data centres within the EU.

shell
$
logit metrics scrape --target=k8s --interval=30s
→ Prometheus · Grafana dashboards synced

Django Logs Management

As Django log files are tricky to handle if you proceed to manage these log files without a log management tool, you'll risk finding yourself overwhelmed with an excessive amount of data and could easily risk missing critical alerts.

Logit.io offers complete log and metrics management which offers an intuitive web interface to receive and manage log files. Our platform works in tandem with Python's built-in module for system logging and improves on it by forwarding logs for processing via hosted Logstash pipelines.

This ensures Django log files are collected as soon as they're generated. You'll also have full flexibility to isolate and manage file sources individually and control the overall access policies using advanced role-based access controls.

FilebeatLogstashFluentdSyslogWinlogbeat
Ship
Parse
Index
Search
Alert
Live log stream
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
+ 12.4k events/s ingested
! 3 severity alerts fired
+ OpenSearch query 37ms

Data Visualisation and Dashboards

A customisable dashboard and accurate data visualisation are two of the cornerstones of effective Django framework reporting. At Logit.io, our powerful Hosted Elasticsearch engine allows you to analyse and centralise millions of log instances. Furthermore, our platform provides a complete and reliable reporting solution that offers both preconfigured and custom dashboards.

Our data visualisation tools are backed by Kibana, Grafana & OpenSearch Dashboards to help you create interactive and shareable results using charts ideal for reporting on Django log activity.

Both dashboard and individual reports can be shared and synced with your team with a single click. Not only is this useful for presentations and sharing key insights, but this also proves vital for timely troubleshooting.

alerts
1
Detect
2
Enrich
3
Route
4
Notify
! anomaly detected · checkout p95 > 500ms
→ context attached · service map · recent deploy
→ routed to #incidents · ack in 12s

Notifications and Alerts

With Logit.io, configure managed Alerting so you are notified of critical errors in Django and Python logs, or when server metrics cross thresholds. Choose from 40+ destinations including Email, Slack, webhooks, PagerDuty, and Opsgenie.

Alert criteria can match any pattern, blacklists, whitelists, field value changes, or spikes/flatlines in regular activity — and work with industry-leading reporting and ticketing systems.

FilebeatLogstashFluentdSyslogWinlogbeat
Ship
Parse
Index
Search
Alert
Live log stream
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
--:--:-- INFO request.completed duration_ms=42 route="/api/v1/orders"
--:--:-- WARN latency.spike service=checkout p95=820ms threshold=500ms
--:--:-- INFO trace.exported spans=128 backend=jaeger status="ok"
--:--:-- INFO metric.scrape target=prometheus job=k8s-pods samples=8421
--:--:-- INFO log.shipped bytes=184032 index=logs-prod
--:--:-- WARN auth.failure ip=203.0.113.42 attempts=3 action=rate_limit
--:--:-- INFO alert.routed severity=high channel="#incidents" dedupe=on
--:--:-- INFO dashboard.refresh uid=ops-overview panels=14 cache=hit
--:--:-- ERROR disk.pressure node=worker-3 usage=92% reclaim=started
--:--:-- INFO pipeline.batch size=2048 lag_ms=18 status=healthy
--:--:-- WARN queue.backpressure topic=ingest depth=1200
--:--:-- INFO otel.export endpoint=collector.svc spans_ok=512
--:--:-- INFO search.query hits=1284 took_ms=37 index=logs-*
--:--:-- INFO retention.policy applied hot=14d warm=30d
--:--:-- WARN tls.cert.expiring host=ingest.logit.io days=12
--:--:-- INFO ha.failover check region=eu-west status=ready
+ 12.4k events/s ingested
! 3 severity alerts fired
+ OpenSearch query 37ms

Companies Feel The Difference When They Use Logit.io

Internally, Logit.io has made it easier for us to provide better support for our customers, since finding individual messages based on various data in the payload has become easier.

At Youredi, pretty much everyone from our technical support teams through to our professional services teams uses Logit.io.

Youredi

Mats von Weissenberg

CTO @ Youredi

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