What monitoring tools or systems have you used or know for production web applications?

The most common methods of monitoring web applications in production include:

• Application Performance Monitoring (APM): Tools that collect metrics on response times, errors, resource usage (CPU, memory), database queries. Examples: New Relic, Dynatrace, AppDynamics, Jaeger (for distributed tracing).
• Log Monitoring: Collecting, aggregating, and analyzing application logs to identify errors, exceptions, and problematic situations. Tools: Elasticsearch, Logstash, Kibana (ELK Stack), Grafana Loki, Splunk.
• Infrastructure Monitoring: Tracking the status of servers, containers, databases, and other infrastructure components on which the application runs. Tools: Prometheus, Nagios, Zabbix, CloudWatch (AWS).
• Uptime Monitoring: Regular checks of web application availability from outside to identify access issues. Tools: Uptime Robot, Pingdom, Datadog Synthetics.
• Real User Monitoring (RUM): Collecting data on how real users interact with the application, including page load times, JavaScript errors, and client-side performance. Examples: Sentry, Google Analytics, FullStory.
• Business Metrics: Tracking key business indicators (KPIs), such as conversion rate, active users, orders, etc., to identify issues affecting business goals.

In practice, a combination of these approaches is often used to ensure comprehensive monitoring. For Python applications, integrations of APM tools with popular frameworks (Django, Flask) and libraries for tracing and metric collection (Opentracing, OpenTelemetry) are especially useful.