How We Do Observability and Analytics at Gridlines

Like many software startups, we've been evolving our observability stack as we grow. While our setup isn't unique, we wanted to share our thought process and experiences in case it helps others making similar decisions.

At Gridlines, we recently made a strategic shift from Sentry + PostHog to Datadog + PostHog. While this meant some upfront migration work, we believed the improved developer experience of having most of our observability tools in one place would be worth it. This transition has significantly improved our ability to monitor, analyze, and respond to our application's performance and user behavior. Here's a deep dive into our current setup and the reasoning behind our choices.

Analytics with PostHog

PostHog has been instrumental in providing us with comprehensive analytics insights. We leverage it for:

• Daily reporting of high-level metrics including user logins, sign-ups, and other key performance indicators

• Real-time analytics events pushed to Slack through their data pipeline feature, enabling immediate visibility into important user actions

• Product analytics that help us make data-driven decisions about feature development and improvements

Application Performance Management (APM)

Our APM setup, powered by Datadog, gives us deep visibility into our application's performance. We use dd-trace with our FastAPI backend to:

• Track API response times with granular detail

• Identify recurring performance bottlenecks

• Pinpoint opportunities for optimization

• Monitor system resources and infrastructure health

Real User Monitoring (RUM)

Real User Monitoring (RUM) is a crucial component of our frontend observability strategy. Using Datadog's RUM library, we capture detailed data about our users' actual experience:

• Page load times and performance metrics

• User interactions and journey flows

• Frontend errors and JavaScript exceptions

• Network timing and API call performance

• Browser and device analytics

This real-world performance data helps us understand how our application behaves in production environments across different browsers, devices, and network conditions.

Error Monitoring

Previously handled by Sentry, our error monitoring is now integrated into our Datadog setup. This consolidation provides:

• Unified error tracking across frontend and backend systems

• Detailed error context and stack traces

• Automatic error grouping and prioritization

• Real-time alerts for critical issues

Centralized Logging

As part of our SOC2 compliance requirements, we maintain centralized logging in Datadog. This gives us:

• A single source of truth for all application logs

• Compliance-ready audit trails

• Powerful log search and analysis capabilities

• Custom log parsing and filtering