Why Datadog
Datadog gives me infrastructure-level observability across servers, containers, and services. Where New Relic focuses on application performance, Datadog brings the full picture — host metrics, container health, log aggregation, and cross-service dashboards.
How I Use It
At KnausDev, I use Datadog on client infrastructure where I need to correlate application behavior with system-level metrics. CPU spikes during queue processing, memory pressure on Docker containers, disk I/O during database migrations — these are infrastructure problems that don’t show up in application-level monitoring alone.
On platforms like Exlink with 15+ servers across Hetzner and Azure, Datadog ties together what’s happening across providers into a single view. Background jobs processing expert matching queries, Meilisearch indexing, and Zoom webhook ingestion all generate infrastructure load that needs visibility beyond the Laravel application layer.
RUM & Session Tracking gives me the frontend side — real user performance data, session replays, and error tracking from the browser. When a client reports something is broken, I can pull up the exact session and see what happened from their perspective.
Log management is the other key piece. Centralizing logs from Laravel applications, Nginx, and background workers into a single searchable interface saves hours of SSH-ing into individual servers to grep through log files.
In the Stack
Datadog, New Relic, and Uptime Kuma cover three different levels of the same problem across KnausDev infrastructure. Uptime Kuma watches the surface — is it responding. New Relic watches the application — is it performing. Datadog watches the infrastructure — is it healthy. k6 validates performance before deployment. Not every project needs all four, but having experience across the spectrum means I can pick the right tool for the scale.