Dash0 is now adopted by all four teams. The Cayenne team completed onboarding this quarter. Dash0's OpenTelemetry-native pipeline and cost-transparent pricing model have proven ideal for our multi-team setup. It serves as the observability backend for all services running on Kubernetes. Custom dashboards provide real-time business KPIs alongside technical metrics, and automatic instrumentation keeps onboarding effort minimal.
Why Dash0
We evaluated Dash0 alongside Datadog, Grafana Cloud, and New Relic. The decision came down to three factors:
- OTel-native architecture — Dash0 ingests OTLP directly without requiring proprietary agents. This aligns with our OpenTelemetry strategy and avoids vendor lock-in at the instrumentation layer.
- Transparent pricing — per-GB ingestion pricing with no hidden per-host or per-container fees. For our Kubernetes environment with high pod churn, this saves ~40% compared to per-host models.
- Automatic instrumentation — Dash0's Kubernetes operator automatically instruments workloads without code changes, which was critical for onboarding the 50+ services already running.
Dashboard Strategy
Each team maintains two dashboard categories:
- Technical dashboards — latency percentiles, error rates, pod resource utilization, deployment frequency
- Business dashboards — conversion funnels, configurator session duration, API consumer usage patterns
A shared "platform health" dashboard aggregates cross-team SLOs, giving management a single pane for service reliability. Alerts route to PagerDuty with team-specific escalation policies.
Integration Architecture
Application Pods
└─ OTel SDK / auto-instrumentation
└─ OTel Collector (DaemonSet)
└─ OTLP export
└─ Dash0 SaaS
├─ Metrics store
├─ Trace store
└─ Log store
FluentBit collects container logs and forwards them via OTLP, unifying all three signals in a single backend. Correlation between traces, metrics, and logs uses the W3C trace context propagated through service calls.
