Datadog: project + rebuild ROI.

Hosts, custom metrics, log volume, APM traces, RUM, synthetics — they all bill separately. Fourteen probing questions. Output: 24-month Datadog projection, comparison to Prometheus + Grafana + Tempo + OpenObserve rebuild, payback month, 3-yr reclaim. The 8-page memo includes architecture sketch + migration playbook + cardinality control patterns.

📋 14 questions · ~3 min 🔓 No signup to see result 📩 8-page memo for your email

How this is calculated

Datadog list pricing per product line (infra, APM, logs, RUM, synthetics, DBM, cloud cost). Custom metrics surcharge applied beyond base allowance. 24-month projection assumes typical 25%/yr growth in monitored stack. Rebuild cost: Prometheus + Grafana + Tempo + OpenObserve productized stack on AWS, with 1-2 platform FTE depending on scale.

What this does NOT estimate

Migration disruption to incident-response workflows
Custom dashboard rebuild effort (typically modest with Grafana provisioning)
Specific compliance overlays beyond stated

FAQ

When does rebuilding from Datadog make sense?

Above ~$300K/yr Datadog spend with growing stack, rebuild typically pays back in 8-14 months. Below $150K/yr, stay on Datadog — operational simplicity wins.

What about cardinality?

Custom metrics surcharge is the silent cost driver — most orgs find 30-50% of metrics are unused. Memo includes the cardinality audit playbook.

What's in the memo?

Cost projection, rebuild architecture sketch, migration playbook, cardinality control patterns, on-call workflow continuity. About 8 pages.

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