Datadog Pricing Explained: Hosts, Custom Metrics, and Ingestion

Datadog pricing is modular and usage-based, which means there is no single per-user price that tells you what the platform costs. Instead you pay for each product separately: infrastructure monitoring per host, APM per host, custom metrics above a free allotment, logs by the gigabyte ingested and then again by the event indexed, plus synthetics, RUM and a long list of add-ons. The total bill is the sum of every meter you enable, and because each meter scales with your fleet and your traffic, the bill grows as adoption spreads, often faster than anyone forecast.

This explainer is part of our complete guide to SaaS and data platform cost optimization, the cluster pillar it links up to. Once you understand the meters here, the practical cuts are in the companion guide, how to cut Datadog costs without losing observability. All figures below are list prices for reference; confirm your own rate on the official Datadog pricing page and billing documentation, since pricing varies by commitment and changes over time.

How does Datadog charge for hosts?

Datadog charges for infrastructure monitoring per host per month, where a host is a physical or virtual server, instance or node running the Datadog agent. As of 2026 the Pro tier lists at about $15 per host per month on an annual commitment, rising to about $18 per host on month-to-month billing; the Enterprise tier lists at about $23 per host annually and about $27 month-to-month. The tier you need depends on features such as longer metric retention and more granular data, not on host count alone.

The trap in per-host pricing is autoscaling. Datadog bills on the high-water mark of concurrent hosts in a billing hour, so a fleet that scales up for a daily peak or a batch job is billed at the peak, not the average. Containerized and serverless environments make this worse, because every short-lived node can count toward the high-water mark. Confirm whether you are being billed for ephemeral nodes that exist for minutes, because that is one of the most common sources of an inflated infrastructure line.

What is a Datadog custom metric and why does it cost so much?

A custom metric is a single, unique combination of a metric name, host and tag values, and Datadog counts each distinct combination as its own billable metric. Plans include a free allotment of custom metrics per host, and beyond that you are billed per additional metric, on the order of $0.05 per custom metric per month at list. The danger is cardinality: because every unique tag value combination is a separate metric, attaching a high-cardinality tag such as a raw user ID, request ID or container ID to a metric can multiply one logical metric into thousands of billable ones.

Datadog measures custom metrics on the monthly average of unique metrics submitted per hour, so a single badly tagged metric pushed by a busy service can dominate the count. This is the most common reason a Datadog bill jumps without any deliberate change: a developer adds a useful-looking dimension to a dashboard, and the custom-metric count quietly explodes. Auditing the custom-metric inventory and dropping high-cardinality tags nobody graphs is one of the highest-return moves available, covered in the cutting guide.

How does Datadog log pricing work: ingestion vs indexing?

Datadog bills logs in two separate layers, and confusing them is the most expensive misunderstanding in the whole pricing model. Ingestion is the charge for sending log data to Datadog at all, listed at about $0.10 per GB. Indexing is the separate, larger charge for making logs searchable and alertable, listed at about $1.70 per million log events at 15-day retention. You can ingest a log without indexing it, which is the entire basis of cost control: send everything cheaply, but only index the events you actually need to search fast.

Most teams over-index because the default is to index everything, and indexing is where the log bill concentrates. Datadog's filters and exclusion rules let you index only high-value events such as errors and security logs, route the rest to a cheaper archive tier, and rehydrate them for search only when needed. This is the same ingest-index-retain logic that applies across every observability platform, covered in how to reduce observability costs with sampling and retention.

What other Datadog products show up on the bill?

Beyond hosts, metrics and logs, Datadog meters several other products that each have their own runaway mode. APM is billed per host, often as a separate line from infrastructure. Synthetic monitoring is billed per test run, so dozens of checks across many locations add up. Real User Monitoring is billed per thousand sessions. Continuous Profiler, Database Monitoring, CSM and CI Visibility each carry their own meter. None is expensive alone, but the modular model means the total is the sum of all of them, and platforms with broad adoption end up paying for products that overlap or that nobody actively uses.

The short version

Datadog pricing is the sum of many usage-based meters, not a single price. Infrastructure is billed per host at roughly $15 to $27 depending on tier and commitment, custom metrics are billed per unique tag combination above a free allotment, and logs are billed twice, cheaply at ingestion and expensively at indexing. Understand which meters dominate your own bill before you try to cut it, because the largest two or three almost always hide the savings. When you are ready to act on it, read how to cut Datadog costs without losing observability and return to the SaaS and data platform cost pillar for the rest of the stack.