Product and charge type, month to date
CostMon reads Datadog's Usage Metering API every hour. It splits month-to-date spend by product and by committed or on-demand charge. You do not wait for one subscription total at month end.
Datadog cost monitoring
CostMon reads Datadog's Usage Metering API. This is the data behind your Datadog invoice. CostMon splits it by product and by committed or on-demand spend. It refreshes the month-to-date total every hour. A high-cardinality custom metric or a host surge shows in that total before the invoice.
Datadog bills custom metrics by cardinality. That means each unique mix of metric name and tag values. One metric tagged by customer_id or request_id can grow into a five- or six-figure billable count. Nobody has to add a new metric name. Host billing has its own trap. Datadog samples host count every hour and bills near the peak. A brief autoscale spike can set the host charge for the whole month. Log ingest and log indexing are separate meters. One verbose logging change can move two line items. None of this shows as one clear number until the invoice arrives.
Cost anatomy
Alerts
Datadog data arrives as monthly totals, so a monthly budget is the rule that fits it. An alert always shows up in your CostMon feed. Add an email, Slack, or webhook channel to send it somewhere else too.
A monthly budget on total Datadog spend catches the month-to-date total climbing, from a new high-cardinality tag or a host surge.
To find what to cut, the recommendations list flags idle spend and commitment gaps to review.
Why CostMon
CostMon reads Datadog's Usage Metering API every hour. It splits month-to-date spend by product and by committed or on-demand charge. You do not wait for one subscription total at month end.
The month-to-date total for a product climbs as a new tag or new hosts add usage. A budget alert warns you when the total nears your limit. You do not find out at the invoice.
A Datadog bill often tracks the infrastructure it watches. With both in one view, you can check a Datadog host-count jump. Did the AWS or GCP fleet really grow too?
CostMon connects with a Datadog API key and application key scoped to read-only usage and cost endpoints only. It never touches your monitors, dashboards, or telemetry data.
Getting started
Add a Datadog API key and application key scoped to the Usage Metering API's read-only cost endpoints. CostMon never touches your monitors, dashboards, or telemetry data.
CostMon pulls estimated and historical cost data on a schedule. It keeps one row for each product and charge type in each month. Each row uses the cost schema of your AWS and AI data.
Check month-to-date Datadog spend for each product. An autoscale burst lifts the infra_host line. A new high-cardinality tag lifts the custom metrics line. A budget alert fires when the total crosses your limit.
FAQ
Through a Datadog API key and application key scoped to the Usage Metering API's read-only cost endpoints. CostMon never requests access to your monitors, dashboards, or logs themselves, only cost and usage data.
No. CostMon reads the same Usage Metering API. Your Datadog month-to-date figure then shows next to your AWS, GCP and model spend.
Yes. Each cost row keeps its product and its committed or on-demand charge type. You can see trends for APM, logs, infrastructure or custom metrics. An allocation rule can assign Datadog spend to a team by source, service or connector.
The background scheduler syncs every hour by default. It uses Datadog's estimated-cost endpoint for the current and previous month. It uses historical cost for older months. Datadog data is monthly. Each row is one product and charge type for one month, so you see month-to-date totals, not daily figures.
A flat monthly rate per plan. It never charges a cut of your Datadog spend or the savings CostMon helps you find. Free includes 2 connectors; Professional and Enterprise include unlimited connectors.
Connectors
AWS, GCP, and Azure for cloud. Anthropic, OpenAI, Amazon Bedrock, Vertex AI / Gemini, and Helicone for AI and LLM spend. Snowflake and Databricks for the data cloud. Datadog, GitHub, and Vercel for the rest of the stack. Add CSV import for any tool without a native connector. That's 14 connectors, all normalized into the same unified view.
Connect a provider and CostMon builds a daily baseline for it. From there, a spike reaches your team as an alert.