Start with the billing route: direct Anthropic API calls and calls billed through Amazon Bedrock have different reporting tools. For direct Anthropic usage, export the Claude Console Usage report for a quick check by API key and model. For finer, repeatable attribution, query the organization Messages usage-report API. Then compare the usage with billing details and application logs; an error code or displayed balance alone may not explain the change.
First identify who bills for the API calls
If your application sends requests directly to Anthropic, use the Claude Console Usage page or the organization usage-report API described below. If it invokes Claude through Amazon Bedrock, investigate the AWS billing and logging path instead. Anthropic says its Admin, Usage, and Cost API endpoints are not supported for Bedrock; AWS Bedrock invocation logging is the relevant route for tracing those calls. Anthropic’s Bedrock documentation explains the distinction.
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Run a quick audit in Claude Console
- Open the Usage page in Claude Console.
- Export the usage report as a CSV.
- Compare equivalent time periods and inspect usage by API key and model. Look for a new concentration or a sharp change rather than comparing mismatched date ranges.
- Keep the export alongside incident notes and compare the affected interval with application logs and deployment times.
Anthropic’s instructions for auditing model usage describe the CSV breakdown by API key and model. See Anthropic’s usage-and-costs guidance. Comparing the export with releases and logs is an investigation technique, not proof that a deployment caused the increase.
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For automation or more granular grouping, Anthropic documents GET /v1/organizations/usage_report/messages. The report can group or filter by API key, workspace, model, service tier, and context window; its reference also documents account and service-account IDs and inference geography. It reports token-usage categories and may include server tool use, so do not assume token totals alone account for every billable component without checking the applicable pricing and features. Consult the usage-report API reference.
Choose a bucket size and bounded time range
The endpoint accepts RFC 3339 time boundaries and snaps them to UTC bucket boundaries. Supported bucket widths are 1d, 1h, and 1m. The maximum ranges are 31 daily buckets, 168 hourly buckets, or 1440 minute buckets. If the response indicates more results with has_more, request the next page using the returned page token.
Example request
This illustrative request asks for hourly usage grouped by API key, workspace, and model. Use an Admin API key with suitable organization permissions, keep the date range bounded, and protect the credential:
curl "https://api.anthropic.com/v1/organizations/usage_report/messages?starting_at=2026-10-01T00:00:00Z&group_by[]=api_key_id&group_by[]=workspace_id&group_by[]=model&bucket_width=1h&limit=24"
--header "anthropic-version: 2023-06-01"
--header "x-api-key: $ANTHROPIC_ADMIN_KEY"Choose a time range and grouping that match the incident you are investigating; the reference documents the available parameters and pagination behavior.
Choose the reporting path that matches your setup
| Option | Best use | Attribution and granularity | Boundary |
|---|---|---|---|
| Claude Console Usage CSV | Fast manual audit | API key and model | Use for direct Anthropic billing; confirm the provider route first. |
| Admin API Messages usage report | Automation and deeper grouping | API key, workspace, model, service tier, context window; minute, hour, or day buckets | Requires suitable Admin API access; date ranges are bounded and results may require pagination. |
| AWS Bedrock reporting and logging | Calls billed through Bedrock | AWS-side invocation logs and billing/usage path | Anthropic Admin, Usage, and Cost endpoints are unsupported for Bedrock. |
Trace a sudden usage increase systematically
- Confirm the provider. Establish whether the affected calls are billed directly by Anthropic or through Bedrock, then use the corresponding reporting path.
- Compare matched windows. Use equivalent date ranges and bucket sizes. The usage-report API uses UTC bucket boundaries, so align the periods before interpreting a difference.
- Find where the change is concentrated. In the CSV, compare API keys and models. In the API report, add workspace, service tier, or context window where relevant.
- Correlate the affected interval with application activity. Review request logs, deployment changes, retry behavior, scheduled jobs, and newly enabled features. Treat these as leads to test, not assumed causes.
- Separate usage from billing and error conditions. Compare reported usage with the relevant billing view and the account’s payment or credit arrangement. Anthropic says billing is based on actual monthly usage, payments are in USD, and usage tracking is available in Claude Console. Check Anthropic’s pricing and billing information.
Interpret spend-limit, billing, and rate-limit errors
HTTP status codes point to different possible problems; they do not all mean credits have run out. Anthropic documents that the meaning of a 429 depends on the case, including rate limiting and applicable spend limits. See the API error reference.
- 400: May indicate that a configured organization or workspace spend limit has been reached.
- 402: Indicates a billing or payment issue. Check the account’s payment details.
- 429: May indicate rate limiting, a monthly tier spend cap, or a Claude Code workspace spending limit. A 429 by itself does not establish that prepaid credits are exhausted.
Check the error body and account configuration alongside usage and billing views; the status alone may not identify the underlying cause.
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For a specific failed response, preserve its request ID. Anthropic says each response has a unique request ID and asks customers to include it in support requests. Read Anthropic’s request-ID guidance.
Include the affected UTC interval, organization and workspace identifiers, API key identifier (never the secret), model, HTTP status and error body, and request ID. For a usage spike, retain the relevant CSV or report output and note any corresponding application or deployment events.
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