claude_code_cost_usage_USD_total OTEL counter collides across parallel processes sharing the same session_id, producing oscillating values and inflating increase() queries by 100×+
Preflight Checklist
- [x] I have searched existing issues and this hasn't been reported yet
- [x] This is a single bug report (please file separate reports for different bugs)
- [x] I am using the latest version of Claude Code
What's Wrong?
Claude Code emits claude_code_cost_usage_USD_total from multiple processes (likely multiple --resume instances) without a process-distinguishing label, causing collisions in
any time-series backend.
jsonl file of the session:
25554c44-43fd-4d31-beb2-905547620336_jsonl.csv
cost reports that were received in Prometheus from Claude Code:
25554c44-session-metrics-2026-04-27.csv
What Should Happen?
Add pid or instance_uuid to the label set, or aggregate to a single per-session emitter.
Error Messages/Logs
Steps to Reproduce
- Configure Claude Code OTEL export to a Prometheus-compatible backend (Mimir, Prometheus, etc.) per the https://docs.anthropic.com/en/docs/claude-code/monitoring-usage. Confirm cumulative temporality at both the Claude Code
OTEL SDK and the OTEL collector.
- In one terminal (e.g., PyCharm), run claude --resume <session-id> and start working — make a few prompts that incur cost.
- Without exiting the first instance, in a second terminal of the same terminal_type (another PyCharm window) run claude --resume <session-id> against the same session UUID. Issue a few more prompts.
- After both processes have emitted at least one OTEL export interval (~60s), query the metric in your TSDB:
claude_code_cost_usage_USD_total{session_id="<session-id>"}
- Sample at fine resolution (step=2s over a 5-minute window).
Claude Model
Not sure / Multiple models
Is this a regression?
I don't know
Last Working Version
_No response_
Claude Code Version
2.1.126
Platform
Anthropic API
Operating System
Ubuntu/Debian Linux
Terminal/Shell
Other
Additional Information
_No response_
This issue has 3 comments on GitHub. Read the full discussion on GitHub ↗