Keep Every LangSmith Trace Without the 10 Retention Bill
LangSmith is excellent for debugging live AI systems. But keeping every trace in its extended-retention tier can turn observability into a surprisingly large line item. Today we merged a new archive workflow into langsmith-cli that changes that tradeoff: keep LangSmith for live debugging, continuously archive verified traces to organization-owned private S3, and query the retained Parquet directly with DuckDB. In other words, you can preserve your complete trace history without placing every trace on LangSmith's extended-retention tier. The cost-overrun risk LangSmith currently documents two trace-retention tiers: Tier Retention Published trace price Base 14 days 0.05¢ Extended 400 days 0.50¢ total The 0.45¢ extended-retention upgrade makes an extended trace cost 10× as much as a base trace. That difference becomes material at production volume: Monthly traces Base, 14 days Extended, 400 days Added retention cost 100,000 $50 $500 $450 1,000,000 $500 $5,000 $4,500 10,000,000 $5,000 $50,000 $45,000 These examples use the published per-trace rates before free allowances, plan terms, negotiated pricing, or taxes. Always check the official LangSmith usage and billing documentation before making budget decisions. There is another subtle risk: online evaluators and automation rules can upgrade matching traces when retention extension is enabled. A rule that matches one run upgrades the whole trace, and a thread-level rule can upgrade every trace in that thread. LangSmith currently enables retention extension by default for new online evaluators and automation rules, although you can opt out. At scale, an innocent-looking evaluator or rule can therefore create a much larger bill than expected. The new langsmith-cli archive workflow The new workflow separates live observability from long-term retention: LangSmith live traces (14 days) │ ├── D+2 primary export ───────┐ └── D+12 reconciliation ──────┤ deduplicate by run ID ▼ private S3 / Parquet │ ▼ runs ... --archive (DuckDB)