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Eric Allam 45527e317a feat(webapp): opt-in worker pool for OTLP ingest transform (#4232)
## Summary

Under high OTLP ingest volume, the whole decode, transform, and enrich
pipeline runs on the request event loop, so a single CPU core becomes
the ceiling while the rest sit idle. This adds an opt-in worker pool
that moves decode, transform, and LLM-cost enrichment onto worker
threads, keeping the main thread free for I/O. It is off by default
(`OTEL_TRANSFORM_WORKER_POOL_ENABLED`), so behavior is unchanged unless
enabled.

## Design

Workers do decode, filter, convert, and enrich (including LLM pricing
match). The main thread stays the single database reader: it loads the
pricing registry and broadcasts the compiled model rows to the workers
(re-broadcasting on every reload), so workers never touch the database.
The pure transform is extracted into a dependency-light module (no
Prisma/Redis/ClickHouse imports) so it can run inside a worker.

Importantly, the main thread keeps the existing single consolidated
insert path, so ClickHouse insert batching and part count are unchanged.
The parallelism buys CPU headroom, not more insert streams (which would
add merge pressure).

The worker is bundled as a standalone file at build time and ships in
the existing image with no Dockerfile change. In local load testing the
pool sustained roughly 2.6x the throughput of the single-thread path and
kept the main thread responsive under load.
2026-07-11 13:38:12 +01:00
..

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---
area: webapp
type: fix
---

Speed up batch queue processing by removing stalls and fixing retry race

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  • type (required): feature | fix | improvement | breaking

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---
area: webapp
type: feature
---

TRQL query language and the Query page

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Fix schedule limit counting for orgs with custom limits

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---
area: webapp
type: improvement
---

Use the replica for API auth queries to reduce primary load