## What Follow-up to #4539. The driver-adapter work is inert until a client flips to the pg driver adapter, but the moment one does, our database observability degrades: the OTel metrics pipeline reads pool stats from Prisma's `$metrics`, which is owned by the Rust engine's `quaint` pool. Under the adapter, `pg.Pool` owns the pool, so those gauges read zero. The pipeline also only ever scraped a single client (the control-plane writer singleton). This PR makes database metrics driver-agnostic and per-client: - Every configured client registers a metrics source: control-plane writer/replica, run-ops writer/replica, legacy writer/replica. Previously only the control-plane writer singleton was scraped. - Each OTel instrument is observed per client with `db_client` and `db_driver` (`quaint` | `pg-adapter`) attributes. `db_client` uses our canonical datasource-role labels (`control-plane-writer`, `control-plane-replica`, `run-ops-writer`, `run-ops-replica`, `legacy-run-ops-writer`, `legacy-run-ops-replica`) — the same strings used for the `db.datasource` span attribute, so a metric and a trace point at the same pool. - Pool figures come from the authoritative source per driver: - **pg-adapter**: `pg.Pool` (`totalCount`/`idleCount`/`waitingCount`, plus cumulative opened/closed from `connect`/`remove` events). - **quaint**: the Rust engine's `$metrics` pool gauges/counters, exactly as before. - Query counters and duration histograms still come from `$metrics` for both drivers (the Rust engine executes queries in both cases). - New `db.pool.connections.waiting` gauge (pg.Pool exposes this; quaint reports 0). - Stops exporting Prisma metrics from the Prometheus `/metrics` route. Pool observability now lives entirely in the OTel pipeline, per driver, per client. ## Why So we can flip any client (including the control-plane writer, the primary desync-fix target) to the driver adapter without losing pool visibility. Existing dashboards keyed on the same metric names keep working; they gain a per-client dimension. ## Testing Unit (`apps/webapp/app/utils/databaseMetrics.server.test.ts`): the pure normalizer — quaint reads pool from `$metrics`; adapter reads pool from `pg.Pool` and keeps engine query metrics; `busy` never goes negative; graceful zeroing when `$metrics` is unavailable (adapter still reports live pool figures). Live smoke test against a prod-shaped local stack: three physically-distinct Postgres DBs (control-plane, run-ops, legacy) behind dual PgBouncers, split mode on, with a mix of adapter and quaint clients. Reading the actual emitted OTel metrics, every pool shows up as its own series: ``` db.pool.connections.total{db_client="control-plane-writer", db_driver="pg-adapter"} = 1 db.pool.connections.total{db_client="control-plane-replica", db_driver="quaint"} = 1 db.pool.connections.total{db_client="run-ops-writer", db_driver="pg-adapter"} = 1 db.pool.connections.total{db_client="run-ops-replica", db_driver="quaint"} = 1 db.pool.connections.total{db_client="legacy-run-ops-writer", db_driver="quaint"} = 1 db.pool.connections.total{db_client="legacy-run-ops-replica",db_driver="quaint"} = 1 db.client.queries.total{db_client="control-plane-writer",db_driver="pg-adapter"} = incrementing db.client.queries.duration.count{db_client="control-plane-writer",db_driver="pg-adapter"} = incrementing ``` Confirms: metrics are attributed per pool with the correct driver; adapter pools' figures come from `pg.Pool`; and query counters/duration histograms keep incrementing under the pg adapter. Also verified `/metrics` (Prometheus) now returns zero `prisma_*` series while still serving the app's own metrics. `pnpm run typecheck --filter webapp` passes. ## Notes - `/metrics` (Prometheus) no longer includes `prisma_*` series. Anything scraping that endpoint for Prisma metrics should read the equivalent `db.*` metrics from the OTel exporter instead. - **PgBouncer + `?schema=` gotcha (separate from this PR, worth flagging for rollout):** since #4539 parses `?schema=` from the DSN and passes `{ schema }` to the adapter, node-postgres sends `search_path` as a startup parameter. A transaction-mode PgBouncer rejects that with `FATAL: unsupported startup parameter: search_path`. Our prod control-plane DSNs use the default `public` schema with no `?schema=` param, so this is latent, but any client we flip to the adapter must not carry `?schema=` in its DSN (or the pooler needs `ignore_startup_parameters = search_path`). --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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About Trigger.dev
Trigger.dev is the open-source platform for building AI workflows in TypeScript. Long-running tasks with retries, queues, observability, and elastic scaling.
The platform designed for building AI agents
Build AI agents using all the frameworks, services and LLMs you're used to, deploy them to Trigger.dev and get durable, long-running tasks with retries, queues, observability, and elastic scaling out of the box.
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Long-running without timeouts: Execute your tasks with absolutely no timeouts, unlike AWS Lambda, Vercel, and other serverless platforms.
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Durability, retries & queues: Build rock solid agents and AI applications using our durable tasks, retries, queues and idempotency.
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True runtime freedom: Customize your deployed tasks with system packages – run browsers, Python scripts, FFmpeg and more.
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Human-in-the-loop: Programmatically pause your tasks until a human can approve, reject or give feedback.
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Realtime apps & streaming: Move your background jobs to the foreground by subscribing to runs or streaming AI responses to your app.
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Observability & monitoring: Each run has full tracing and logs. Configure error alerts to catch bugs fast.
Key features:
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import { task } from "@trigger.dev/sdk";
//1. You need to export each task
export const helloWorld = task({
//2. Use a unique id for each task
id: "hello-world",
//3. The run function is the main function of the task
run: async (payload: { message: string }) => {
//4. You can write code that runs for a long time here, there are no timeouts
console.log(payload.message);
},
});
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