| ID | product.serving |
|---|---|
| Description | Query layer and APIs that expose curated data to consumers. |
| Key | serving |
| Type | system |
| Team | Query Platform |
| Owner | query@dataplatform.example |
| Status | active |
| Technologies | Trino, Presto, Redis |
| Attributes | federation: lakehouse, interfaces: sql,metrics |
| Tags |
Serving is the read path of the platform. Analysts, dashboards and external API consumers never scan raw lake files directly — they submit SQL to the distributed query engine or request governed metrics from the semantic layer, which translates business definitions into warehouse SQL with row-level policies applied.
Responsibility in one sentence
Execute federated SQL over the lakehouse, cache hot results, throttle abusive queries, and resolve governed metrics into policy-aware SQL.
Could not build diagram for model "example-data-processing".
Both containers expose REST APIs documented on their Overview tabs:
Live dashboard tiles query materialized stream outputs through the engine:
Analysts iterate in notebooks before publishing governed dashboard tiles:
Fair use
When a query exceeds its time budget, the Query Throttler kills it and suggests an equivalent semantic-layer metric instead.
3 incoming links · 1 outgoing link
| Source object | Label | Link type | Relation | Raw id | Required | Description | |
|---|---|---|---|---|---|---|---|
| queries via | — | links | product.serving | — | — | ||
| serves curated data to | — | links | product.serving | — | — | ||
| publishes results to | — | links | product.serving | — | — |
| Target object | Label | Link type | Relation | Raw id | Required | Description | |
|---|---|---|---|---|---|---|---|
| powers | — | links | product.analytics_ui | — | — |