What is a log API? A practical developer’s guide
Understand logging libraries, ingestion endpoints, and query interfaces—and build an event contract that connects them.
THE BIG PICTURE
Log APIA clearer contract for every event.
Understand the building blocks of a log API: create useful records, move them reliably, and retrieve them with context.
{
"schema_version": "1.0",
"timestamp": "2026-09-21T09:41:02.184Z",
"severity": "INFO",
"event_id": "evt_demo_001",
"event_name": "request.completed",
"service": "checkout-api",
"attributes": {
"route": "/orders/{id}",
"status_code": 200,
"duration_ms": 42
}
}Synthetic fixture · nothing is sentDownload JSON ↗
DESIGN WITH INTENT
Keep the important distinctions.
Emit with purpose
Define the question an event should answer before choosing its attributes.
Deliver deliberately
Separate acceptance into a queue from durable persistence.
Read with context
Connect events using safe references and clearly defined outcomes.
THE EVENT CONTRACT
Fields with a reason to exist.
A logging library, an ingestion endpoint, and a query API solve different problems. Map these responsibilities before selecting an implementation. A small common envelope can keep basic interpretation consistent while allowing approved attributes for different event types.
These fields illustrate a design pattern. Map them deliberately to your own schema, source, and destination.
| Field | What it means |
|---|---|
event_name | The action or occurrence the record describes. |
event_id | A stable identifier retained across delivery attempts. |
timestamp | When the event occurred, with a documented clock. |
service | The component that produced the event. |
A shared JSON shape is a design pattern, not automatic compatibility with a telemetry protocol. Document every mapping to your chosen collector.
Technical reference: OpenTelemetry logs data model . Verify the version and settings used by your own implementation.
FIELD NOTES
Keep following the signal.
Structured JSON logging: design a schema that lasts
Define meaningful fields, preserve data types, and evolve your event schema without breaking downstream readers.
Reliable log ingestion: queues, retries, and duplicates
Define delivery guarantees, bound your buffers, and make duplicate records and pipeline failures visible.
ONE EVENT IS A GOOD START
Make your next log more useful.
Start with a clear schema. Keep the context that matters.