# Log Export
source: https://docs.chalk.ai/docs/logexport

## Export Chalk logs to other monitoring systems.

Chalk's online dashboard provides a simple way to view logs
from resolver execution. However, you may wish to
export these logs into other observability
tools so that you can view your Chalk-related data alongside
data from other systems you maintain.

### Exporting logs

Chalk can export logs to Datadog or an OTLP/HTTP destination.
Follow Export telemetry over OTLP for independent log export
and a test message you can find in your destination’s log UI.
Follow Export logs to Datadog to enable log export from your
cluster's Telemetry tab and confirm delivery in Log Explorer.

### Log fields

The following fields describe Chalk's JSON log format. The fields you see at a destination depend
on its mapping and any remapping you configure.

ISO8601 timestamp.

The log line format version. Currently constant "1".

The log message.

Name of the logger, if relevant.

The log level as a string: "INFO", "WARN", "ERROR", "DEBUG".

Stack trace of the associated exception, if relevant.

A trace ID in OpenCensus format. Used for correlating logs corresponding to a single query.

Chalk Project ID.

Chalk Deployment ID. Can be used to understand log patterns as code evolves.

Your commit SHA, if available for the deployment.

"online" or "offline".

The name of the resolver that produced this log line, if available.

Environment name.

Environment ID.

An array of the tags that were provided for the associated query.

The ID of the agent that made the request (a service token or Chalk user).

### Custom logs

Chalk provides an implementation of the standard Python Logger interface that supports
emitting logs to the web UI and your metrics export sink. You can use this logger like this:

```
from chalk.clogging import chalk_logger

@online
def your_resolver(...):
    chalk_logger.info("Hello world!")
```