Chalk raised $50M to power the future of ML
Chalk home page
Docs
SDK
CLI
  1. Observability
  2. Log Export

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 your logs to a sink of your choosing. You can configure sinks for log export from your settings page. Exported logs will contain the following fields:

Attributes
@timestampInstant
ISO8601 timestamp.
@versionstring
The log line format version. Currently constant "1".
messagestring
The log message.
logger_namestring
Name of the logger, if relevant.
levelstring
The log level as a string: "INFO", "WARN", "ERROR", "DEBUG".
stack_tracestring
Stack trace of the associated exception, if relevant.
tracestring
A trace id in OpenCensus format. Used for correlating logs corresponding to a single query.
projectstring
Chalk Project ID.
deploymentstring
Chalk Deployment ID. Can be used to understand log patterns as code evolves.
commit_shastring
Your commit SHA, if available for the deployment.
contextstring
"online" or "offline".
resolver_namestring
The name of the resolver that produced this log line, if available.
environmentstring
Environment name.
environment_idstring
Environment id.
tagsstring[]
An array of the tags that were provided for the associated query.
agent_idstring
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!")