Panther uses Snowflake to store and search log data.

Integrating Panther with Snowflake enables Panther data to be used in your Business Intelligence tools to make dashboards tailored to you operations. You can also join Panther data (e.g., Panther alerts) to your business data, enabling assessment of your security posture with respect to your organization. For example, you can tally alerts by organizational division (e.g., Human Resources) or by infrastructure (e.g., development, test, or production).

Snowflake instances can be Panther-managed or customer-configured. Learn how Panther configures managed Snowflake instances (or take away recommendations for how to configure an instance you configure) on Snowflake Configuration for Optimal Search Performance. Note that certain Panther features are only available on an Enterprise Edition of Snowflake or higher.

Panther uses Snowpipe to copy the data into your Snowflake cluster.

Use additional data sets in Panther

Panther uses a panther_readonly Snowflake user to query data in Snowflake. By default, this user's role panther_readonly_role is only endowed with a minimal set of grants to enable it to access the data in the panther databases. However, if you wish to add your own preexisting datasets to your Data Explorer queries (such as HR data, in-house or vendor-provided allowlists/denylists) you can make that data accessible to the role with statements like the following:

  ON DATABASE my_database_name
  TO ROLE panther_readonly_role;
  ON SCHEMA my_database_name.my_schema_name
  TO ROLE panther_readonly_role;
  ON TABLE  my_database_name.my_schema_name.my_table_name
  TO ROLE panther_readonly_role;

Note that the newly granted database, schema and table will not populate in the Panther sidebar, but you will be able to access it using regular SQL.

Using the Panther Monitor Database


Panther implements a set of basic data load status self-monitoring tables:

  • a pipe status monitoring table panther_monitor.public.pipe_history

  • a file load status monitoring table panther_monitor.public.load_history

  • a data source table history panther_monitor.public.table_history

  • a monitoring history, tracking any load errors encountered panther_monitor.public.monitor_history

Under the default snowflake configuration settings, a master stack variable named SnowflakeMonitorRunFrequency is set to run a monitoring sweep every 180 minutes. This variable can be adjusted as desired down to a minimum of once every 2 minutes, or up to a maximum of once every 10080 minutes (a week).

If a data loading error is found by the monitor sweep, this should trigger an alarm in CloudWatch, under the /aws/lambda/panther-snowflake-admin-api log group. The data loading errors are also stored in the data monitoring history table.

The monitoring tables are implemented in the panther_monitor database, and can be queried via the WebUI or the Panther Data Explorer. Please note that the monitor database is not currently one of the pre-populated data sets in the Panther UI.

Upgrading considerations

Customers should run the latest version of the snowflake setup instructions before upgrading to a version including snowflake data load monitoring.

Using the load monitors

The monitors are designed to capture information from a variety of sources: 1. The pipe status captures information about the state of all the snowpipes used by the Panther system, and will keep a history of it in the pipe_history table. Pipes that are not in a RUNNING state will generate an alert in CloudWatch and will be recorded as an entry in monitor_history

  1. Load status of every file for every table is stored in load_history -- if a file failed to load (state not LOADED or LOAD_IN_PROGRESS) for any reason, the even will be recorded in CloudWatch and also as an entry in the monitor_history table.

  2. Table History -- at every run of the monitoring sweep, the table history will update, including such information as row and byte counts and row and byte count deltas. Please note that due to clustering compaction operations by Snowflake, byte counts may decrease occasionally between sweeps. Additional useful information in this table is a last_altered time which indicates the last time changes were made to the data in the table, and a last altered delta, indicating the time in seconds between when these changes were made and the last monitor sweep. As different data sources can have dramatically different load frequencies (ranging from seconds to weeks) no default alerting is currently driven from the table history table.

  3. Monitor History -- if there are errors encountered during the load process (an example would be s3 access errors caused by a change in s3 permissions) such errors would be summarized in the monitor_history table.

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