how do I cancel all queued jobs in a kubernetes deployment?

To cancel all queued jobs in a Kubernetes deployment, you can use a script to programmatically cancel the runs. Here's an example script provided in the documentation that you can run to clear out the queue:

python from dagster import DagsterInstance, RunsFilter, DagsterRunStatus  instance = DagsterInstance.get()  # needs your DAGSTER_HOME to be set  while True:     queued_runs = instance.get_runs(limit=100, filters=RunsFilter(statuses=[DagsterRunStatus.QUEUED]))     if not queued_runs:         break     for run in queued_runs:         instance.report_run_canceled(run)

This script retrieves queued runs from the Dagster instance and cancels them in a loop until there are no more queued runs. You would need to have your

DAGSTER_HOME

environment variable set for the

DagsterInstance.get()

method to work correctly. If you're running Dagster in Kubernetes, you can execute this script by running

kubectl exec

into the Dagit pod. This approach allows you to interact with the Dagster instance directly within your Kubernetes cluster.

@Scout what's the best way to clear all materializations + run history from a dagster instance deployed to kubernetes?

To clear all materializations and run history from a Dagster instance deployed to Kubernetes, you can use the

dagster instance wipe

command. This command will eliminate all run history and event logs from your Dagster instance. However, please note that this is a destructive operation and cannot be undone. You should ensure that you have proper backups or that you are certain you want to delete this data before proceeding. Here's how you can use the

dagster instance wipe

command: 1. Connect to your Kubernetes cluster where Dagster is deployed. 2. Use

kubectl

to exec into the Dagit pod:

bash    kubectl exec -it <dagit-pod-name> -- /bin/bash

Replace

<dagit-pod-name>

with the actual name of your Dagit pod. 3. Once inside the pod, run the

dagster instance wipe

command:

bash    dagster instance wipe

4. Confirm the prompt to proceed with wiping the instance data. Please be cautious with this command as it will remove all run history and event logs, which includes materializations, from your Dagster instance. If you only want to delete certain runs or materializations, you would need to use more targeted commands or API calls to delete specific runs or events.

@Scout it says no command 'wipe' I'm using dagster webserver 1.6.3

As of my knowledge cutoff date in early 2023, there is no direct

dagster instance wipe

command available in the Dagster CLI. The documentation does not list such a command for wiping the instance data. If you are seeing an error indicating that there is no 'wipe' command, it means that the command is not available in the version of Dagster you are using. To clear all materializations and run history from a Dagster instance, you would typically need to directly interact with the underlying storage systems that Dagster uses to store this information, such as the event log storage and run storage. This could involve manually deleting data from the PostgreSQL database, if that's what you're using for storage, or clearing the appropriate storage if you're using a different backend. Here are the general steps you would take to clear the data, but please be aware that these are destructive operations and should be done with caution: 1. Identify the storage backend used by your Dagster instance for event logs and run storage. This is typically configured in your

dagster.yaml

file. 2. Access the storage backend. If you are using PostgreSQL, for example, you would access the PostgreSQL database that Dagster is configured to use. 3. Execute the appropriate SQL commands to delete the data from the tables that store run history and event logs. For PostgreSQL, this might involve commands like:

sql    TRUNCATE TABLE event_logs;    TRUNCATE TABLE runs;

Please replace

event_logs

and

runs

with the actual table names used by your Dagster instance if they are different. 4. If you are using other storage backends, follow the appropriate procedures for those systems to clear the data. Since these operations can lead to data loss, it's important to back up any valuable data before proceeding. If you are unsure about how to safely perform these operations, consider reaching out to someone with database administration experience or seeking further assistance from the Dagster community or support channels. Remember that the exact commands and procedures may vary depending on the version of Dagster you are using and the specific configuration of your deployment. Always refer to the documentation for the version of Dagster you are using for the most accurate and up-to-date information.