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Free Trial Cluster
You are welcome to provide your own cluster to use during the free trial period, or even combine your own cluster with the free trial cluster in order to try out the multi-cluster capabilities of Pipekit.
In order to facilitate your trial of Pipekit, the free trial cluster comes with a number of software packages pre-installed and pre-configured. These include:
- Argo Workflows
- Minio (s3-compatible object storage)
- Pipekit Agent
The free trial clusters are constantly maintained, meaning that software versions can change frequently. We aim to keep the cluster and its contents on the latest stable versions.
Your provisioned cluster is not shared with any other users. Your free trial organization will be the only organization with access to the cluster. Access to the cluster is restricted to the Pipekit team and your organization's users. However, we recommend you do not use the cluster for any sensitive data or workflows. We recommend you fork our Pipekit Examples Github repository and use the workflows therein.
You have no access the cluster itself. You can trigger Pipekit workflows and the Pipekit Agent will execute them on your behalf inside the cluster.
While we will make every effort to ensure you have a smooth free trial, we make no guarantees as to the availability of the free trial cluster.
Your workflows should be executed in the
You should use the
argo-workflowService Account Name to run your workflows.
To use private container registries, or to avoid rate limits from public registries. We recommend you add your docker registry credentials to your org in pipekit. Any workflows run from Pipekit will then automatically inherit these secrets.
The cluster is intended for trial purposes only. As such, there are a number of limitations in place to ensure the cluster is not abused.
The cluster is limited in CPU, Memory and Ephemeral Storage. If you breach this limit, the workflows will fail or time out. The limits cannot be increased.
You cannot use persistent storage in the cluster.
In order to facilitate Kubernetes scheduling, if you do not set a resource limit on a resource, we set a default limit of 200m CPU, 200Mi Memory and 100Mi Ephemeral Storage. You can override this by setting a limit in your resource requests in your Workflows.
If you see an error similar to
Invalid value: "1Gi": must be less than or equal to memory limit of 200Mi, this indicates that you set a memory resource request above the default limit, but you did not set a higher memory resource limit. In this case you should set a memory limit on the resource that matches or exceeds your memory request.
Argo Workflows is configured to use minio as an artifactRepository. The minio endpoint can be reached at
http://minio.pipekit.svc.cluster.local:9000. The minio access key and secret key are
Minio does not have persistent storage. All artifacts are stored in memory and may be lost at any time. You should not rely on minio for long-term storage of artifacts. It is recommended to keep the total size of artifacts below 1GB.
These cannot be changed in the free trial cluster, however you can overwrite them in each individual workflow.
Once a free trial cluster has been deleted, it cannot be recreated.
Last modified 1mo ago