Datasets: The LF AI & Data Foundation includes datashim in their incubator

The Kubernetes framework regulates access to S2 and NFS data sources in pods using a custom resource definition.

 Datasets: The LF AI & Data Foundation is including datashim in their incubator

Datashim opens up declarative, transparent access to datasets in Kubernetes and OpenShift application environments. The LF AI & Data Foundation has now included the two-year-old open source project, which goes back to IBM, in its incubator. With community support, Datashim is set to evolve, grow, and mature for production use.

Dataset CRD for Kubernetes and OpenShift

As a Kubernetes framework, Datashim is designed to support the Enable and manage access to different data sources for pods in Kubernetes and OpenShift environments. To do this, Datashim uses the Custom Resource Definition (CRD) dataset, which serves as a pointer to existing S3 and NFS data sources and HostPath volumes. Since the project is also compatible with the Container Storage Interface (CSI), further data sources are to be made accessible in the future.

Datashim provides developers with the logic required to convert the data sets into Persistent Volume Claims and ConfigMaps that users can then refer to in their pods. A dataset can be created and described in Datashim with a few lines of code. The example Persistent Volume Claim example-dataset is then available in the pods for read/write operations:

apiVersion: kind: Dataset metadata: name: example-dataset spec: local :type: “COS” accessKeyID: “{ACCESS_KEY_ID}” secretAccessKey: “{SECRET_ACCESS_KEY}” endpoint: “{S3_SERVICE_URL}” bucket: “{BUCKET_NAME}” readonly: “true” #OPTIONAL, default is false region: “” #OPTIONAL

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