1.5.0

New features:

• Mount custom persistent volumes onto the worker pods using the additionalWorkerPVCs parameter.
• Specify tolerations for the job manager and worker pods using the jobManagerTolerations and workerTolerations parameters.
• Specify custom annotations for the load balancer service using the loadBalancerAnnotations parameter.
• Configure resource requests and limits for all pods deployed by the Helm chart, including the controller and ingress proxy pods.
• The MATLAB Job Scheduler controller now uses Go v1.23.5.

Bug fixes:

• Job manager pods no longer fail to restart after a previous job manager pod stops.
• You can now use the Helm chart as a subchart, as the restrictions in its JSON schema have been removed.

1.4.0

Release Notes:

New features:

• Specify node selectors for the MJS job manager and worker pods using the jobManagerNodeSelector and workerNodeSelector parameters. For more information about node selectors, see Assigning Pods to Nodes on the Kubernetes website.

Bug fixes:

• Workers in R2024b now consistently return licenses to the network license manager.
• The job manager pod now correctly avoids mounting MATLAB from a persistent volume when the jobManagerUsesPVC parameter is set to false.

1.3.0

New features:

• Set up the MATLAB Job Scheduler Helm chart to export cluster monitoring metrics such as cluster status, worker utilization, and licenses in use. Use these metrics to monitor the health of the MATLAB Job Scheduler cluster, diagnose issues, and optimize performance. You can gather the exported metrics with a cluster monitoring system such as Prometheus® and visualize them in a preconfigured Grafana® dashboard. This setup allows for live cluster monitoring and alerts. For more information, see Configure Cluster Monitoring Metrics.
• The Helm chart includes a JSON schema to define the structure of the Helm values file.

1.2.0

New features:

• MATLAB Job Scheduler in Kubernetes now supports MATLAB R2024b.
• You can configure MATLAB Job Scheduler in Kubernetes to run multiple versions of MATLAB Parallel Server. For setup instructions, see Run Multiple MATLAB Parallel Server Versions.
• You can configure MATLAB Job Scheduler in Kubernetes to use an LDAP server to authenticate user credentials. For setup instructions, see Configure LDAP over SSL.
• The README now contains storage requirements and troubleshooting steps for common validation failures.

1.1.0

New features:

• The GitHub repository now includes utilities that build MATLAB Docker images for the MATLAB Job Scheduler Job Manager and workers, and host these images in the GitHub Container Registry. By default, the Helm chart pulls these images, so you do not need to build your own. The repository also contains the Dockerfiles for these images, which you can modify to create a custom worker image with the MATLAB toolboxes and support packages you need.
• The example values.yaml file in the README now includes parameters for configuring MATLAB Parallel Server licensing.
• Template files in the Helm chart now have one YAML file per Kubernetes resource.
• MATLAB Job Scheduler controller Docker image now uses Go version 1.22.2.

Bug fixes:

• The job manager and worker pods now error correctly if there is an error setting up MJS.

1.0.0

A Helm chart to deploy MATLAB Job Scheduler onto your Kubernetes cluster. You can then connect to the MATLAB Job Scheduler and use it to run MATLAB Parallel Server jobs on the Kubernetes cluster.