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Update ReadMe for Helm Charts to specify required charts and their purpose #101

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Update ReadMe for Helm Charts to specify required charts and their purpose #101

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Update readme.md formatting to add a "required for" column
nghtm Jun 10, 2025
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Update readme.md
nghtm Jun 10, 2025
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Update readme.md with some initial requirements for helm chart depede…
nghtm Jun 10, 2025
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30 changes: 15 additions & 15 deletions helm_chart/readme.md
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Expand Up @@ -13,21 +13,21 @@ chmod 700 get_helm.sh

## 2. Package structure

| Chart Name | Usage | Enable by default |
|------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------|
| Cluster role and binding | Defines cluster-wide roles and bindings for Kubernetes resources, allowing cluster administrators to assign and manage permissions across the entire cluster. | No |
| Team role and binging | Defines cluster and namespaced roles and bindings, allowing cluster administrators to create scientist roles with sufficient permissions to submit jobs to the accessible teams. | No |
| Deep health check | Implements advanced health checks for Kubernetes services and pods to ensure deep monitoring of resource status and functionality beyond basic liveness and readiness probes. | Yes |
| Health monitoring agent | Deploys an agent to continuously monitor the health of Kubernetes applications, providing detailed insights and alerting for potential issues. | Yes |
| Job auto restart | Configures automatic restart policies for Kubernetes jobs, ensuring failed or terminated jobs are restarted based on predefined conditions for high availability. | Yes |
| MLflow | Installs the MLflow platform for managing machine learning experiments, tracking models, and storing model artifacts in a scalable manner within the Kubernetes cluster. | No |
| MPI Operators | Orchestrates MPI (Message Passing Interface) jobs on Kubernetes, providing an efficient way to manage distributed machine learning or high-performance computing (HPC) workloads. | Yes |
| namespaced-role-and-bindings | Creates roles and role bindings within a specific namespace to manage fine-grained access control for Kubernetes resources in a limited scope. | No |
| neuron-device-plugin | Deploys the AWS Neuron device plugin for Kubernetes, enabling support for AWS Inferentia chips to accelerate machine learning model inference workloads. | Yes |
| storage | Manages persistent storage resources for Kubernetes applications, ensuring that data is retained and accessible across pod restarts and cluster upgrades. | No |
| training-operators | Installs operators for managing various machine learning training jobs, such as TensorFlow, PyTorch, and MXNet, providing native Kubernetes support for distributed training workloads. | Yes |
| HyperPod patching | Deploys the RBAC and controller resources needed for orchestrating rolling updates and patching workflows in SageMaker HyperPod clusters. Includes pod eviction and node monitoring. | Yes |
| aws-efa-k8s-device-plugin | This plugin enables AWS Elastic Fabric Adapter (EFA) metrics on the EKS clusters. | Yes |
| Chart Name | Usage | Required For | Enable by default |
|------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------|-------------------|
| Cluster role and binding | Defines cluster-wide roles and bindings for Kubernetes resources, allowing cluster administrators to assign and manage permissions across the entire cluster. | | No |
| Team role and binging | Defines cluster and namespaced roles and bindings, allowing cluster administrators to create scientist roles with sufficient permissions to submit jobs to the accessible teams. | | No |
| Deep health check | Implements advanced health checks for Kubernetes services and pods to ensure deep monitoring of resource status and functionality beyond basic liveness and readiness probes. | [Deep Health Check](https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-hyperpod-eks-resiliency-deep-health-checks.html) | Yes |
| Health monitoring agent | Deploys an agent to continuously monitor the health of Kubernetes applications, providing detailed insights and alerting for potential issues. | [Health Checks done by Health Monitoring Agent](https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-hyperpod-eks-resiliency-health-monitoring-agent.html) | Yes |
| Job auto restart | Configures automatic restart policies for Kubernetes jobs, ensuring failed or terminated jobs are restarted based on predefined conditions for high availability. | | Yes |
| MLflow | Installs the MLflow platform for managing machine learning experiments, tracking models, and storing model artifacts in a scalable manner within the Kubernetes cluster. | | No |
| MPI Operators | Orchestrates MPI (Message Passing Interface) jobs on Kubernetes, providing an efficient way to manage distributed machine learning or high-performance computing (HPC) workloads. | | Yes |
| namespaced-role-and-bindings | Creates roles and role bindings within a specific namespace to manage fine-grained access control for Kubernetes resources in a limited scope. | | No |
| neuron-device-plugin | Deploys the AWS Neuron device plugin for Kubernetes, enabling support for AWS Inferentia chips to accelerate machine learning model inference workloads. | | Yes |
| storage | Manages persistent storage resources for Kubernetes applications, ensuring that data is retained and accessible across pod restarts and cluster upgrades. | | No |
| training-operators | Installs operators for managing various machine learning training jobs, such as TensorFlow, PyTorch, and MXNet, providing native Kubernetes support for distributed training workloads. | | Yes |
| HyperPod patching | Deploys the RBAC and controller resources needed for orchestrating rolling updates and patching workflows in SageMaker HyperPod clusters. Includes pod eviction and node monitoring. | | Yes |
| aws-efa-k8s-device-plugin | This plugin enables AWS Elastic Fabric Adapter (EFA) metrics on the EKS clusters. | | Yes |

## 3. Test the Chart Locally

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