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Oracle Cloud Infrastructure Kubernetes Engine (OKE) just got even better for high-performance workloads. You can now launch **managed node pools** directly into OCI Compute Clusters with RDMA networking — delivering ultra-low latency communication between worker nodes without giving up the operational simplicity of managed nodes.

This is a major win for distributed AI training, fine-tuning, multi-node inference, and other HPC-style workloads on Kubernetes.

Why RDMA Matters for Kubernetes

• Ultra-low latency (single-digit microseconds) between nodes
• High-bandwidth, direct memory access between GPUs across hosts
• Significantly better scaling efficiency for multi-node AI/ML jobs
• Keeps expensive GPUs utilized instead of waiting on network transfers

Key Benefits of This Release

• Full managed node pool experience (auto-scaling, upgrades, node replacement, cordon/drain)
• No more need for self-managed nodes just to get RDMA
• OKE automatically enables the required HPC plugins for RDMA
• Perfect for large-scale distributed training and inference

How to Use RDMA with OKE Managed Node Pools

Prerequisites

• Use an enhanced OKE cluster
• The Compute Cluster must exist and be in ACTIVE state
• Use an RDMA-capable bare metal shape
• Placement must be in the same availability domain as the Compute Cluster
• Do not specify fault domains (managed by Compute service)

Required IAM Policy

allow any-user to {COMPUTE_CLUSTER_LAUNCH_INSTANCE}
  in compartment <compartment_name>
  where request.principal.type = 'nodepool'
    and target.resource.id = '<compute_cluster_OCID>'

Creating a Managed Node Pool with RDMA (Console)

1. In the OCI Console, go to your enhanced OKE cluster
2. Create a new managed node pool
3. Under Advanced Options → Add a Compute Cluster:
   • Select the compartment
   • Select the Compute Cluster
4. Choose an RDMA-supported shape
5. Configure placement in the matching availability domain
6. Create the node pool

OKE will automatically launch instances into the Compute Cluster with RDMA enabled.

Best Practices

• Use enhanced clusters for all new workloads
• Start with smaller clusters to validate performance gains
• Monitor GPU utilization and inter-node communication metrics
• Combine with OKE autoscaling for dynamic workloads
• Plan for the fact that Compute Cluster cannot be changed after node pool creation

Conclusion

With RDMA support for managed node pools, OKE now delivers the best of both worlds: the operational simplicity and automation of managed Kubernetes nodes combined with the ultra-low latency networking required for large-scale AI and HPC workloads.

Whether you’re doing distributed training, multi-node inference, or any communication-intensive workload, you can now take full advantage of OCI’s high-performance Compute Clusters without sacrificing managed node benefits.