DPF Operator Version Migration Guides
This document describes the process of upgrading between different versions of the DPF Operator.
Prerequisites
Before starting the upgrade process, ensure you have the following Helm Prerequisites installed and configured.
Further prerequisites include:
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All DPF Operator components MUST be in a ready state
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All DPUs MUST be in a ready and healthy state
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Always review the release notes for the version you're upgrading to
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Release notes contain critical information about:New features and capabilitiesBug fixes and improvementsBreaking changes and migration requirementsKnown issues and workaroundsConfiguration changes that may be required
Verifying Readiness
You can verify the readiness of your DPF Operator and DPUs using dpfctl or kubectl:
Using dpfctl (recommended):
# Check overall DPF Operator status
dpfctl describe all --show-resources=dpfoperatorconfig
# Check all conditions for troubleshooting
dpfctl describe all --show-resources=dpfoperatorconfig --show-conditions=all
The dpfctl tool provides a more user-friendly view of the DPFOperatorConfig status and all related conditions, making it easier to identify validation issues.
Using kubectl:
kubectl get dpfoperatorconfig -o yaml
All status conditions in the status section should be True, and the version field should match the current DPF Operator version.
Supported Upgrade Path (n-1 Policy)
Important: DPF Operator follows an n-1 upgrade policy with the version pattern year.month.patchVersion. You can upgrade from the previous release version to the current release version. Patch-level upgrades within the same minor version are always allowed.
✅ Supported:
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v25.7.0 → v25.10.0
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v25.7.0 → v25.7.1
❌ Not Supported:
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v25.4 → v25.7 (unsupported version upgrade)
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v25.7 → next GA release (skipping version v25.10)
Why this matters: Skipping versions can lead to:
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Failed upgrades due to missing intermediate API changes
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Data corruption or loss
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Incompatible resource states
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Unsupported configuration combinations
Prevalidation
Before the DPF Operator upgrades any components, the system performs prevalidation checks to ensure the cluster is in a safe state for the upgrade. These validations are automatically executed and must pass before the upgrade can continue.
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Version Compatibility ValidationDPF Version Check: Validates that the current DPF version is compatible with the target versionSupported Upgrade Path: Ensures you're upgrading from a supported version (n-1 policy)
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System Components ReadinessThe operator validates that all critical system components are ready for upgrade
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DPU State ValidationDPU Readiness: All DPUs must be in a ready stateDPF Version Compatibility: Each DPU's DPF version must be compatible with the upgradeDPU Health: All DPUs must be healthy and operational
Validation Failure Handling
If any validation fails:
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Upgrade Blocked: The upgrade process is automatically halted
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Status Updates: The
DPFOperatorConfigstatus reflects the validation failure
Status Monitoring
You can monitor prevalidation status using either dpfctl or kubectl as described in the prerequisites above. The DPFOperatorConfig status will indicate whether prevalidations have passed or failed. All conditions must be True for the upgrade to proceed.
What to Do Next
After completing your DPF Operator upgrade, follow these steps to ensure everything is working correctly:
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Verify DPFOperatorConfig Status: Verify that your DPFOperatorConfig custom resource is in a ready state and all conditions are met.
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Update to Supported BFB and DPUFlavor: Create the new BFB object and DPUFlavor object according to the new guide. Review and update your DPUDeployment/DPUSet resources as needed to reference those objects to make the system compatible with the new operator version.
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Update DPUServices: Review and update your DPUDeployment/DPUService resources to use services that are compatible with BFB version and operator version.
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Monitor the Upgrade: Use
dpfctl describe allto monitor the reconciliation process and ensure all resources reach ready state.
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