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Use GKE rollout sequencing with custom stages to upgrade lower-risk environments first, then a labeled production canary, and finally the rest of production. Define the ordered stages and soak periods declaratively with the documented gcloud YAML workflow or a Terraform resource; put a catch-all stage after each selected subset so no clusters in a fleet are accidentally left out. Custom stages control which clusters go when. They do not change how nodes in a pool are replaced.

How custom-stage sequencing works

GKE groups clusters into fleets, often by environment. A custom-stage sequence can order those fleets and select labeled subsets within a fleet. That makes it possible to test an eligible upgrade in development or staging, apply it to a production canary, and then continue to the remaining production clusters.

Custom sequencing uses the RolloutSequence and Rollout API objects. When clusters in a sequence become eligible for an upgrade target from their release channel, GKE creates a rollout and progresses through its configured stages. It is not a command to immediately upgrade every cluster, nor does manually upgrading the first stage by itself cause the sequence to qualify a version or advance. Progress is tied to the official automatic-upgrade target for the applicable channel.

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Google recommends custom stages for new environments. They provide finer-grained targeting and more rollout controls than the earlier fleet-based sequencing model, but they are not supported in the Google Cloud console.

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Plan the sequence before configuring it

Align upgrade eligibility

For predictable sequencing, Google recommends using the same release channel and minor version across the clusters in a sequence. This helps ensure they are eligible for the same upgrade target. If channels differ, GKE selects a target from the most conservative channel present in the sequence, which can affect when the rollout proceeds.

Choose stages and soak periods

Plan the order around risk and workload criticality. A representative design is:

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Order Stage target Purpose
1 All clusters in the development or testing fleet Expose compatibility issues in a lower-risk environment.
2 All clusters in the staging fleet Validate behavior in a pre-production environment.
3 Production clusters labeled for the canary Observe the upgrade on a limited production subset.
4 Remaining clusters in the production fleet Continue after the canary stage has soaked.

Google’s how-to example uses a seven-day soak after each of three stages. That is an example configuration, not a default or a universal recommendation. Set each soak long enough to observe the signals that matter for your workloads, such as application errors, latency, and operational alerts. A soak is elapsed time in the sequence; it does not replace health checks or application-specific acceptance criteria.

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Configure a canary stage and a production catch-all

  1. Put clusters in the intended fleets. Organize clusters into environment fleets such as testing, staging, and production before defining their rollout order.
  2. Label the production canary clusters. For example, the documented CLI workflow uses gcloud container clusters update with --update-labels. A command can take this form: gcloud container clusters update CLUSTER_NAME --location=LOCATION --update-labels=canary=true. Replace the cluster name and location with your values. The label update can overwrite existing labels, so include any existing labels you need to preserve in the update.
  3. Declare ordered stages and soak durations. Use the documented gcloud YAML workflow or the Terraform resource for rollout sequencing. For a production canary, define a stage in the production fleet with a CEL label selector that begins with resource.labels, followed by a production stage without a selector to cover the remaining clusters.
  4. Add a catch-all stage for every fleet. A stage without a label selector ensures clusters not selected by an earlier subset stage are still covered. If a cluster matches multiple stages in the same sequence, GKE assigns it to the earliest matching stage.
  5. Review the rollout and workload signals during each soak. Monitor rollout status and validate workloads against your own acceptance criteria before relying on progression to the next stage.

The precise manifest structure belongs to the current Google Cloud gcloud or Terraform documentation for the API; do not treat the stage outline above as a copy-and-paste YAML schema.

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Understand when a stage can progress

Maintenance windows and exclusions can delay when GKE starts cluster upgrades. There is also a 30-day maximum upgrade time: if upgrades are still unfinished after that period, a stage can enter its soak phase anyway. Remaining cluster upgrades may continue during the soak. Therefore, entry into soak means the sequence has progressed under this safeguard, not that every cluster has completed upgrading.

A rollout sequence is not an absolute upgrade freeze. Restricting upgrade types through sequencing or using maintenance exclusions does not prevent mandatory automatic upgrades. Plan for that possibility in operational procedures.

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Keep cluster sequencing separate from node replacement

Rollout sequencing determines the order and timing of cluster groups. The node upgrade strategy remains whatever is configured for each node pool. For standard node pools, the documented choices include surge and blue-green upgrades; Autopilot nodes use surge upgrades.

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Node strategy Replacement behavior Capacity consideration
Surge Adds nodes according to the pool’s surge settings during an upgrade. Extra nodes may be required; available resources and quota can constrain progress.
Blue-green Creates a temporary parallel node-pool environment for the upgrade. Node count temporarily doubles, increasing demand for quota and resources.

Before rollout, check Compute Engine quota, resource availability, and reservations for the selected strategy. Insufficient capacity can slow or prevent upgrades even when the cluster-stage sequence itself is configured correctly.

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Choose custom stages or fleet-based sequencing

Approach Targeting and controls Console support Best fit
Custom stages Can select label-matched subsets within a fleet and exposes rollout objects and additional controls, including specifying upgrade types and managing rollouts. No Google Cloud console support. New sequences that need finer control, such as a production canary followed by the remaining production fleet.
Earlier fleet-based model Orders broader fleet groups and has fewer controls. Supported. Existing workflows that depend on console support or do not need subsets within a fleet.

Google recommends custom stages for new environments. The fleet-based model remains the version supported in the console.

Preflight checks for a safer rollout

  • Review current GKE release notes, known issues, release schedule, and API deprecations for the target version. These details change over time.
  • Check control-plane and node version skew against current GKE guidance before selecting an upgrade target.
  • Validate the upgrade in pre-production and use a production canary where appropriate. Google’s GKE best-practices guidance recommends multiple environments to test software and infrastructure changes separately from production.
  • Give minor upgrades additional scrutiny: Google’s documentation notes that they introduce more changes than patch upgrades.
  • Verify node-pool strategy, quota, reservations, and resource headroom before the sequence reaches high-impact clusters.
  • Decide which workload and operational signals must remain acceptable during each soak; the sequencing feature does not define those application-level checks for you.

For release-specific behavior and the currently supported configuration schema, use Google Cloud’s GKE custom-stage rollout, how-to, upgrade, and best-practices documentation. Those details can change as GKE versions and rollout behavior evolve.

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