Single service comparison

CCE is Huawei's CNCF-certified managed Kubernetes and the closer functional analog to a GKE Standard cluster: you pick CCE Standard (overlay container networking on user-managed ECS/BMS nodes) or CCE Turbo (VPC-flattened ENI networking, Kata-based isolation), and still own node lifecycle, OS patching, and scale boundaries of 50–2000 nodes per cluster. GKE Standard similarly leaves node pools to the operator, but CCE exposes Huawei-specific abstractions such as Volcano scheduling and HCE/EulerOS node images that have no GKE equivalent; Autopilot's no-node, per-pod billing maps to CCE Autopilot rather than to CCE Standard. Schema and CRD compatibility is high (both run upstream Kubernetes), but admission webhooks, cloud-controller-manager, and volume CSI drivers differ, so treat manifests as portable only after retesting add-ons and PV/PVC storage classes.

CCI is a separate serverless container runtime, not a node-pool cluster, and is the closer match for GKE Autopilot's 'run pods, not infrastructure' posture. CCI bills per-second from 0.25 vCPU, scales pods in seconds, and isolates them in lightweight VMs, but it does not expose a full cluster object or arbitrary daemonsets/node operators, so workloads relying on host-level privileges, hostNetwork, or custom node taints will not port directly. CCI is also positioned as an elastic burst target for CCE (CCE pods scaling to CCI) rather than a wholesale replacement for a full GKE cluster; choose CCI for event-driven or bursty jobs and CCE (Standard/Turbo/Autopilot) for long-lived platform workloads that need cluster-scoped APIs.

Start with an assessment that classifies workloads by operating-model fit: steady-state platform services, stateful workloads, and those needing cluster-scoped APIs or node-level control go to CCE (Standard or Turbo for ENI passthrough/HPC); bursty, event-driven, or per-second-billed pod workloads map to CCI, and Autopilot-style GKE workloads map to CCE Autopilot. Inventory your GKE manifests, CRDs, admission webhooks, ConfigConnector/Terraform automation, Workload Identity bindings, and Persistent Disk Claims, and flag dependencies requiring reimplementation such as ingress-gce, external secrets, or GKE-specific autoscaler profiles. Confirm target-region availability of CCE, CCI, and the GPU/Ascend flavors you need.

For application and configuration migration, retarget container images to Huawei Cloud SWR (or keep an external registry reachable over Direct Connect/VPN), translate GCP Ingress/BackendService into ELB-backed Kubernetes Ingress or LoadBalancer services, and remap GCP PD/Filestore StorageClasses to EVS or SFS CSI classes on CCE. Re-create Workload Identity and IAM patterns with Huawei IAM and CCE service-account token volumes, and port HPA/VPA/Cluster Autoscaler policies to CCE node scaling plus HPA, validating CPU/memory metrics via AOM/Celeborn-equivalent monitoring. CCI workloads need namespace-level resource quotas and no node-affinity; use the documented CCE-to-CCI elastic scaling pattern for burst pods.

Validate feature-by-feature before cutover: run a parallel cluster, smoke-test upgrades, rolling updates, PodDisruptionBudgets, network policies (CCE network policy vs CCI VM isolation semantics), and DNS/CoreDNS behavior, then confirm ELB health checks, TLS termination, and observability feeds (logs to LTS, metrics to AOM/APM). Huawei provides a best-practice path for migrating existing Kubernetes clusters to CCE; use it for kubeconfig/manifest import and for canonical resource translation rather than assuming a one-click tool. Schedule cutover with blue-green or canary traffic shifting through ELB and keep a GKE rollback mirror until autoscaling and failure-injection tests pass.

Mind the cost and operational gaps: GKE Standard charges a per-cluster management fee plus node and network usage, while Autopilot bills per-pod-request; CCE has no comparable control-plane fee line item but you pay for the underlying ECS/BMS/EVS and bandwidth/traffic, while CCE Autopilot and CCI shift cost to per-pod/per-second. Recompute TCO with your real peak concurrency, pod request sizes, egress across AZs/Direct Connect, and retention windows, since cross-AZ and interconnect traffic pricing differs materially from GCP. Anticipate functional gaps where GKE-only add-ons (Config Sync/Policy Controller/Anthos), GCP-specific controllers, or Datadoc-style GKE dashboards have no native Huawei counterpart and will need third-party or self-managed equivalents.