Single service comparison

Huawei IMS exposes public, private, shared, and Marketplace images but has no first-class image-family construct equivalent to Compute Engine's nested family + deprecation lifecycle. In GCP a family points to the latest image and `deprecated`/`obsolete` states steer new launches automatically; on Huawei you select an explicit image ID per rollout and manage successor links manually, so release progression and canary cutover must be orchestrated externally (for example via Packer pipelines plus a self-maintained tag map). Cross-account and cross-project sharing also differ: GCP uses IAM on a project/image resource, while IMS uses in-region image sharing and inter-region/cross-account copy jobs.

Storage, format, and operational boundaries diverge. Compute Engine images are Google-managed objects in a project with built-in regional/multi-regional replication and per-image IAM; IMS stores image files in OBS (redundant, 99.999999999% durability) with optional KMS envelope encryption, and supports importing external files in VHD, VMDK, QCOW2, and RAW formats. IMS is tightly coupled to ECS/EVS as the consumption surface and integrates with Auto Scaling for batch deployment, whereas GCP images are consumed by Compute Engine and MIGs with native family-based update orchestration. Verify per-region availability and OS authorization (e.g., CentOS replacement with HCE) before assuming parity.

Integrations and operational responsibility differ. GCP images integrate with Confidential VMs, Shielded VM, and Confidential Computing, and support startup scripts/instance templates for fleet rollout; Huawei IMS pairs with ECS, EVS, AS, and CCE and relies on Cloud Eye/CTS for observability and audit. Migration tooling also differs: GCP offers Migrate to Virtual Machines and image export; Huawei provides image import/export plus the SMS (Server Migration Service) and MgC migration toolchain, but there is no one-click GCP-to-Huawei image conversion path—image contents, drivers, and cloud-init configuration require rebuild or reimaging.

Assess the source image inventory and classify each GCP image by OS, guest drivers, boot mode (BIOS/UEFI), and consumer workload (standalone ECS, AS group, or CCE node). The target capability is IMS, paired with ECS for consumption and AS/CCE for fleet rollout; do not treat them as interchangeable because batch update behavior depends on which consumer service wraps the image. Confirm Huawei regional availability of the target public/Marketplace image or plan a custom private image build, and check quota for private images and OBS storage in each destination region.

Rebuild images rather than lift-and-shift GCP disk images: there is no supported Google-to-Huawei disk-image conversion. Use Huawei best practices (Packer integration is documented) or the IMS import flow with QCOW2/VMDK/VHD/RAW, install Huawei Cloud drivers and cloud-init, then create a system disk image from an ECS or external file. Carry over startup scripts, software stacks, and configuration management, but re-encode any GCP-specific metadata (project IDs, service accounts, gcloud guest attributes) into Huawei userdata and IAM equivalents.

Validate parity feature-by-feature: boot success on the chosen ECS flavor, application behavior, encryption with KMS, AS launch templates, and rollback. Exercise deprecation-style lifecycle manually via image tagging and version metadata since IMS does not enforce family deprecation. Run parallel canaries in a target region before promoting, and keep a golden-image CI pipeline so each GCP image family branch maps to an explicit IMS image ID rather than an auto-advancing pointer.

Recalculate cost and governance. Compute Engine charges per-second for running vCPU/RAM plus image storage at a per-GB-month rate; Huawei bills ECS runtime, EVS volumes, OBS for image storage, and optional management add-ons, with cross-region/CCE node pricing depending on the consuming service. Model peak load, image retention, and cross-region copy/traffic before cutover, and account for SMS/MgC migration-tool consumption if you also migrate running servers rather than only rebuilding images.