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GCP Compute Engine + Vertex AI support #4

@maksimov

Description

@maksimov

Add Google Cloud Platform as a GPU provider. Looking for contributors with GCP experience — I don't have access to GCP so can't test this myself.

What to implement

A new internal/providers/gcp/ package following the same pattern as internal/providers/aws/:

Discovery

  • Compute Engine GPU VMs — A100, H100, L4, T4 instances (a2, a3, g2 machine families)
  • Vertex AI endpoints — managed GPU inference endpoints

Metrics

  • Cloud Monitoring — CPU utilization, GPU utilization (via compute.googleapis.com/instance/gpu/utilization), network I/O

Pricing

  • Add GCP GPU instance specs to internal/pricing/ (on-demand + preemptible/spot prices)

How the codebase works

The existing analysis rules in internal/analysis/rules.go are provider-agnostic — they operate on models.GPUInstance. Once a GCP provider populates the same struct, all 9 rules work automatically.

Key files to reference:

  • internal/providers/aws/ec2.go — EC2 discovery pattern to follow
  • internal/providers/aws/cloudwatch.go — metrics enrichment pattern
  • internal/models/models.goGPUInstance struct and Source type (add SourceGCE, SourceVertexAI)
  • cmd/gpuaudit/main.go — CLI wiring (add --skip-gcp flag, call provider)

GCP SDK

Use cloud.google.com/go/compute and cloud.google.com/go/monitoring. Auth should use Application Default Credentials (gcloud auth application-default login).

Happy to review PRs and help with architecture decisions — just need someone who can test against real GCP GPU instances.

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    help wantedExtra attention is neededproviderCloud provider supportv0.2Version 0.2 milestone

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