fix: overhaul the platform skeleton, add a serverless deployment track
An end-to-end audit found the repo could not build, test or run as shipped. This fixes every finding, then adds a Cloud Run track so the demo costs about £1/month idle instead of ~£150. CI (red on its first run) - api: setuptools could not build the package (flat layout with app/ and alembic/) - web: missing @types/node; `vitest run` exited 1 with no test files - pipeline: the stub run needed a gitignored VCF, and no process had a stub block - ruff pinned, mypy configured, DB tests on real Postgres (pgserver locally, service in CI) ML serving (scores were meaningless) - the registered model now carries its own feature engineering and returns predict_proba, so serving sends raw columns and cannot drift from training - resolve by registry alias (stages are deprecated in MLflow 3) and record the real version; re-scoring upserts instead of failing on the unique constraint - ClinVar labels parsed from VEP's lowercase terms Pipeline - exact ref/alt recovered from a CHROM_POS_REF_ALT VCF ID; loading is idempotent - job status reaches running/failed/succeeded, so the UI stops polling dead jobs - DATABASE_URL travels in the environment or a Nextflow secret, never on a command line - VEP cache and plugins staged as inputs; the gcp profile runs tasks on Google Batch Deployment - the API serves /api (matching the ingress); the web app reads its API URL at runtime - migrations run in an init container under a Postgres advisory lock - terraform: custom VPC shared with Batch, private Cloud SQL, API enablement, Workload Identity bindings, Secret Manager, deletion protection - serverless track, now the default: Cloud Run services scaling to zero, a Cloud Run job for the Nextflow driver, and Neon or Cloud SQL behind one DATABASE_URL secret. GKE and Argo remain, behind -var deploy_kubernetes=true. See docs/cloud.md. Correctness and security - 409 on duplicate sample names, 422 on bad paging, natural chromosome ordering, wider VEP text columns, enum dropped on downgrade, the sample's assembly actually used - vcf_uri restricted to gs:// objects or files under the data root, blocking option injection - CORS restricted to configured origins; `make down` no longer deletes volumes Data - docs/data.md records the peer-reviewed, openly licensed sources (GIAB HG002, ClinVar, gnomAD) with citations and an honest evaluation plan; `make data` fetches a chr22 slice Verified: api 50 tests, ml 18, loader 16, web 12; ruff, mypy, svelte-check, terraform validate and both kustomize overlays clean.
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@@ -1,6 +1,7 @@
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# Workload Identity Federation: GitHub Actions pushes images without long-lived keys.
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resource "google_iam_workload_identity_pool" "github" {
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workload_identity_pool_id = "github"
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depends_on = [google_project_service.enabled]
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}
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resource "google_iam_workload_identity_pool_provider" "github" {
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@@ -29,22 +30,66 @@ resource "google_artifact_registry_repository_iam_member" "ci_push" {
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member = "serviceAccount:${google_service_account.ci.email}"
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}
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# Runtime identities (bound to k8s ServiceAccounts via GKE Workload Identity)
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resource "google_service_account" "api" { account_id = "rarelens-api" }
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# Runtime identities, bound to Kubernetes ServiceAccounts in namespace "rarelens" via GKE
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# Workload Identity (the gcp overlay annotates the k8s side).
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resource "google_service_account" "api" { account_id = "rarelens-api" }
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resource "google_service_account" "pipeline" { account_id = "rarelens-pipeline" }
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resource "google_service_account_iam_member" "api_workload_identity" {
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count = var.deploy_kubernetes ? 1 : 0
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service_account_id = google_service_account.api.name
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role = "roles/iam.workloadIdentityUser"
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member = "serviceAccount:${var.project}.svc.id.goog[rarelens/rarelens-api]"
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}
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resource "google_service_account_iam_member" "pipeline_workload_identity" {
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count = var.deploy_kubernetes ? 1 : 0
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service_account_id = google_service_account.pipeline.name
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role = "roles/iam.workloadIdentityUser"
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member = "serviceAccount:${var.project}.svc.id.goog[rarelens/rarelens-pipeline]"
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}
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resource "google_project_iam_member" "api_sql" {
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project = var.project
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role = "roles/cloudsql.client"
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member = "serviceAccount:${google_service_account.api.email}"
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}
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resource "google_project_iam_member" "api_pubsub" {
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project = var.project
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role = "roles/pubsub.publisher"
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member = "serviceAccount:${google_service_account.api.email}"
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resource "google_pubsub_topic_iam_member" "api_publish" {
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topic = google_pubsub_topic.vcf_uploaded.name
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role = "roles/pubsub.publisher"
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member = "serviceAccount:${google_service_account.api.email}"
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}
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resource "google_pubsub_subscription_iam_member" "pipeline_subscribe" {
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subscription = google_pubsub_subscription.vcf_uploaded_argo.name
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role = "roles/pubsub.subscriber"
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member = local.pipeline_sa_member
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}
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resource "google_storage_bucket_iam_member" "pipeline_data" {
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bucket = google_storage_bucket.data.name
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role = "roles/storage.objectAdmin"
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member = "serviceAccount:${google_service_account.pipeline.email}"
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member = local.pipeline_sa_member
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}
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resource "google_artifact_registry_repository_iam_member" "pipeline_pull" {
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repository = google_artifact_registry_repository.images.name
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location = var.region
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role = "roles/artifactregistry.reader"
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member = local.pipeline_sa_member
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}
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# Nextflow's google-batch executor submits Batch jobs that run as the pipeline SA itself.
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resource "google_project_iam_member" "pipeline_batch" {
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for_each = toset(["roles/batch.jobsEditor", "roles/batch.agentReporter", "roles/logging.logWriter"])
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project = var.project
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role = each.value
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member = local.pipeline_sa_member
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}
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resource "google_service_account_iam_member" "pipeline_act_as_self" {
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service_account_id = google_service_account.pipeline.name
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role = "roles/iam.serviceAccountUser"
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member = local.pipeline_sa_member
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}
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