Kemal Yaylali
11fb6b3d73
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.
17 lines
1.1 KiB
Terraform
17 lines
1.1 KiB
Terraform
locals {
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registry = "${var.region}-docker.pkg.dev/${var.project}/rarelens"
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# join("", ...) rather than one(...): with count = 0 these collapse to "" instead of null.
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db_credentials = "${join("", google_sql_user.api[*].name)}:${join("", random_password.pg[*].result)}"
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db_name = join("", google_sql_database.rarelens[*].name)
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db_private_ip = join("", google_sql_database_instance.pg[*].private_ip_address)
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# The API reaches Cloud SQL through its cloud-sql-proxy sidecar on localhost; pipeline tasks
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# (Google Batch VMs, Argo pods) use the private IP inside the VPC. With deploy_cloud_sql = false
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# both use the URL you supplied, which is expected to be reachable over TLS.
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api_database_url = var.deploy_cloud_sql ? "postgresql+asyncpg://${local.db_credentials}@127.0.0.1:5432/${local.db_name}" : var.database_url
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pipeline_database_url = var.deploy_cloud_sql ? "postgresql://${local.db_credentials}@${local.db_private_ip}:5432/${local.db_name}" : var.database_url
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pipeline_sa_member = "serviceAccount:${google_service_account.pipeline.email}"
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}
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