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.
78 lines
3.5 KiB
Makefile
78 lines
3.5 KiB
Makefile
.PHONY: up down clean migrate test lint data loader pipeline annotate images kind serverless-deploy serverless-destroy gcp-configure gcp-secrets
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VCF ?= data/example.vcf.gz
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TAG ?= latest
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# The loader container reaches docker-compose's Postgres through the host.
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HOST_DB_URL ?= postgresql://rarelens:[email protected]:5432/rarelens
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up:
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docker compose up -d --build
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down:
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docker compose down
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clean: ## also deletes the Postgres and MLflow volumes
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docker compose down -v
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migrate:
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docker compose exec api alembic upgrade head
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test:
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cd api && uv run --extra dev pytest -q
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cd ml && uv run --extra dev pytest -q
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cd pipeline && uv run --no-project --with-requirements requirements.txt --with pytest --with pgserver pytest -q tests
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cd web && npm test
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lint:
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cd api && uv run --extra dev ruff check . && uv run --extra dev mypy app
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cd web && npm run check
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data: ## download the public demo slice: GIAB HG002 + ClinVar, chr22 (see docs/data.md)
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scripts/fetch-demo-data.sh
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loader:
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docker build -t rarelens/loader:dev -f pipeline/loader.Dockerfile pipeline
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pipeline: loader ## dry run: annotate $(VCF) without touching the database
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cd pipeline && nextflow run main.nf -profile docker --vcf ../$(VCF)
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annotate: loader ## make annotate JOB=<job id> [VCF=data/x.vcf.gz]
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@test -n "$(JOB)" || (echo "usage: make annotate JOB=<job id> [VCF=...]"; exit 1)
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cd pipeline && DATABASE_URL=$(HOST_DB_URL) nextflow run main.nf -profile docker \
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--vcf ../$(VCF) --job_id $(JOB)
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images:
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docker build -t rarelens-api:dev api
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docker build -t rarelens-web:dev web
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kind: images
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kind create cluster --name rarelens 2>/dev/null || true
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kind load docker-image rarelens-api:dev rarelens-web:dev --name rarelens
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kubectl apply -k infra/k8s/overlays/local
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kubectl -n rarelens rollout status deploy/postgres deploy/api deploy/web
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@echo "kubectl -n rarelens port-forward svc/web 8080:80 (UI)"
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@echo "kubectl -n rarelens port-forward svc/api 8000:80 (API, used by the UI)"
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serverless-deploy: ## deploy the Cloud Run track: make serverless-deploy PROJECT=<id> [TAG=<sha>]
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@test -n "$(PROJECT)" || (echo "usage: make serverless-deploy PROJECT=<gcp project id> [TAG=<image tag>]"; exit 1)
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@test -n "$$TF_VAR_database_url" || echo "note: TF_VAR_database_url is unset; add -var deploy_cloud_sql=true or export a Postgres URL"
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cd infra/terraform && terraform apply -var project=$(PROJECT) -var image_tag=$(TAG)
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serverless-destroy: ## tear it all down
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cd infra/terraform && terraform destroy -var project=$(PROJECT) -var deletion_protection=false
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gcp-configure: ## one-time: write your GCP project id into the gcp overlay and Argo manifests
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@test -n "$(PROJECT)" || (echo "usage: make gcp-configure PROJECT=<gcp project id>"; exit 1)
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grep -rl __GCP_PROJECT__ infra/k8s/overlays/gcp infra/argo-workflows \
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| xargs sed -i.bak "s/__GCP_PROJECT__/$(PROJECT)/g"
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find infra -name '*.bak' -delete
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gcp-secrets: ## after terraform apply: copy DB URLs from Secret Manager into k8s secrets
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@test -n "$(PROJECT)" || (echo "usage: make gcp-secrets PROJECT=<gcp project id>"; exit 1)
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kubectl -n rarelens create secret generic api-secrets --dry-run=client -o yaml \
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--from-literal=DATABASE_URL="$$(gcloud secrets versions access latest --project $(PROJECT) --secret rarelens-api-database-url)" \
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| kubectl apply -f -
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kubectl -n rarelens create secret generic pipeline-secrets --dry-run=client -o yaml \
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--from-literal=DATABASE_URL="$$(gcloud secrets versions access latest --project $(PROJECT) --secret DATABASE_URL)" \
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| kubectl apply -f -
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