chore: optimize docker image to alpine, add job-level ci conditions, and add deployment docs#9
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kenneth-loto merged 2 commits intoJul 1, 2026
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Merges the completed User module with create, update, and delete endpoints and test coverage, improved Prisma error messages for P2002, P2025, and P2003, enableShutdownHooks for graceful termination, onPoolError logging in PrismaService, the corrected e2e test, readme fixes, and the rootDir tsconfig.build.json fix resolving the start:prod build path bug from develop into main.
…and add deployment docs - switch Dockerfile base from node:22-slim to node:22-alpine reducing image size from 907mb to 406mb - add --omit=peer to npm install preventing @prisma/client from pulling prisma cli and typescript into the production image - prune wasm query compiler files keeping only postgresql and dropping the other four database engines - move 14 step-level if conditions in ci.yml to job-level so skipped jobs do not provision runners at all - create DEPLOYMENT.md with full deploy guide - add deployment section to README.md - create .env.example with all env var names and empty values
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Summary
Cuts the Docker image size by 55% with an Alpine base and dependency pruning, reduces CI runner cost by moving change detection conditions to job level, and adds deployment documentation.
What's Changed
node:22-slimtonode:22-alpine, reducing the production image from 907 MB to 406 MB--omit=peerto the install step preventing@prisma/clientfrom pulling the Prisma CLI and TypeScript compiler into the production layerif: needs.changes.outputs.code == 'true'conditions inci.ymlto job level so skipped jobs don't provision runners, saving runner minutes on non-code pushesDEPLOYMENT.mdwith a full deploy guideREADME.md.env.examplelisting all required environment variable names with empty valuesWhy
The 907 MB image was primarily bloated by peer dependencies pulled in transitively by
@prisma/clientand by four WASM query compiler files for database engines the app never uses. Alpine and--omit=peerare low-risk changes for a NestJS app with no native module dependencies. Moving change detection to job level rather than step level means the runner is never provisioned at all for non-code changes, not just skipped partway through, which is a meaningful cost reduction on a busy branch.