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Case Study: Reproducing a 7-Day Micro-App Build with Ephemeral Environments and LLM Helpers

UUnknown

2026-02-07

9 min read

Reproduce Rebecca Yu's 7-day micro-app using ephemeral sandboxes, LLM helpers, CI gates, and templates—step-by-step artifacts to run in minutes.

Hook — Your team needs fast, reliable test environments that don't cost a fortune

If your CI feedback is slow, tests flake in shared environments, or spin-ups blow the cloud budget, this case study is for you. We'll reproduce Rebecca Yu's seven-day micro-app build — the "Where2Eat" vibe-coding project — but with an enterprise-grade twist: ephemeral sandboxes, LLM-assisted development, reproducible builds, CI gates, and deployment templates. By the end you'll have concrete artifacts and templates to run the same micro-app pipeline in minutes, not days.

Executive summary (most important first)

In 2026, micro-apps and LLM-assisted development are mainstream. This guide shows how to reproduce a seven-day micro-app prototype using ephemeral sandboxes and automation so that every commit produces a reproducible build. You'll get:

Full reproducible artifact list: Dockerfile, GitHub Actions workflow, Kubernetes + Helm templates, Terraform module for ephemeral sandboxes.
LLM-assisted development playbook: prompts, patterns, local & CI usage, and guardrails to avoid hallucinations.
CI gates and policies: deterministic test gates, contract tests, cost checks, and auto-teardown rules.
Step-by-step reproduction instructions: spin up, test, deploy, and tear down within ephemeral sandboxes.

Why reproduce a seven-day micro-app in 2026?

By late 2025 and into 2026, industry momentum favors rapid, single-developer micro-app prototypes powered by LLMs and composable cloud infra. For engineering teams, reproducing such prototypes deterministically is critical to: reduce wasted cloud spend, integrate prototypes into CI/CD safely, and onboard non-dev stakeholders quickly.

Key 2026 trends this case study leverages

LLM-assisted code generation with robust function-calling and RAG to reduce hallucinations.
Ephemeral sandbox platforms (self-hosted or SaaS) that provision per-PR environments with policy controls and cost budgets.
Shift-left security and deterministic test gates in CI (unit, contract, and infra as code validations).
Reproducible build artifacts (buildpacks, OCI images, and content-addressed caches) to guarantee identical deployables across environments.

Goals and constraints for the reproduction

Reproduce Where2Eat's feature set (restaurant recommendations, shared preferences, simple web UI) within a seven-day cadence—but with a reproducible pipeline and safety gates suitable for team use.

Goal: From repo commit to running sandbox in <10 minutes.
Constraints: Keep costs under a configured budget per sandbox, require passing CI gates for any persistent deploy, and ensure infra is destroyed after 24 hours unless explicitly promoted.

Technology stack (suggested)

Backend: Node.js 20 (or Deno), Fastify/Express, Prisma or Postgres client
Frontend: React + Vite + TypeScript
Database: PostgreSQL (ephemeral managed instance or container)
Infrastructure: Docker, Kubernetes (or lightweight K3s), Helm, Terraform
CI: GitHub Actions (example) with self-hosted runners or ephemeral runner pools
LLM: hosted API with function-calling + RAG (local LLM fallback for privacy-sensitive orgs)
Sandboxing: ephemeral environment platform (API-driven) or mytest.cloud-like service

Project layout and reproducible build artifacts

Use a monorepo layout for the micro-app to keep build steps deterministic.

// repo structure
/where2eat
├─ /web (React + Vite)
├─ /api (Node + Fastify)
├─ /infra
│  ├─ Dockerfile.api
│  ├─ Dockerfile.web
│  ├─ k8s/helm-chart
│  └─ terraform/sandbox-module
├─ .github/workflows/ci.yml
└─ llm/prompts.md

Dockerfile (API) - reproducible, small, content-addressed

FROM node:20-alpine AS build
WORKDIR /app
COPY api/package*.json ./
RUN npm ci --production=false
COPY api/ ./
RUN npm run build

FROM node:20-alpine AS runtime
WORKDIR /app
COPY --from=build /app/dist ./dist
COPY api/package*.json ./
RUN npm ci --production
CMD ["node", "dist/index.js"]

Helm values (k8s) - defaults for ephemeral sandboxes

replicaCount: 1
image:
  repository: ghcr.io/org/where2eat-api
  pullPolicy: IfNotPresent
resources:
  limits:
    cpu: "500m"
    memory: "256Mi"
  requests:
    cpu: "250m"
    memory: "128Mi"
env:
  - name: DATABASE_URL
    value: "postgres://user:pass@postgres:5432/where2eat"
lifecycle:
  preStop:
    exec:
      command: ["/bin/sh", "-c", "sleep 5"]

LLM-assisted development: practical playbook

LLMs accelerate scaffolding, tests, and integration code, but you need guardrails to keep outputs reliable and auditable.

LLM usage patterns

Scaffold generation: Use prompts that output structured files (JSON list of files) to avoid mismatch.
Test generation: Ask the model to produce unit tests + table-driven cases and include expected responses for deterministic assertions.
RAG for domain data: Provide a domain context (restaurant taxonomy, ratings schema) to reduce hallucination when LLM suggests business logic.
Function calling: Use function-calling to let the model return typed outputs for automatic commit or PR creation.

Sample LLM system + user prompt (2026 best practice)

// System
You are an assistant that produces exact file contents. Always wrap files in a JSON object {"path":"...","content":"..."}.

// User
Generate an Express route /recommend that accepts POST {preferences:[string], location:{lat,lng}} and returns top 3 restaurants with id,name,score.
Include Prisma schema and one unit test using jest.

Tips to avoid hallucination

Use small, deterministic LLMs for code scaffolding (fine-tuned on your codebase where possible).
Pin model versions and enable response validation in the pipeline.
Always run generated code through unit and contract tests in ephemeral sandboxes before merging.

CI pipeline: gates, reproducible builds, and ephemeral sandboxes

The CI pipeline must produce content-addressed OCI images, run tests in a per-PR ephemeral sandbox, validate contracts, run cost policy checks, and destroy the sandbox automatically.

GitHub Actions example (abridged)

name: CI
on: [pull_request]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Build images
        run: |
          docker build -f infra/Dockerfile.api -t ghcr.io/${{ github.repository }}/where2eat-api:${{ github.sha }} ./api
          docker build -f infra/Dockerfile.web -t ghcr.io/${{ github.repository }}/where2eat-web:${{ github.sha }} ./web
      - name: Push images
        uses: docker/build-push-action@v4
        with:
          push: true
          tags: ghcr.io/${{ github.repository }}/where2eat-api:${{ github.sha }}

  ephemeral_sandbox:
    needs: build
    runs-on: ubuntu-latest
    steps:
      - name: Create sandbox
        run: |
          curl -X POST "https://sandbox.example/api/v1/environments" \
            -H "Authorization: Bearer ${{ secrets.SANDBOX_TOKEN }}" \
            -d '{"name":"pr-${{ github.event.number }}","image":"ghcr.io/${{ github.repository }}/where2eat-api:${{ github.sha }}","ttl":86400}'
      - name: Run tests in sandbox
        run: |
          # wait for endpoints, run integration tests
          ./scripts/wait-for-sandbox.sh $SANDBOX_URL
          npm run test:integration -- --baseUrl=$SANDBOX_URL
      - name: Destroy sandbox
        if: always()
        run: |
          curl -X DELETE "https://sandbox.example/api/v1/environments/pr-${{ github.event.number }}" \
            -H "Authorization: Bearer ${{ secrets.SANDBOX_TOKEN }}"

CI gates to enforce (should be automated)

Unit test suite (fast)
Contract tests (OpenAPI/GraphQL schema validation)
Integration tests against ephemeral sandbox (end-to-end API flows)
Security static analysis (SAST), dependency checks, license checks
Cost policy: estimate expected cloud spend for the sandbox and fail if above threshold

Provisioning ephemeral sandboxes: Terraform module

Use a Terraform module to create namespaced resources and a managed Postgres instance tied to the sandbox lifecycle.

terraform {
  required_providers {
    kubernetes = { source = "hashicorp/kubernetes" }
  }
}

module "sandbox" {
  source = "git::https://repo/terraform-modules.git//sandbox?ref=v1.0"
  name   = "pr-${var.pr_number}"
  ttl    = 86400
  image  = var.image
}

Reproducible builds: caching and provenance

Content-addressed images (OCI) + SBOMs and build metadata ensure the same source + dependencies produce identical images.

Generate SBOMs for each build (CycloneDX/SPDX).
Record build provenance (git sha, builder version, base image digest).
Store artifacts in an immutable registry and refer by digest (not tag) in infra manifests.

Observability and debugging ephemeral sandboxes

Ephemeral sandboxes must provide quick access to logs, traces, and downloadable core dumps. Add lightweight observability agents with TTL-aware sampling to reduce cost.

Expose an ephemeral logs UI link in the PR.
Capture request traces to a short-lived tracing back-end with redaction rules.
Enable pprof/metrics endpoint guarded by a one-time token stored in the sandbox metadata.

Cost control and lifecycle management

Enforce budgets per sandbox and auto-teardown policies to prevent runaway costs.

Set TTL (e.g., 24h) on every sandbox; require manual promotion for longer life.
Provide a cost-estimate step in CI that cancels the pipeline when predicted cost > budget.
Use small instance types and resource requests/limits in k8s manifest defaults.

Step-by-step reproduction checklist (practical)

Clone the repo: git clone --recurse-submodules git@github.com:org/where2eat.git
Install dev tools: Node 20, Docker 24, Terraform 1.6+, kubectl
Build images locally: docker build -f infra/Dockerfile.api -t where2eat-api:local ./api
Run local sandbox (k3d or Docker Compose): ./scripts/start-local-sandbox.sh
Run LLM code generation (optional): ./scripts/llm/generate-scaffold.sh --prompt-file=llm/prompts.md
Run tests: npm run test && npm run test:integration -- --baseUrl=http://localhost:8080
Create PR: push branch, open PR — CI will create an ephemeral sandbox and run integration tests.
Review CI gates and logs; promote to staging by running the promote script if all gates pass.

Example artifact: integration test (Jest + Supertest)

const request = require('supertest');
  const baseUrl = process.env.BASE_URL || 'http://localhost:8080';

  describe('POST /recommend', () => {
    it('returns 3 scored restaurants', async () => {
      const res = await request(baseUrl)
        .post('/recommend')
        .send({ preferences: ['sushi','quiet'], location: { lat: 37.77, lng: -122.41 } });
      expect(res.statusCode).toBe(200);
      expect(res.body).toHaveLength(3);
      res.body.forEach(r => {
        expect(r).toHaveProperty('id');
        expect(r).toHaveProperty('score');
      });
    });
  });

Advanced strategies and 2026 predictions

The tools and patterns shown here are aligned with 2026 trends. Expect the following trajectories and adopt them early:

ModelOps maturity: production LLMs will adopt standardized model cards and reproducible model checkpoints; pin model versions in pipelines.
Ephemeral infra ecosystems: Sandbox providers will offer multi-cloud ephemeral environments with cost forecasting and automated drift detection.
Secure RAG: Retrieval pipelines will be standard for domain-specific logic to reduce hallucinations in business logic generation.
Composability: Micro-app features will increasingly be assembled from secure, tested microservices and sidecar function templates rather than ad-hoc code blobs.

Lessons learned (from reproducing the 7-day build)

Reproducible builds are the difference between a prototype that delights and a prototype that becomes technical debt.

Start with small, deterministic components and make every artifact immutable.
Use ephemeral sandboxes for integration tests to eliminate "works on my machine" issues.
Keep LLM outputs auditable—store prompts, responses, and validations as part of build provenance.
Automate teardown and cost checks to keep cloud spend predictable.

Checklist before merging a micro-app into mainline

All unit tests pass locally and in CI
Integration tests pass in an ephemeral sandbox created by CI
SBOM and build metadata published and linked in PR
Cost estimate under budget and TTL set
LLM-generated code validated with tests and annotated in CHANGELOG
Security scan results reviewed (SAST/Deps)

Reproducing Where2Eat — commands recap

# clone
git clone git@github.com:org/where2eat.git
cd where2eat

# local build
docker build -f infra/Dockerfile.api -t where2eat-api:local ./api
./scripts/start-local-sandbox.sh

# run tests
BASE_URL=http://localhost:8080 npm run test:integration

# push and open PR
git push origin feature/quick-recommend
# open PR; CI will create ephemeral sandbox and run integration tests

Final thoughts

Reproducing a seven-day micro-app build with enterprise-ready reproducibility requires design choices that favor immutability, automation, and policy enforcement. The patterns here — ephemeral sandboxes, content-addressed builds, CI gates, and LLM-assisted but audited development — let teams move at the speed of prototypes while keeping reliability, cost, and security under control.

Call to action

Ready to reproduce this pipeline in your org? Start by forking the sample repo, applying the Terraform sandbox module to your environment, and running the CI workflow on a test branch. If you want a guided implementation, contact our customer engineering team for a 2-hour workshop to wire your existing CI into ephemeral sandboxes and LLM-safe workflows.

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