Inner Loop Speed Improvements

Why this matters

Your inner loop is the cycle of edit → build → test → run → see feedback. When it is slow, developers wait, context-switch, and ship less. As a Platform Engineer, you help teams get from save to feedback in seconds, not minutes.

• Real tasks you will do: cut container rebuild time, enable hot reload, configure dependency caches, set up fast test selection, and make local services easy to run.
• Outcomes: faster feature delivery, happier developers, and fewer mistakes introduced under time pressure.

Concept explained simply

Inner loop speed is how quickly a developer sees the result of a code change on their machine (or dev environment). The goal is to reduce delay and friction.

Mental model

Think of the loop time T as the sum of steps plus penalty for interruptions: T = Edit + Build + Test + Run + Feedback + Context Switch. You can improve T by:

• Avoid work: cache, incremental compile, test selection.
• Do less work: smaller builds, slimmer images, fewer services.
• Do work earlier: pre-bake dependencies, warm caches.
• Parallelize: run builds/tests concurrently where safe.
• Move work closer: local services, volume mounts, hot reload.
• Improve feedback: fail fast with clear, actionable messages.

Worked examples

Example 1 — Faster Docker builds for a Node.js service

Problem: Every code change forces a full dependency reinstall in the container.

Solution idea: Use multi-stage Dockerfile, copy dependency manifests first, leverage BuildKit cache, and mount source via volumes in dev.

# syntax=docker/dockerfile:1.5
FROM node:20-slim AS deps
WORKDIR /app
COPY package*.json ./
RUN --mount=type=cache,target=/root/.npm npm ci --prefer-offline --no-audit

FROM node:20-slim AS dev
WORKDIR /app
ENV NODE_ENV=development
COPY --from=deps /app/node_modules /app/node_modules
COPY . .
CMD ["npm","run","dev"]

FROM node:20-slim AS prod
WORKDIR /app
ENV NODE_ENV=production
COPY package*.json ./
COPY --from=deps /app/node_modules /app/node_modules
COPY . .
RUN npm run build
CMD ["node","dist/index.js"]

Why it’s faster: package*.json changes are rare; by copying them first you keep the dependency layer cached across most edits.

node_modules
.git
.gitignore
.env
coverage
dist

Example 2 — Java service with Gradle build cache and test selection

Problem: Each edit triggers a clean build and full test suite.

Solution idea: Turn on Gradle build cache, enable incremental compilation, and run only tests affected by changed files (then run full suite in CI).

// gradle.properties
org.gradle.caching=true
org.gradle.parallel=true
org.gradle.configureondemand=true
org.gradle.daemon=true

// build.gradle.kts (snippet)
tasks.test {
  useJUnitPlatform()
  // Example: only run tests in changed modules when CHANGED_PATHS is provided
  val changed = (System.getenv("CHANGED_PATHS") ?: "")
  if (changed.isNotBlank()) {
    include(changed.split(",").map { "**/*${'$'}it*Test*" })
  }
}

Workflow: on local runs, set CHANGED_PATHS from git diff to limit tests. CI still runs full tests for confidence.

Example 3 — Kubernetes dev loop with live reload

Problem: Rebuilding and redeploying to a cluster takes minutes.

Solution idea: Use a dev tool that syncs files and live-reloads inside containers, or run services locally and proxy cluster dependencies.

1. Run the service locally with volume mounts and hot reload.
2. Point dependencies (DB, queue) to local or cluster endpoints via env vars.
3. Use a file sync or dev sync feature to avoid full image rebuilds on save.
4. Seed local data on startup for realistic behavior.

services:
  api:
    build:
      context: .
      target: dev
    volumes:
      - ./:/app
    environment:
      - DB_URL=postgres://postgres:postgres@db:5432/app
    command: npm run dev
  db:
    image: postgres:15
    environment:
      - POSTGRES_PASSWORD=postgres
    ports:
      - "5432:5432"

Metrics and targets

• Primary metric: time from save to visible feedback (app updated or test result).
• Baseline: measure 5 times, take median.
• Good targets: interpreted languages ~1–3s; compiled services ~3–10s. Start with what’s realistic and ratchet down.

Step-by-step: Diagnose and speed up your inner loop

1. Map the loop
   • List each sub-step: editor save, package manager, compiler, container build, tests, run, view.
   • Note where time and context-switches occur.
2. Measure baseline
   • Warm caches, then measure 5 times for: no-op build, small code change, typical test run.
3. Quick wins (hours)
   • Add .dockerignore and proper Docker layers.
   • Use volume mounts + hot reload; avoid rebuilds for code-only edits.
   • Turn on incremental compilation and local build caches.
   • Run only affected tests by default; full suite in CI.
4. Deeper improvements (days)
   • Prebake dependencies into base images.
   • Split monolith builds; build/test only changed modules.
   • Parallelize tasks; provision a shared remote cache if your build tool supports it.
5. Guardrails
   • Add preflight scripts to verify env and print actionable hints.
   • Document one-command dev: "make dev" or "task dev".

• Checklist for completion:
  • No-op container rebuild < 2s.
  • Small edit to feedback < 5s for compiled, < 3s for interpreted.
  • Command to run only affected tests exists and is the default.
  • One-command dev startup documented.

Exercises

Do these in a throwaway repo or a small service.

Exercise ex1 — Optimize a Dockerfile for fast inner loop

Goal: Rework a Dockerfile so code edits do not reinstall dependencies and dev runs via volume mounts.

1. Create or take a small service (any language) with a Dockerfile.
2. Restructure layers so dependency install happens before copying full source.
3. Add a dev target that mounts source and runs a watch/hot-reload command.
4. Add a .dockerignore to keep the build context lean.
5. Measure: no-op rebuild time and small-edit feedback time.

Exercise ex2 — One-command dev with watch + affected tests

Goal: Provide a single command (e.g., make dev) that starts the app in watch mode and a command that runs only affected tests.

1. Add a Makefile or Taskfile.
2. Implement dev target to run app with hot reload.
3. Add test-changed that detects changed files (vs main) and runs only impacted tests.
4. Seed local DB automatically on startup (optional but recommended).
5. Measure: save-to-feedback for both app and tests.

Common mistakes and self-checks

• Reinstalling dependencies on every change. Self-check: Does changing a single .js file invalidate your dependency layer?
• Building containers for local code edits. Self-check: Can you see changes without docker build?
• Running full test suite locally by default. Self-check: Do you have an affected-tests command?
• Ignoring no-op times. Self-check: Is no-op build under 2s? If not, why?
• Too many services to start. Self-check: Can you stub or mock external services for local runs?

Practical projects

• Dev bootstrap CLI: a single script that verifies tools, starts local services, seeds data, and runs watch mode.
• Test accelerator: a wrapper that finds changed files and runs affected tests, with an escape hatch to run all.
• Container build optimizer: baseline and improve Docker no-op and code-change rebuild times with documented before/after metrics.

Learning path

• Start: measure inner loop and apply quick wins (caching, hot reload, affected tests).
• Next: container image strategy (multi-stage, minimal base images, pre-baked deps).
• Then: build systems and remote caching, module-level builds.
• Advanced: local-cluster hybrids (sync, proxies), hermetic dev environments.

Next steps

• Pick one service and achieve: no-op build < 2s and small-edit feedback < 5s.
• Document one-command dev and share with the team.
• Set a target and track it weekly.

Mini challenge

Within one day, reduce a service’s save-to-feedback time by 30% and write a short changelog of what worked. Tip: target caching and watch mode first.

Quick Test is available to everyone; only logged-in users get saved progress.