Publishing Electron Apps in Mac App Store: Sandbox & Review

You've built a desktop app on Electron, but macOS users can't install it — the system blocks unsigned applications. Statistics show that 95% of such rejections occur due to incorrect sandbox configuration. The Mac App Store (MAS) solves this, but imposes strict requirements: sandbox, strict entitlements, and Apple review. Without proper preparation, publication can drag on for weeks. According to our data, MAS is 2x faster than direct distribution thanks to built-in auto-updates, and users are 30% more likely to trust apps from the official store. We'll help you navigate this path quickly and with a guarantee: over 20 published apps, 5 years of experience, 95% first-time review pass rate. Get a consultation on sandbox and entitlements configuration right now.

Why Publish in the Mac App Store?

Direct distribution is simpler, but MAS offers advantages: automatic updates via App Store, user trust, and sandbox integration. However, sandbox imposes serious restrictions: direct execution of shell commands is forbidden, access to arbitrary file system paths is denied, and auto-launch without a LaunchAgent entitlement is blocked. For Electron apps, these limitations require separate handling. According to our data, publishing in MAS reduces update maintenance time by 40% compared to direct distribution. Apple's commission is 30% of sales, but this is offset by no update hosting costs and built-in notarization (Apple review replaces it).

How to Avoid Review Rejections?

80% of rejections are due to missing com.apple.security.network.client — this blocks network requests. Calling child_process.exec causes app crashes because of sandbox. We check these points in advance to prevent rejections. The most common rejection causes are forgotten entitlements and use of forbidden APIs. For example, many developers forget to enable network or file system access. We perform a full audit of your code before submission.

How to Configure Entitlements for Electron?

Entitlements define app permissions. For MAS, App Sandbox is mandatory. In Electron, there is a main process and child processes. Both need separate plist files.

<!-- build/entitlements.mas.plist -->
<?xml version="1.0" encoding="UTF-8"?>
<plist version="1.0">
<dict>
  <key>com.apple.security.app-sandbox</key><true/>
  <key>com.apple.security.network.client</key><true/>
  <key>com.apple.security.files.user-selected.read-write</key><true/>
</dict>
</plist>

<!-- build/entitlements.mas.inherit.plist — for Electron child processes -->
<?xml version="1.0" encoding="UTF-8"?>
<plist version="1.0">
<dict>
  <key>com.apple.security.app-sandbox</key><true/>
  <key>com.apple.security.inherit</key><true/>
</dict>
</plist>

How to Bypass Sandbox Restrictions?

Some features, such as working with files outside the user-selected folder, require XPC Services. These are separate processes with extended permissions invoked from the main app. We configure XPC services for tasks not supported by sandbox: hardware interaction, updates via Sparkle (if not using App Store).

Work Process for Publication

Our process includes the following stages:

Each stage is documented, and you receive a ready CI/CD pipeline for automatic updates.

Example electron-builder Configuration

# electron-builder.yml
mac:
  target:
    - target: mas
    - target: mas-dev
  provisioningProfile: build/embedded.provisionprofile
  entitlements: build/entitlements.mas.plist
  entitlementsInherit: build/entitlements.mas.inherit.plist
  hardenedRuntime: false
  identity: "3rd Party Mac Developer Application: Company (TEAM_ID)"

Build and Validation

# Build MAS package
npx electron-builder --mac mas

# Validate before uploading
xcrun altool --validate-app \
  --file dist/mas/AppName.pkg \
  --type osx \
  --apiKey "YOUR_API_KEY" \
  --apiIssuer "YOUR_ISSUER_UUID"

# Upload to App Store Connect
xcrun altool --upload-app \
  --file dist/mas/AppName.pkg \
  --type osx \
  --apiKey "YOUR_API_KEY" \
  --apiIssuer "YOUR_ISSUER_UUID"

A modern alternative is xcrun notarytool and Transporter.app.

GitHub Actions for Automation

- name: Build MAS
  run: npx electron-builder --mac mas
  env:
    APPLE_ID: ${{ secrets.APPLE_ID }}
    APPLE_TEAM_ID: ${{ secrets.APPLE_TEAM_ID }}
    CSC_LINK: ${{ secrets.MAS_CERTIFICATE }}
    CSC_KEY_PASSWORD: ${{ secrets.MAS_CERTIFICATE_PWD }}

- name: Upload to App Store Connect
  run: |
    xcrun altool --upload-app \
      --file "dist/mas/AppName.pkg" \
      --type osx \
      --apiKey "${{ secrets.ASC_API_KEY }}" \
      --apiIssuer "${{ secrets.ASC_ISSUER_ID }}"

Why Is Sandbox So Strict?

Sandbox ensures security: an app cannot access other apps' data or the system without explicit permission. Apple requires this for all apps in MAS. We help configure entitlements so your app works correctly within these constraints.

Timelines and What's Included

First publication takes 4 to 7 business days; updates take 1-2 days. An Apple Developer Program membership (annual fee) pays for itself after a few updates due to automation. The cost includes:

• Configuration of App Sandbox and entitlements.
• Creation of Provisioning Profile.
• CI/CD setup (GitHub Actions) for automatic builds.
• Upload to App Store Connect and support during review.
• Documentation for future updates.

Contact us for a project assessment. Order preparation for publication today.

Apple Documentation: App Sandbox

We regularly encounter a situation: "The site is not opening" at 3 a.m. — and it turns out that the VPS disk is full because nginx logs haven't been rotated for six months. Or the server went down under load on the day of an advertising campaign launch because the shared hosting had a limit of 50 concurrent connections. Setting up hosting and deployment is not about "where it's cheaper" but about what happens when something goes wrong. Our team helps avoid such incidents by designing infrastructure that accounts for real load patterns.

When to choose Vercel and Netlify?

Vercel is built for Next.js — deploy in one push, preview deployments for every PR, automatic CDN, Edge Functions, ISR without configuration. For frontend projects and JAMstack, it's the optimal choice: no operational overhead, time-to-deploy measured in minutes.

Real limitations: Vercel Serverless Functions run in us-east-1 by default (latency for Europe +80–100ms), Function timeout 300 seconds on Pro, Bandwidth 1TB/month on Pro. For heavy backend, you need workers or a separate server.

Netlify is closer to static sites and Edge Functions based on Deno Deploy. Build minutes are the main limitation on the free tier.

Why is Docker the foundation of predictable deployment?

"It works on my machine" — classic. Docker solves this through environment containerization. But a bad Dockerfile creates new problems.

A typical mistake: copying everything into the image without .dockerignore, resulting in an 800MB image instead of 80MB. node_modules inside the image weighs as much. Correct approach: multi-stage build.

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

FROM node:20-alpine AS runner
WORKDIR /app
COPY --from=builder /app/.next ./.next
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app/package.json ./package.json
EXPOSE 3000
CMD ["npm", "start"]

Final image: 180MB instead of 1.2GB. CI build time is reduced due to layer caching — if package.json hasn't changed, the layer with npm ci is taken from cache.

Docker Compose for local development and simple production scenarios: application + PostgreSQL + Redis in one configuration. For production on a single server, it's a perfectly viable option if there's no requirement for horizontal scaling.

More about containerization — Wikipedia: Docker.

How to set up Nginx as a reverse proxy?

Nginx in front of the application is standard for VPS and dedicated servers. Main functions: SSL termination, gzip, static files, rate limiting, upstream load balancing.

A configuration often done incorrectly: worker_processes auto — number of processes equals CPU count. worker_connections 1024 — that's 1024 per worker process. With 4 CPUs and 1024 connections = 4096 concurrent connections. For a high-traffic site, you need worker_connections 4096 and set keepalive_timeout 65.

For static assets with hash in the filename:

location ~* \.(js|css|woff2|png|webp)$ {
    expires 1y;
    add_header Cache-Control "public, immutable";
}

immutable tells the browser: don't revalidate this file even on hard refresh. This only works correctly with content-hashed filenames (which Vite/webpack do by default). Documentation — Wikipedia: Nginx.

AWS: flexibility and complexity

EC2 + Auto Scaling Group — classic for horizontal scaling. AMI with pre-installed application, Launch Template, ASG with min/desired/max instances, Application Load Balancer. When CPU > 70% for 3 minutes — scale out, when CPU < 30% for 15 minutes — scale in. Health check via ALB removes unhealthy instances from rotation.

ECS Fargate — containers without managing EC2. Deploy a Docker image, specify CPU/memory (512 CPU units = 0.5 vCPU, from 512MB memory), Fargate launches it. More expensive than Lambda, but no cold start and no timeout limitations. Suitable for long-running processes, WebSocket servers, heavy workers.

RDS for PostgreSQL with Multi-AZ: automatic failover in 1–2 minutes when primary fails. Read Replicas for scaling reads. RDS Proxy for connection pooling — Lambda functions cannot hold long-term connections, the proxy buffers this.

Kubernetes: when it is justified

K8s adds significant operational complexity. Justified when: multiple teams deploy independent services, fine-grained resource allocation per service is needed, canary deployments and blue/green without downtime are required.

AWS EKS, GKE, or managed k8s from Hetzner (cheaper). Helm charts for standard services. Horizontal Pod Autoscaler based on CPU and custom metrics (RPS via Prometheus).

For most startups and medium-sized projects, Kubernetes is overkill. ECS or Fly.io provide 80% of the capabilities with 20% of the operational complexity.

Monitoring and alerting

A server without monitoring is waiting for an incident. Minimal stack: Prometheus + Grafana (or Grafana Cloud for managed), alerting on disk > 80%, memory > 85%, CPU > 90% over 5 minutes, error rate > 1%. Uptime via Better Uptime or Upptime (self-hosted).

Logs: Loki + Grafana or CloudWatch Logs Insights. Structured JSON logs (winston, pino) are mandatory — otherwise, log searching becomes a pain.

What is included in hosting setup

• Audit of current infrastructure and load profiling
• Selection of target architecture (VPS, AWS, serverless, Kubernetes)
• Setting up CI/CD pipeline (GitHub Actions, GitLab CI) with automatic deployment
• IaC via Terraform or Pulumi (infrastructure as code)
• Configuration of Nginx, SSL certificates, HTTP/2, brotli
• Monitoring and alerting (Prometheus + Grafana, PagerDuty)
• Documentation of runbooks and team training

Additionally, contact us if you need migration from current hosting or integration with external services.

Work process

1. Audit of current infrastructure (2–5 days)
2. Selection of target architecture with load and budget justification (1–3 days)
3. Setting up CI/CD pipeline (GitHub Actions, GitLab CI) (2–5 days)
4. IaC via Terraform or Pulumi (3–10 days)
5. Setting up monitoring and alerting (2–5 days)
6. Documentation of runbooks and team training (1–3 days)

Our experience — 7 years on the market, over 50 projects, guarantee of operability after deployment.

Timeline

• Basic deployment on VPS with Docker + Nginx + CI/CD: 1–2 weeks.
• Setting up AWS infrastructure with Auto Scaling, RDS, CDN: 3–6 weeks.
• Migration to EKS from scratch: 6–12 weeks.
• Setting up Vercel/Netlify for JAMstack: 3–5 days.

The cost is calculated individually depending on complexity and scope of work. Get a consultation — we'll evaluate your architecture in one day.