Startup Infrastructure Checklist: From MVP to Scale

The Infrastructure Trap

Startups fail in two ways with infrastructure: they over-engineer from day one (Kubernetes cluster for 10 users) or they under-invest until scaling is an emergency (single server with no backups serving 10,000 users).

This checklist maps infrastructure to your actual stage. At TechSaaS, we have guided dozens of startups through this progression. The key insight: your infrastructure should be boring enough that you can focus on your product.

Stage 1: Pre-Launch (0 Users)

Goal: Ship something. Anything. As fast as possible.

Must Have

• Single server or PaaS (Vercel, Railway, Fly.io, or a VPS)
• PostgreSQL database (managed or self-hosted)
• Git repository (GitHub, Gitea, GitLab)
• Basic CI (run tests on push)
• Domain name and DNS
• SSL/TLS (Let's Encrypt or Cloudflare)

Nice to Have

• Staging environment
• Error tracking (Sentry/GlitchTip)
• Basic logging (stdout to a file)

Skip

• Kubernetes
• Microservices
• Multi-region
• CDN
• Load balancer
• Message queues
• Cache layer

Estimated cost: $5-60/month

# This is all you need for MVP
# docker-compose.yml
services:
  app:
    build: .
    ports:
      - "3000:3000"
    environment:
      DATABASE_URL: postgres://user:pass@db:5432/myapp
    depends_on:
      - db

  db:
    image: postgres:16-alpine
    volumes:
      - pgdata:/var/lib/postgresql/data
    environment:
      POSTGRES_PASSWORD: change-me

volumes:
  pgdata:

Stage 2: First Users (1-100 Users)

Goal: Validate the product. Start collecting data. Fix obvious reliability issues.

Add Now

• Automated database backups (daily, tested restore)
• Environment variables for all secrets (never in code)
• Health check endpoint (/health)
• Basic uptime monitoring (UptimeRobot, Uptime Kuma)
• Email delivery (transactional emails via SendGrid/Postmark/Resend)
• Error tracking in production (GlitchTip, Sentry)
• HTTPS everywhere

Simple Backup Script

#!/bin/bash
# /opt/backup.sh — run via cron daily at 3am
DATE=$(date +%Y-%m-%d)
BACKUP_DIR=/backups

# Database backup
pg_dump -h localhost -U myapp myapp_db | gzip > "$BACKUP_DIR/db-$DATE.gz"

# Keep last 7 days
find $BACKUP_DIR -name "db-*.gz" -mtime +7 -delete

# Optional: upload to S3 or remote storage
# aws s3 cp "$BACKUP_DIR/db-$DATE.gz" s3://my-backups/

Skip Still

• Kubernetes
• Microservices
• Multi-region
• Dedicated cache layer

Estimated cost: $15-100/month

Stage 3: Growing (100-1,000 Users)

Goal: Reliability becomes important. Users expect uptime. Performance matters.

Add Now

• Reverse proxy (Traefik or Nginx) with proper headers
• Redis for sessions and caching
• Job queue for background tasks (BullMQ, Celery)
• Structured logging (JSON format, not plain text)
• Application metrics (response times, error rates)
• Monitoring dashboard (Grafana)
• CI/CD pipeline (automated deploy on merge to main)
• Staging environment that mirrors production
• Rate limiting on API endpoints
• Security headers (CSP, HSTS, X-Frame-Options)
• Dependency vulnerability scanning

Infrastructure Upgrade

services:
  app:
    build: .
    deploy:
      replicas: 2  # Basic redundancy
    labels:
      - "traefik.enable=true"
      - "traefik.http.routers.app.rule=Host(`app.company.com`)"

  db:
    image: postgres:16-alpine
    volumes:
      - pgdata:/var/lib/postgresql/data

  redis:
    image: redis:7-alpine
    volumes:
      - redis_data:/data

  traefik:
    image: traefik:v3.0
    ports:
      - "80:80"
      - "443:443"

Consider

• CDN for static assets (Cloudflare, free tier)
• Database connection pooling (PgBouncer)
• Separate read replicas if read-heavy

Estimated cost: $50-300/month

Stage 4: Scaling (1,000-10,000 Users)

Goal: Performance at scale. Team is growing. Infrastructure must not be a bottleneck.

Add Now

• Load balancer (if not using Traefik/Nginx)
• Database read replicas
• CDN for all static assets and images
• Centralized logging (Loki, ELK)
• APM (Application Performance Monitoring)
• Alerting with on-call rotation
• Infrastructure as Code (Terraform, Ansible, or Docker Compose)
• Secret management (Infisical, Vault)
• Database migration tooling (tested rollback procedures)
• Disaster recovery plan (documented and tested)
• Security audit (at minimum: OWASP Top 10 check)

Performance Optimization Checklist

Database:
  [ ] EXPLAIN ANALYZE on slow queries
  [ ] Add missing indexes (pg_stat_user_tables → seq_scan counts)
  [ ] Connection pooling (PgBouncer)
  [ ] Vacuum and analyze schedules

Application:
  [ ] Response caching (Redis)
  [ ] Database query caching
  [ ] Pagination on all list endpoints
  [ ] N+1 query elimination
  [ ] Image optimization and lazy loading

Infrastructure:
  [ ] Gzip/Brotli compression
  [ ] HTTP/2 or HTTP/3
  [ ] CDN for static files
  [ ] DNS prefetch for external resources

Consider

• Message queue (Kafka/RabbitMQ) if you have event-driven workloads
• Search engine (Meilisearch, Elasticsearch) if search is core to your product
• Horizontal scaling of application servers

Estimated cost: $200-2,000/month

Stage 5: Scale (10,000+ Users)

Goal: High availability. Zero-downtime deployments. SLAs matter.

Add Now

• Kubernetes or equivalent orchestration (if complexity warrants it)
• Multi-AZ or multi-region database
• Blue/green or canary deployments
• Chaos engineering (test what happens when things fail)
• SOC 2 / ISO 27001 compliance (if serving enterprise)
• Dedicated SRE or DevOps engineer
• Incident management process (runbooks, post-mortems)
• Cost monitoring and optimization
• API gateway with advanced rate limiting
• WAF (Web Application Firewall)

When Kubernetes Makes Sense

Kubernetes is worth the complexity when:

• You have 10+ services that scale independently
• You need automated scaling based on load
• Your team has Kubernetes expertise (or can hire it)
• You need multi-region deployment
• Your deployment frequency is daily or more

Until then, Docker Compose on a single server (or two for HA) handles most workloads. At TechSaaS, we run 50+ containers on a single server with Docker Compose and it serves us well.

The Anti-Patterns

Over-Engineering

• Kubernetes for a CRUD app with 50 users
• Microservices before you have product-market fit
• Multi-region before you have customers outside one city
• Event sourcing for a blog

Under-Engineering

• No backups until data loss
• No monitoring until an outage
• No CI until a bad deploy
• No rate limiting until a DDoS

Cargo Culting

• Using what Google/Netflix uses because they are successful
• Choosing technology based on hype instead of team capability
• Adding complexity because "we might need it someday"

The TechSaaS Recommendation

For most startups through Stage 3 (up to 1,000 users), a single well-configured server with Docker Compose is the right answer. It is:

• Cheap: $60-200/month for serious hardware
• Simple: One server to SSH into, one compose file to manage
• Fast: No network hops between services, everything on localhost
• Reliable: With proper backups and monitoring, 99.9% uptime is achievable

We help startups set up exactly this infrastructure — optimized, monitored, backed up, and documented — so they can focus on building their product instead of managing servers. Contact us at [email protected].