Technical Architecture

Stop Chasing Trends: When NOT to Copy What Big Tech Does

By Jeff Wray •

"Netflix uses microservices." "Google built on Kubernetes." "Facebook runs React at scale." Your developer wants to rebuild your application the same way. After all, if it's good enough for companies worth billions, it's good enough for your startup with 12 customers, right?

Wrong. Spectacularly, expensively wrong.

The Big Tech Cargo Cult

Big tech companies publish blog posts about their infrastructure. Developers read these posts, attend conference talks, and come back excited to implement the same solutions. Nobody stops to ask: "Do we actually have the same problems?"

The Pattern:

  • 1. Big tech solves a problem at massive scale → 10 million requests per second
  • 2. They write a blog post about their solution → "How We Handle Scale"
  • 3. Developers read it and think it's best practice → "This is how real engineering is done"
  • 4. Small companies adopt the same approach → For 100 requests per second
  • 5. Result: Massive complexity, zero benefit → Solving problems you don't have

The Microservices Trap

This is the classic example. Your developer comes to you with a proposal:

"We should split our monolith into microservices."

Why? "That's what Amazon does. Microservices let different teams work independently."

How many teams do you have? "Currently just me, but when we hire more..."

How many customers do you have? "About 200. But we're planning to scale!"

Amazon has 1.5 million employees and serves hundreds of millions of customers. You have one developer and 200 customers. You don't have Amazon's problems.

What Microservices Actually Cost

Before (Simple Monolith):

  • • One codebase to understand
  • • One database to manage
  • • One deployment to worry about
  • • Bugs are easy to trace end-to-end
  • • Testing is straightforward

After (Microservices "Upgrade"):

  • • 8 different services, each with their own repo
  • • 8 databases to keep in sync
  • • Service mesh configuration (Istio, Consul, whatever's trendy)
  • • Distributed tracing (because debugging now requires it)
  • • Service discovery, load balancing, circuit breakers
  • • Authentication between services
  • • Monitoring for each service
  • • Deployment orchestration (now you need Kubernetes!)
  • • Network latency and failures between services

Result: 10x complexity, zero benefit at your scale

The Kubernetes Obsession

"We need to deploy on Kubernetes." No, you need to deploy your application. Kubernetes is one way to do that—a way that makes sense if you're managing thousands of containers across hundreds of servers.

Are you? Or are you running 3 containers on 2 servers?

Your Actual Needs:

  • ✓ Run some code
  • ✓ Handle a few hundred requests/day
  • ✓ Deploy updates occasionally
  • ✓ Restart if it crashes

Solution: A $10/month VPS or Heroku

What Kubernetes Provides:

  • • Auto-scaling across 1000+ nodes
  • • Complex networking configurations
  • • Multi-tenant isolation
  • • Service meshes
  • • Custom resource definitions
  • • Helm charts, operators, ingress controllers...

Cost: $200K/year for a DevOps engineer who knows how to manage it

When Big Tech's Problems Became Your Developer's Resume

Here's the uncomfortable truth: Some developers push for complex architectures not because your business needs them, but because their resume does.

  • •
    "Scaled microservices architecture serving millions" sounds better on LinkedIn than "Built a monolith that works fine."
  • •
    "Implemented Kubernetes clusters with Istio service mesh" gets interview callbacks. "Deployed to Heroku" doesn't.
  • •
    "Distributed systems engineer" commands a higher salary than "Maintained a simple Rails app."

The incentives are misaligned. What's good for your developer's career isn't always what's good for your business.

What You Should Copy From Big Tech

Not all big tech practices are bad. Some are genuinely valuable at any scale:

  • ✓ Code review: Catch bugs before they ship, regardless of team size
  • ✓ Automated testing: Confidence in changes, whether 1 developer or 1000
  • ✓ Monitoring and logging: Know when things break, at any scale
  • ✓ Documentation: Onboard new people faster (even if "new people" is future you)
  • ✓ Security practices: Customer data matters whether you have 10 or 10 million users
  • ✓ Automated deployments: Ship faster with less risk

Notice what's not on that list? Complex infrastructure, distributed systems, or bleeding-edge frameworks.

The Right Question

When your developer proposes adopting some big tech pattern, don't ask: "Is this what Netflix does?"

Ask:

  • "What problem does this solve for us, specifically?"
    Not theoretically. Not at imagined future scale. Right now.
  • "What's the simpler solution?"
    There's always a simpler solution. What is it and why won't it work?
  • "What's the ongoing maintenance cost?"
    Complex systems require constant care. Who's going to maintain this in 6 months?
  • "What happens if we do nothing?"
    Sometimes the answer is "we're fine." That's a valid answer.

Scale When You Need It, Not Before

"But what if we get a million users tomorrow?" Then you'll have revenue to hire people to scale the architecture. That's a good problem to have.

Building for imaginary future scale is called premature optimization. It's expensive and often wrong—you'll scale in directions you don't actually need.

The Scaling Reality:

Most startups fail because they don't get customers, not because their monolith couldn't handle the traffic they never got.

Twitter ran on a monolith until they had millions of users. Instagram had 30 million users before they split up their architecture. WhatsApp handled 450 million users with 32 engineers.

Simple scales further than you think.

The "Boring Technology" Rule

You have a finite capacity for dealing with complexity and unknowns. Every new technology, framework, or architectural pattern consumes some of that capacity.

Choose boring, proven technology for most of your stack. Save your innovation budget for the parts that actually differentiate your business.

Boring (Use This):

  • ✓ PostgreSQL (been solid for 25 years)
  • ✓ Rails/Django (mature, well-documented)
  • ✓ AWS EC2 (simple, predictable)
  • ✓ React (huge community, lots of help available)
  • ✓ Background jobs with Sidekiq/Celery

Exciting (Be Very Careful):

  • ✗ New database technology "way faster than Postgres"
  • ✗ Bleeding-edge framework (v0.8.2-beta)
  • ✗ Custom service mesh implementation
  • ✗ Novel architecture from last week's HackerNews
  • ✗ "We'll write our own..." anything

When Should You Actually Adopt Complex Patterns?

Eventually, you might need them. Here are the actual triggers:

Microservices: When You Have Multiple Teams

If different teams are stepping on each other's toes in the same codebase, it might be time. Not before.

Kubernetes: When Manual Infrastructure Gets Overwhelming

If you're managing 50+ servers manually and spending all your time on infrastructure, K8s might help. At 5 servers? No.

Event-Driven Architecture: When You Need Real Async Processing

If you have truly independent processes that don't need to know about each other. Not because you read a blog post about it.

NoSQL: When Relational Models Don't Fit

If your data genuinely doesn't fit tables and relationships. But 95% of applications fit perfectly fine in Postgres.

The Bottom Line

Netflix, Google, and Facebook have problems you'll never have. They also have resources you don't have—hundreds of engineers, massive budgets, and years to get things right.

Your competitive advantage isn't in copying their architecture. It's in moving fast, staying simple, and solving actual customer problems instead of imaginary scaling problems.

Build for the scale you have, not the scale you dream about. You can always add complexity later. You can't easily remove it.

Need Help Separating Necessary Architecture from Resume-Driven Development?

A fractional CTO can evaluate technical proposals, spot premature optimization, and ensure you're solving real problems instead of imaginary ones.

Get Practical Technical Guidance