Many startups make the same mistake early on: they overengineer their cloud setup before they even know what they’re building.
Founders watch conference talks from big tech, read deep-dive postmortems from hyperscale systems, and assume that’s the bar they need to hit on day one. So they start designing for millions of users, global failover, and extreme availability - before they’ve shipped a stable product.
You’re not Netflix.
And that’s not a weakness. It’s clarity.
Let’s walk through the most common cloud myths we see - and why they usually hurt more than they help.
Myth #1: You need multi-cloud to save money
Multi-cloud doesn’t save money in the early stages. It burns it.
Running across multiple cloud providers means duplicating everything: networking concepts, IAM models, deployment pipelines, monitoring, alerting, and on-call knowledge. You’re paying twice in infrastructure and three times in cognitive load.
Early on, cost problems are rarely about cloud pricing. They’re about architecture decisions and unused resources. The fastest way to stay efficient is to pick a single cloud provider, learn it well, and build something simple that your team actually understands.
Multi-cloud can make sense later, when you have real scale, real leverage, and real reasons. Until then, it’s a solution looking for a problem.
Myth #2: You need enterprise-grade tooling from day one
Enterprise tooling exists to solve enterprise problems.
Most startups don’t have those problems yet.
You don’t need a service mesh when you have five services. You don’t need a complex analytics pipeline when your product usage still fits into a single database table. And you definitely don’t need dashboards nobody looks at just to feel “production-ready.”
What you need early on is boring reliability: a deployment process that works, basic monitoring that tells you when something is broken, and logs you can actually read when things go wrong. Anything beyond that is usually noise.
Complex tooling too early doesn’t make you safer. It makes you slower.
Myth #3: You need a big DevOps team early on
This used to be true. It isn’t anymore.
With modern managed services, one or two strong engineers can comfortably handle infrastructure for an early-stage product. Databases, load balancers, queues, and CI/CD are mostly solved problems now - if you let them be.
In many cases, you don’t need a dedicated DevOps engineer at all. And if you’re using a managed platform like LARA, infrastructure stops being a bottleneck entirely. There’s less custom glue, fewer moving parts, and far fewer things that only one person understands.
Your team’s time is better spent improving the product than babysitting infrastructure.
Myth #4: Everything must be fully automated immediately
Automation is great - but only when it solves a real problem.
If a process happens once every few weeks and takes five minutes, automating it on day one is rarely worth the effort. That time is usually better spent shipping features, talking to users, or fixing real pain points.
The right approach is incremental. Automate the things that are frequent, fragile, or annoying. Leave the rest manual until it starts to hurt. Manual steps at small scale are not a failure. They’re often the most pragmatic choice.
Automation is a tool, not a goal.
Myth #5: The cloud locks you in forever
Yes, cloud providers have opinions.
Yes, there is vendor coupling.
But no, that doesn’t mean you’re trapped forever.
With sensible architectural choices - clean interfaces, reasonable abstractions, and avoiding unnecessary provider-specific magic - lock-in can be reduced to a manageable level. More importantly, the value you get today from tight integration with a single platform almost always outweighs theoretical portability concerns years down the line.
Startups don’t fail because they picked the “wrong” cloud.
They fail because they moved too slowly or over-optimized too early.
More myths we see all the time
Myth #6: You need Kubernetes from the first deploy
Kubernetes is a powerful platform. It’s also a lot of work.
If you don’t have multiple teams, complex workloads, or serious scaling requirements, Kubernetes will usually add operational overhead without delivering much value. Suddenly you’re debugging YAML, managing clusters, and dealing with abstractions you don’t actually need yet.
For many teams, simpler deployment models work better early on. Kubernetes can come later - when it solves real problems, not hypothetical ones.
Myth #7: Building it yourself is always better than using managed services
Building your own infrastructure can feel empowering.
It’s also expensive.
Managed services exist because certain problems have already been solved extremely well: backups, scaling, high availability, and security updates. Re-implementing those from scratch is rarely a good use of time, especially for small teams.
Your time is valuable. Managed services are often cheaper than the hours you’d spend maintaining your own solution - and they keep working even when you’re asleep.
Myth #8: You need to get cloud architecture “right” from day one
There is no final, perfect architecture.
Good systems aren’t designed in one go. They evolve. The best teams start with something simple, learn from real usage, and refactor when there’s a clear reason to do so.
Trying to future-proof everything from day one usually leads to complexity without payoff. Architecture should match your current stage - not an imagined future.
Bottom line: less heroics, more pragmatism
Cloud infrastructure isn’t about showing how smart you are.
It’s about supporting the product and the team without getting in the way.
If you keep things simple, use managed services, and resist the urge to copy big tech without a clear reason, you’ll move faster, waste less time, and make better decisions.
And in early-stage companies, that’s what actually matters.
Navigating the cloud doesn’t have to be hard
Cloud today feels like a maze. Endless options, strong opinions, and a lot of advice that only works if you’re already at hyperscale.
That’s where we come in.
At Labyrinth Labs, we act as guides through the cloud labyrinth. We help teams cut through noise, avoid unnecessary complexity, and choose architectures that actually fit their stage, team, and goals - not someone else’s scale story.
No overengineering.
No blind best practices.
Just clear, pragmatic decisions that move you forward.
If you want help navigating your cloud setup - or just a second opinion before things get complicated - it’s simple.
Reach out. We’ll help you find the right path.
