How to Avoid 5 Costly Cloud Architecture Mistakes (and Save Months of Rework)
A few months ago, we got a call from a fast-growing e-commerce startup.
They had just closed a funding round and launched massive ad campaigns, some of them on prime-time TV. Their marketing was working — but the infrastructure? Not so much.
Every time an ad aired, their website broke.
They were spending $500k–$1M/month on ads… and a chunk of that money was leaking through downtime.
They needed help. Fast.
This wasn’t a company doing anything wrong on purpose. They were just in that typical funded-startup stage — focused on product, not on scaling infrastructure. Their small-scale setup worked fine… until it didn’t.
Once the traffic hit real volume — especially the sudden spikes from TV campaigns — the system couldn’t keep up.
And that’s when we came in.
Auto-scaling was broken or missing across multiple components.
Redis kept crashing from connection storms triggered by the PHP backend.
No health checks, so deployments were dangerous.
Vault, Consul, Jenkins, NGINX, CoreDNS, ElastiCache — all jammed into one cluster, often overprovisioned or misconfigured.
No visibility: monitoring and tracing were minimal or non-existent.
All environments ran in the same EKS cluster. (Yes, you read that right.)
On paper, they had “all the right components.”
In practice, it was duct tape over a scale problem.
We didn’t bulldoze the system. Instead, we rebuilt one piece at a time, with fast feedback loops and the team’s full involvement.
Here’s how it went down:
We set up monitoring (Prometheus, Grafana) and tracing (Jaeger, OpenTelemetry).
Identified which services failed under load — Redis, CoreDNS, NGINX, ElastiCache.
Redis was crashing because the PHP app opened too many connections → migrated to Memcached, which plays better with PHP.
Manual scaling during traffic spikes gave us insight into real bottlenecks.
Introduced auto-scaling for backend services.
Fine-tuned Aurora configurations and enabled auto-scaling for the DB tier.
Introduced a task-based autoscaling model for background jobs.
Removed Consul, Vault, and Jenkins — all overkill for this scale.
Switched to External Secrets and internal config tooling.
Split PHP deployment to test new configs without breaking production.
Tuned native EKS autoscaling settings — defaults were far from optimal.
Added proxy layers and SQL caching to reduce database load.
Introduced load testing setup to simulate traffic bursts.
Deployment process was fixed — with health checks, faster rollout, and zero-downtime strategies.
Within the first week, we had visibility and early wins.
Handled 3–4x traffic spikes without failure.
Brought availability to 99.95%.
Stabilized deployments — no more downtime on rollout.
Reduced cloud cost from $60k/month to $35k/month, mainly by database and compute tuning.
Rolled out spot instances to save even more.
The team felt the shift immediately.
They moved from firefighting to shipping. From blind spots to observability.
This transformation wasn’t just about infra. It was about culture.
Their CTO could rally the entire 30-person team in minutes.
The devs were pragmatic, curious, and open to learning.
Held short training sessions as infra patterns evolved.
Shared dashboards and logs to explain “why” something was failing.
Worked with the team to spot and clean up leftover tech debt.
Instead of finger-pointing, we had discussions about caching strategies.
Instead of pushing tools, we shared real-world trade-offs.
That made all the difference.
One of the most underrated challenges?
Assuming EKS will scale out of the box.
It doesn’t.
Tune your Cluster Autoscaler,
Set proper resource requests/limits,
Configure HPA/VPA,
Split workloads by type and lifecycle,
…it won’t scale when you need it to.
This startup hit that wall hard. Their pods were pending, not scaling. And their cluster size wasn’t adjusting fast enough. We fine-tuned all of it — and it finally started behaving like a true autoscaling platform.
Here’s what we learned — and what every e-commerce startup should know before running that big ad campaign.
Having Vault, Consul, and Jenkins doesn’t mean you’re ready.
Each one adds complexity — and breaks under load if not perfectly tuned.
We use open-source Terraform modules — but they’re opinionated.
They carry our past failures, so you don’t repeat them.
Flexibility is power. But also responsibility.
At small scale, problems are silent.
At big scale, they explode. You need tested systems, not learning curves.
Every extra service is a point of failure.
Stick to what you can monitor, scale, and debug in minutes — not hours.
You can’t fix what you can’t see.
Dashboards and traces were the reason we could act fast and prioritize.
This project reminded us of something important:
The best infra is not the fanciest — it’s the one you can own and operate under pressure.
You don’t need 20 cloud services. You need 5 that scale.
You don’t need perfect architecture. You need resilient, observable, testable foundations.
So the next time someone says, “Let’s add Vault just in case…”
Ask them if they’ll be on call when it crashes.