Cloud Spending Out of Control? Fix Your Planning First
Yash Singh
Devops
Aug 12, 2025
|
5
min
Whenever I talk to founders or teams about their cloud setup, the conversation always takes a familiar detour: active users, feature roadmaps, growth and then the cloud bill.
It’s huge. And when I ask where the money is going, the typical answer is: “We’re not sure.”
That’s shockingly common. Companies routinely spend thousands, sometimes hundreds of thousands on cloud services without a clear view of what they're actually using. Even worse, many aren’t using the features they already pay for.
The real issue nobody admits
People complain cloud is expensive, but the truth is: cloud becomes costly when planning and maintenance are missing. The root causes I see again and again are simple:
- No clear infrastructure plan
- No auto-scaling or improper scaling rules
- No regular optimization reviews
- A poor understanding of actual resource needs
A scenario I’ve seen too often
I recently met a founder scaling fast. On paper their setup looked “production ready,” but a closer look revealed:
Test environments running full production services
No use of Spot or Reserved Instances (both can cut costs by up to 50%)
Over-provisioned servers far more CPU/RAM than the app needed
An old config that “works” so nobody wants to change it, even though it wastes money
That “it works” attitude is expensive. If a system is left untouched just because it runs, you're paying the price for inertia.
Why resource mapping matters
One big indicator of poor planning: no architecture diagram, no resource map, no visibility. Without that map you can’t:
Plan auto-scaling properly
Identify idle or wasteful resources
Prepare for future growth
Auto-scaling is one of the cloud’s most powerful levers. It adjusts capacity to traffic in real time, so you don’t pay for full capacity around the clock.
How mapping cut our bill by 22%
When I joined my current company, the first task was resource mapping: list what we used, where it ran, and whether it matched real needs. That visibility made it obvious where to cut waste.
Combine that clarity with a few operational changes:
Use Spot and Reserved Instances where appropriate
Configure Auto Scaling Groups correctly
Remove unused resources on a schedule
Conduct regular infrastructure reviews
These moves cut our cloud spend by about 22% in three months. I’ve applied the same approach at Dodo Payments small changes regularly compound into meaningful savings.
Practical changes that help immediately
Here are the concrete practices I recommend:
- Use Spot Instances for dev and test environments.
- Use Reserved Instances (or savings plans) for predictable workloads.
- Review and clean unused resources every quarter to optimize cost, improve security, and remove waste.
- Monitor performance and align resource sizing with real app needs, don’t just add CPU/RAM because it "feels" necessary.
Too many teams reflexively add resources instead of diagnosing the bottleneck. Know what the app actually needs first.
Don’t forget cloud credits
A common missed opportunity: cloud provider startup programs. AWS, GCP, and Azure all offer substantial credits to startups and use these credits to run experiments and find your true infrastructure needs without upfront spend.
Final thoughts
Cloud isn’t the villain, poor planning is. If you:
Understand your application requirements,
Architect intentionally,
Use native features like auto-scaling and Reserved/Spot Instances, and
Continuously monitor and optimize,
then cloud can be a strategic advantage rather than a cost sink. With the right planning, the cloud becomes your greatest ally, scalable, flexible, and cost-efficient.
