Taming the GCP Compute Beast: How We Wrestled $2,800/Month Back From Oversized Instances

"Why are we spending so much on compute when nobody's using it?"

It started innocently enough. Our dev team needed powerful GCP instances for some quick experiments. We spun up some beefy n1-highmem-96 machines, perfect for crunching large datasets. The experiments ran, the results came in, everyone was happy.

Except, nobody remembered to scale them down. Those instances sat there, humming away, costing us a small fortune for weeks, then months. It was a classic case of "out of sight, out of mind," and it was quietly draining our budget.

The Illusion of "Temporary"

In the fast-paced world of software development, “temporary” resources often have a way of becoming permanent fixtures. We had cost alerts set up, of course, but they were tuned to catch sudden spikes, not slow bleeds. This creeping cost of oversized instances flew completely under the radar.

We knew we needed a more proactive solution, one that could intelligently identify and address this kind of waste.

An abstract image representing wasted cloud resources, perhaps depicted as leaking pipes or overflowing containers.
A visual representation of EazyOps's analysis, perhaps a stylized graph showing resource utilization or cost savings.

The EazyOps Intervention

We started using EazyOps to gain deeper insights into our GCP spending. It didn’t take long for EazyOps to flag those oversized instances. The platform highlighted the chronic underutilization of both CPU and memory, clearly showing us where the waste was hiding.

EazyOps not only identified the problem but also offered concrete solutions. It recommended smaller machine types – n1-standard-32 instances in this case – that could handle the workload without the hefty price tag.

Automation to the Rescue

The best part? EazyOps didn’t just give us recommendations; it empowered us to automate the fix. We set up rightsizing policies that automatically adjusted the instance sizes based on actual usage. This meant no more manual intervention, no more forgotten instances burning a hole in our pockets.

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A visual metaphor for cost savings and regained budget, perhaps a plant growing or a building being constructed.

Reaping the Rewards

The results spoke for themselves. We reduced our compute costs by 65%, reclaiming $2,800 per month. That's a significant chunk of change that can now be invested in other important initiatives.

More importantly, we gained peace of mind knowing that our resources were being used efficiently and that we had a system in place to prevent this kind of waste from happening again.

Key Takeaways

  • Even small inefficiencies can add up to significant costs over time.
  • Proactive monitoring and automation are crucial for effective cloud cost management.
  • The right tools can make a huge difference in identifying and addressing waste.

Looking Ahead

We're now exploring how EazyOps can help us optimize other areas of our cloud spending, including storage and networking. We’re confident that with the right tools and strategies, we can continue to drive down costs and maximize the value of our cloud investments.

About Shujat

Shujat is a Senior Backend Engineer at EazyOps, working at the intersection of performance engineering, cloud cost optimization, and AI infrastructure. He writes to share practical strategies for building efficient, intelligent systems.