The Silent Drain: How Idle Cloud SQL Replicas Cost Us $1,500 a Month

"Why are we still paying for these Cloud SQL instances?"

It started with a routine cost review. Our GCP bill showed a consistent $1,500 monthly charge for Cloud SQL instances that, according to our inventory, weren't actively used. They were like phantom servers, quietly draining our budget.

This mystery kicked off a week-long investigation, diving into logs, dashboards, and infrastructure diagrams. We were determined to find the source of this unexplained expense.

An abstract representation of idle, unused cloud resources consuming budget.

The Ghost in the Machine: High Availability Gone Wrong

Our initial assumption was a misconfigured billing report. We meticulously checked our tagging, resource groups, and billing filters. Everything seemed correct. Then, we dug into the Cloud SQL instances themselves.

It turned out these weren't phantom servers; they were read replicas, originally set up for high availability during a major application migration. Once the migration was complete, the read replicas were no longer necessary. But they remained, silently accumulating costs.

Manual Cleanup: A Risky Proposition

Deleting the replicas manually was an option, but a dangerous one. We needed absolute certainty that no applications still relied on them. Manually tracing dependencies across our complex microservice architecture was a time-consuming and error-prone process. One wrong move could disrupt production.

A visual metaphor for the complexity and risk of manual dependency tracing.
An abstract image depicting automated analysis and identification of idle resources by EazyOps AI.

EazyOps AI: The Automated Solution

We turned to EazyOps AI. Its dependency mapping feature automatically identified all connections to the idle replicas. After verifying zero traffic, EazyOps recommended automated removal. The entire process, from identification to validation to removal, took less than an hour.

The Results: Savings and Peace of Mind

EazyOps AI eliminated the $1,500 monthly waste. More importantly, it gave us the confidence to automate future cleanup tasks, knowing that dependencies are automatically tracked and validated. We regained control of our cloud spend and reduced the risk of manual errors.

A visual representation of cost savings and improved efficiency achieved through automated optimization.

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.