Azure Disk Tiering Neglected: How We Saved $2,000 a Month

"Why are we spending $3,000 a month on Premium SSDs for archival data?"

That question from our CFO kicked off a deep dive into our Azure storage costs. We knew we were using Premium SSDs for performance-sensitive applications, but $3,000 a month seemed excessive. It turns out, we had a silent storage killer: neglected disk tiering.

The Premium SSD Trap

Like many engineering teams, we had opted for Premium SSDs early on for their speed and reliability. They were the easy button for ensuring application performance. The problem? We hadn't revisited our storage strategy as our data volumes grew. We were paying a premium price for performance we didn't need for a significant portion of our data.

Abstract image representing escalating cloud storage costs, perhaps a graph with an upward trend or stacks of metaphorical data blocks.
Abstract representation of manual data management, like tangled wires or a complex flowchart.

Manual Tiering: A Non-Starter

Initially, we considered manually moving older data to Standard HDDs. However, the sheer volume of data, combined with the ongoing effort required to identify and migrate cold data, made this impractical. We needed an automated solution.

EazyOps and the Power of Intelligent Tiering

That's where EazyOps came in. Its intelligent tiering feature analyzes I/O patterns and automatically moves infrequently accessed data to Standard HDDs, while keeping hot data on Premium SSDs. The implementation was surprisingly seamless, requiring minimal configuration.

Visual metaphor for automated tiering, possibly a streamlined flow of data or sorted blocks.

The Results: Significant Savings and Improved Efficiency

Within a month, our Azure storage costs dropped by 65%, a savings of $2,000 per month. EazyOps not only optimized our storage spending but also provided valuable insights into our data usage patterns, helping us further refine our storage lifecycle management.

Lessons Learned and Looking Ahead

This experience highlighted the importance of regularly reviewing cloud resource utilization. EazyOps proved invaluable in addressing a common, yet often overlooked, area of cloud waste. Now, we're exploring other cost optimization opportunities within EazyOps, including right-sizing VMs and optimizing reserved instances.

Abstract representation of future optimization possibilities, like expanding interconnected nodes or an upward trajectory towards a goal.

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.