You’re probably overpaying for Azure Disks but it's not your fault.
If you're managing infrastructure in Azure, there's a good chance you're overspending on storage. Not because you're careless, but because Azure’s disk pricing is a maze of hidden defaults, inconsistent billing models, and performance assumptions that don’t match real workloads.
The whitepaper Azure Compute Disks: The Hidden Cost Optimization Opportunity takes a hard look at this problem. It breaks down how and why you’re getting trapped in inefficient storage configurations, and more importantly, what you can do about it.
Real-World Considerations and Architecture Tradeoffs
The paper includes concrete examples and architecture patterns that lead to meaningful savings, like:
Those wins don’t happen by accident. Here’s what makes them so hard to achieve.
Azure’s Disk Defaults Are Quietly Draining Your Budget
When you spin up a new VM, Azure defaults to Premium SSD. Seems fine—until you realize you’re paying 1.5 to 2 times more than necessary for workloads that don’t need that level of performance. Worse, Premium SSD v2 is often cheaper and faster, but not the default.
More Performance Doesn’t Always Mean Better Performance
The paper debunks a common assumption: that disk tier is the key to app responsiveness. In reality, performance issues often stem from CPU, memory, or code-level bottlenecks. If you’re not profiling I/O patterns before upgrading, you’re just throwing money at the problem.
Ultra Disk Is Overkill for Most Workloads
But that performance comes with a 7x price tag, and most workloads simply don’t need it. You're paying 7x more for theoretical sub-millisecond latency that most applications will never need or even notice. The paper outlines the math and includes benchmark strategies worth replicating for your specific use case.
Billing Complexity Makes Optimization Inaccessible
Azure's billing models are fragmented: fixed pricing here, transaction-based there, and granular tuning elsewhere. There’s no consolidated view that ties IOPS, throughput, capacity, and usage patterns to actual spend. Optimization becomes a manual, error-prone task—unless you automate it.
Azure’s defaults aren’t built for efficiency. The whitepaper shows how to find what works.
End with a registration form unless we can include the registration form on the top righthand side of the blog.
