EBS IOPS Calculator for AWS Volumes

In storage, it’s not just about how much disk space you purchase. It’s also about how fast data can flow to and from those disks, how big chunks of data need to be sent, and what the limitations on your servers are. A lot of engineers think IOPS is the magic bullet answer for everything. They’re wrong.

In reality there are bandwidth ceilings, queue depths, and throughput limits. They frequentely affect production traffic in ways you wouldn’t expect. These are EBS bandwidth, queue depth, latency targets, and IO size throughput. Remember: One number isn’t everything. Use the calculator as part of the overall picture.

Why IOPS Is Not Enough for Storage

First, remember IO size. It is often overlooked until your database start timing out. By traditional definitions, an IOP is a single 16 KiB operation. That means that an application performing lots of small (4 Ki) random reads will consume your provisioned IOPS budget four-fold relative to a workload reading bigger chunk. Even with a lot of raw throughput available, you may not have enough IOPS capacity. Because the answer depend upon this information, the tool requests your average IO size prior to answering.

Another thing that matters is latency targets. You can have a highly available system, but if it’s not planned out based off the latency target, then it will fail. For example, if you’re doing financial transactions where you want a response time of less than a millisecond, a general purpose volume may be able to handle the IOPS needs. However, under load, it won’t meet them. The calculator also finds out if your queue depth match your latency goal.

In most cases, if you have tight latency targets and high concurrency, you’ll typically need dedicated storage types such as Block Express. Running something like this on cheaper storage is likely to cause timeouts at busy periods.

But don’t forget about the instance itself. I’ve seen people set up a huge volume and then complain that it doesn’t work well. Maybe it’s because of the instance connecting to the volume, it is not the storage layer at all. There is a maximum bandwidth for an EC2 instance connected to an EBS volume. That’s set based off the instance type. After you reach the limit, you can tune the volume all day long and you won’t gain anything. Check out the table on the page for some examples. This isn’t a software issue; it’s a physical limitation of the network interface within your virtual machine. Your volume may be plenty big enough for high-traffic but you’re only attaching it to a small connection on your system.

Stable systems have headroom, a few tenths of a second here, or a gigabyte there is not very expensive; a hard limit reached when your site spikes is incredibly expensive. You can plug that buffer into the calculations ahead of time with this tool so that you avoid right-sizing too tightly for “typical” usage, which is what everyone does: averages conceal maxima, and storage performance is measured in maxima, which must be met without stalling.

When choosing storage volume type, consider how you access your data. Random read and write access (e.g., search index) differs from sequential read/write access (e.g., backup stream, logging). Streaming large files is best done on fast-transfer drives, while small random operations don’t do well. By matching the workload pattern to the hardware you avoid paying for capabilities that you won’t need. You also avoid frustration when you deploy a powerful drive in the wrong context and it performs poorly as a result.

Storage sizing isn’t about the biggest, it’s about knowing your constraints. If you don’t understand what the friction is then how can you eliminate it? Is it the IO size of an app? Is it the network bandwidth? Or maybe the volume limit? Knowing this up front will save you a lot of time down the road. There are tools out there that make these constraints crystal clear. Stop guessing at performance and instead engineer it precisely. When the next big launch arrives your infrastructure wouldn’t of skipped a beat.