Hyperscalers such as Microsoft, Google, Amazon, etc., all run their cloud divisions with a specific goal. To provide their hardware to someone else in a form called instance and have the user pay for it by the hour. However, instances are usually bound by a specific CPU and memory configuration, which you can not configure yourself. But instead, you can only choose from the few available options that are listed. For example, when selecting one virtual CPU core, you get two GB of RAM and can go as high as you want with CPU cores. However, the available RAM will also double, even though you might not need it. When renting an instance, the allocated CPU cores and memory are yours until the instance is turned off.

And it is precisely this that hyperscalers are dealing with. Many instances don't fully utilize their DRAM, making the whole data center usage inefficient. Microsoft Azure, one of the largest cloud providers, measured that 50% of all VMs never touch 50% of their rented memory. This makes memory stranded in a rented VM, making it unusable for anything else.

At Azure, we find that a major contributor to DRAM inefficiency is platform-level memory stranding. Memory stranding occurs when a server's cores are fully rented to virtual machines (VMs), but unrented memory remains. With the cores exhausted, the remaining memory is unrentable on its own, and is thus stranded. Surprisingly, we find that up to 25% of DRAM may become stranded at any given moment.