Amit Golander

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Storage is moving to flash, and flash is getting faster, so people keep asking me why I keep talking about latency as if there is a problem.  Isn't faster flash going to just make everything faster?  Won't "the rising tide lift all boats"? Flash media as a storage media is indeed "faster" than the spinning hard-disks we've all been using for decades.  But when it is used to simulate a hard disk, as is the case with SSD products, there are software layers which prevent it from reaching its full potential.  That explanation always gets heads nodding, because it is obvious.  But what about when the flash media is not simply packaged into an "SSD" and connected over SATA or SAS, but instead can be addressed via NVMe over PCIe?  Doesn't that make the problem of hard disk drive emulation go away? Not entirely.  For one thing, in some cases the SSD abstraction is maintai... (more)

New Changes in Persistent Memory | @CloudExpo #Cloud #Storage

Incumbent storage vendors such as EMC, Netapp, and Nutanix have built their rich code base on the block layer. This means that the only viable option to use Persistent Memory as a storage tier is to wrap it up with an abstraction layer that will present it as a block device. As a veteran researcher, I'm always interested in brand-new approaches for doing things. One great example is the new NVM programming model (NPM) proposed by SNIA. The new NPM approach took a big step forward this week, as version 1.0 of the associated NVM library (NVML) was released. For the few people who u... (more)

Wasting Money Is Easier than Ever Before

Normal 0 false false false EN-US X-NONE HE In the hilarious 1985 film “Brewster’s Millions,” Richard Pryor had to work hard for a full month in order to waste 30 million dollars. And he almost failed. Today, with a modern data center infrastructure for production and test environments, wasting millions is barely a challenge. Unlike Richard Pryor, you’re not actively trying to waste money. It just happens. Apache Cassandra, like other NoSQL or In-Memory compute middleware, was designed with the assumption that the active working set should fit inside memory in order to achieve l... (more)