If 2019 was the year Computational Storage made an impact, you should expect 2020 to be an even more groundbreaking year for the storage industry. Last year, we saw new use cases for Computational Storage emerge as more organizations adopted AI and ML. Likewise, the enterprise has discovered moving massive amounts of data from storage to host CPU memory to process a query is costly in terms of power consumption and time. Computational Storage helps negate the growing strain of data movement in nearly all compute applications.
Below are my predictions on how organizations will store and process data in 2020, particularly enterprises relying on hyperscale, edge and CDN environments.
- NVMe is NOT Enough – Move Less and Analyze More at the Edge. One of the major issues organizations experience when connecting more edge and IoT devices (think video surveillance cameras and autonomous cars or ‘anything’ that can churn out data 24/7) – are data bottlenecks. The trick is to find the right data out of petabytes of data storage that can be used for timely analysis. NVMe (Non-Volatile Memory Express) has provided a measure of relief and proven to remove existing storage protocol bottlenecks for platforms churning out terabytes and petabytes of data regularly. Even though NVMe is substantially faster, it is not fast enough by itself when petabytes of data are required to be analyzed and processed in real-time. Computational Storage, especially the way we marry the use of NVMe SSDs and compute power, adds analytical power and speed so that results can be accomplished right away and where the data is generated.
- Computational Storage Enables Better 5G Connectivity: In 2020, we will see more emphasis on processing massive data workloads at the edge and this will be intensified with the advent of 5G. As more cell towers are built to support 5G, there needs to be more complex infrastructure that can manage the data “in and out of the box” so user data is optimally utilized. Computational Storage with its small form factors and added compute power can pack an analytical uppercut punch in the limited size and power enabled edge-datacenters that live at each of these new cell tower platforms. By providing additional compute to the confined resources that exist is paramount to the successful growth of this space.
- Computational Storage Can Simplify the Traffic Flow of Content Delivery Networks: Streaming services have continued to dominate headlines this year. The recent launches of Apple TV+, Disney Plus and NBC Peacock, combined with Netflix, Hulu and Amazon Prime’s increasing investments pose major hurdles for the content delivery networks (CDNs). Video requires lots of expensive data movement, which makes it more costly and difficult to deliver and this is where Computational Storage can be a major asset. CDNs have typically relied on a traditional cloud model to support streaming customers, but they realized centralized clouds were too far on average from the endpoints they sent data to, racking up costs, latency and downtime. Computational Storage can solve these issues. While a typical CDN traffic flow involves lots of data movement and processing spread out over a variety of edge infrastructure, Computational Storage can simplify this flow.
These are just three of many ways we will see Computational Storage make a splash over the next year. Throughout the last year, we’ve had many incredible conversations and are extremely bullish on where Computation Storage is headed in 2020 and beyond. Every day we are working with innovative businesses to solve their data problems, and we look forward to helping you out as well. Contact us and tell us what your biggest data-related issues are and we can show you how NGD can help.