Below are three things about data storage every IT pro should know:
1. AI and machine learning involve a ton of data.
AI projects are undeniably “cool,” in an obvious sense and a technical manner, but to accomplish the goals they set, they need to correlate and mathematically analyze massive data sets. This data tends to be generated on the edge of the network — where people and machines all live — and the data must be frequently accessed with high availability and low latency for analysis. Often, maintaining this level of access comes at a high cost, which is why the companies making waves in the AI space are often major enterprises and incumbent vendors, rather than resource-strapped startups. AI and ML didn’t even make the top ten priorities for SMBs in a 2019 survey from Techaisle, an analyst firm that focuses on SMB and midmarket IT.
2. In the cloud-focused future, there are still some tough problems to solve.
Developers, not traditional IT professionals, are driving the creation and adoption of next-generation architectures that aim to leverage public clouds while supporting AI, machine learning, machine data analytics and more. Trying to spin a “Goldilocks” architecture from scratch that can provide the performance, latency and cost characteristics that these workloads require is far from a trivial effort. When problems such as these arise, IT has an opportunity to produce innovative solutions rather than throw up roadblocks. Getting involved, and driving discussion about alternatives, is the best way to remain relevant.
Read this article from Forbes contributor Tom Coughlin on how ClearSky’s architecture solves the latency problems inherent in the cloud.
3. “Storage is dead” is one of the industry’s greatest myths.
IDC released its latest Worldwide Enterprise Storage Systems tracker update in June 2019, which showed worldwide revenue declining by 0.6%. This finding has led journalists such as CRN’s Joe Kovar to conclude that “the heady days of enterprise storage growth are over.” Vendors that once dominated enterprise IT have been making major changes within their organizations, and those actions have sent waves throughout the technology market. Sometimes, the resulting effects from these changes help populate one of the industry’s biggest myths — that storage is dead. It’s just that storage as we currently know it is dead. Storage has just embarked on some of its biggest changes yet, with a better next-gen model now emerging.
ClearSky Data is on the forefront of this storage transformation. We provide a full stack, self-protecting storage service that combines the power of the cloud with the sub-millisecond latency of the edge. As a result, enterprises manage just a single copy of their data, which is accessible with flash performance wherever it is needed, whether the end user is a person or an AI / ML application.
What’s more, ClearSky is working in partnership with other vendors — from cloud providers and data center companies to wireless providers — to build out the edge so that it can meet the data demands of AI, ML and other use cases that are data hungry and sensitive to latency.
For example, ClearSky recently joined Packet, a bare-metal cloud provider, and SBA Communications, a large wireless tower operator, to provide the data layer for a new edge data center built at the base of SBA’s Boston-area tower. These towers are already located on the metro edge, so they’re in a perfect position to aggregate data, and can provide all the power, cooling, security and connectivity a data center requires. ClearSky’s service enables data center customers to connect to as many terabytes of storage as they need in a matter of seconds, and they can access it at multiple locations.
For enterprises and startups alike, machine learning and AI will only continue to take root in companies’ interests, priorities and eventually, roadmaps. Data storage will need to support that journey every step of the way — although the systems of the past were never built to handle the massive amounts of data generated by AI projects, Internet of Things (IoT) information and machine data analytics. To stay alive, storage is evolving to meet the needs of such initiatives.