Why Storage as a Service Makes Sense in a Multicloud Environment
Learn how enterprises deploy storage as a service in their multicloud.
Businesses today are generating more data than ever before. Earth’s population is above 7.8 billion and growing. More and more people are working from home. Technologies like the Internet of Things (IoT), the growth of edge computing, edge data centers, and artificial intelligence (AI) proliferate. The number of enterprise and consumer endpoint devices is growing. All these factors result in the proliferation of enterprise data.
The world will generate 175ZB of data a year by 2025. Enterprise data alone is projected to grow at an annual growth rate of 42.2 percent as the new reality of self-driving cars, smart factories, and automated disease diagnostics advances.
Mining and analyzing this data can open doors to a new wave of innovation, higher operational efficiency, and new sources of revenue. Companies that are simply sitting on these repositories of data are missing out on the revenue-enhancing value of the data they collect. In fact, more than 68 percent of the data available to enterprises goes unused.
And this data management puzzle is getting even more complicated as more and more enterprises move their data infrastructure to a mutlicloud environment.
One of the ways in which enterprises can maintain better control over how they store, activate, manage, and monetize the surge in data is to deploy storage as a service (StaaS) as a central part of their multicloud.
Enterprises, regardless of company size, industry or business goals, are embracing the mutlicloud approach. Historically, cloud adopters opted for either private cloud or public cloud platforms. Private cloud provided greater control and security compared with public cloud platforms that use third-party cloud services and infrastructure. Next came hybrid cloud architectures with a goal to combine load balancing and the cost-effective scale of public cloud without exposing all of a company's applications and data beyond their own intranet.
Multicloud architecture goes a step further and combines services and resources from two or more cloud providers. Multicloud combines services and resources from multiple cloud providers to increase the flexible use of and availability of various applications and services like StaaS, software as a service (SaaS), compute as a service (CaaS), infrastructure as a service (IaaS), and platform as a service (PaaS).
While multicloud implementation creates flexibility to service data in ways that can create maximum value, managing storage across multiple clouds can create a great deal of complexity. It can be cost prohibitive because of added fees for transferring, storing, accessing, reading, and writing data. Variation in security control from one cloud to another can increase the risk of breaches. Meanwhile, keeping mass data on-premises typically presents scalability limits, and enterprise backup environments are often messy, with multiple different backends for storage.
When considering the complexities of managing data in a multicloud environment, it's important to understand that storing and harnessing vast troves of data is no longer a nice to have feature — it's a necessity.
Take healthcare, for instance. Artificial intelligence algorithms, trained to interpret images and recognize patterns, now outperform humans in detecting breast cancer on mammograms. This wouldn't be possible without collecting, storing and analyzing the huge amounts of unstructured data from medical imaging done in the past few decades. And that's just one type of data. Imagine the possibilities that the rest of the patient, insurance, and scheduling data can open up for the healthcare industry.
Now consider self-driving cars. To navigate the roads on their own, they need to process troves of data within their maps and from their many sensors to compare and assess current conditions. Similarly, they need data that enables them to identify nearby objects, such as other cars, pedestrians, traffic lights, road markings, and other signals. Cross-analyzing the data collected by various sensors has the potential to help improve safety and traffic flow, and to help pave the way for other smart city implementations.
The story is similar in fields as varied as enterprise video, advertising, manufacturing and retail. That's why organizations across sectors need a robust infrastructure equipped to handle the ever-increasing volume of data being generated by cameras, sensors, and humans.
Data growth, however, is outstripping storage capacity and network bandwidth, especially when sensors and cameras are located in remote locations, far away from data centers.
The challenge of managing the explosive data growth in a multicloud environment is where StaaS factors into the data management equation.
As organizations combine public and private cloud services, they move the data between multiple cloud platforms from time to time. In such a dynamic environment, they need the flexibility to scale up and scale down their storage and to do so in regular intervals. The ideal StaaS would offer a zero-commitment risk-free model that enables enterprises to pay for only the storage they use on a subscription basis. The resulting ability to pivot quickly is a critical advantage in a world where market conditions change in a blink.
Pricing models of various cloud platforms vary and as a result multicloud implementations involve complex cost calculations. Deploying StaaS helps reduce the complexity by enabling businesses to acquire storage as an operating expense, without the need to commit capital resources to purchase, manage and scale storage infrastructure that might become obsolete soon.
Moreover, the "as a service" strategy reduces the total cost of ownership over the lifecycle of a storage system. The cost of on-demand storage for the first year or two will be much lower than the cost of buying the same amount of storage space upfront. At the same time, businesses retain the flexibility to benefit from volume pricing if they choose to scale up later as their needs change without incurring any add-on charges, thus maintaining the cost of ownership advantage over the long-term too. This makes costs predictable and eliminates guesses about future needs.
Best-in-class StaaS offerings typically make backing up data easy via automation — users simply select what and when they want to backup. Security, resiliency, redundancy, and data recovery is built in, and data is encrypted both during transmission and while at rest, ensuring only authorized users can access their information.
The best-in-class StaaS providers won't just offer a subscription model but will make pricing simple, scalable, and predictable. They will also ensure that there are no vendor lock-ins and will enable enterprises to make their data available for processing by any public cloud service as they scale storage up or down. They should complement an organization's existing cloud infrastructure and offer the flexibility to swiftly and easily move data from one cloud platform to another. Additionally, they should provide an easy way to deploy storage at the edge and keep data near the edge, bringing data closer to where it is generated so that it can be processed and analyzed with minimal latency. With the right solution, organizations can combine the value of StaaS with the added benefits of centralized management, improved control, and local performance.
In today's business environment data is not just generated, reviewed, and considered. Outside of human intelligence, data is the most valuable asset for most enterprises and to extract the most value possible from it, companies need a flexible and affordable infrastructure to store, move, analyze, and leverage their data.
And that is perhaps the biggest reason why a StaaS model should be central to a multicloud strategy: as it simplifies the complex cloud management system, it enables organizations to store data they might have historically been forced to delete. And as a result, business leaders who leverage StaaS will be able to make the most of their data cost-effectively—spurring better outcomes and greater opportunities for growth.