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How independent are the data?

How independent are the data? Cloud and the question of sovereignty.

Data movements and the need for interoperability between different data centers are not the only challenges posed by public cloud computing. "As public clouds represent one of the main solutions for businesses to store their data, the dependence on these external providers poses a growing challenge in terms of business continuity and data sovereignty," says Ricardo Mendes, co-founder and CEO of Vawlt, a provider of storage and security software. Other experts on our podium also identify data sovereignty as a challenge for businesses relying on public clouds. For Cubbit, Signoretti records: "Navigating through complex data governance regulations, such as in the context of GDPR and NIS2, increases complexity for businesses."

In addition to this, public cloud SaaS services have introduced additional locations where data must be protected. "A major difference today is the number of different places businesses store critical data. This is especially apparent when considering the increasing use of SaaS applications. An average medium-sized business uses more than 200 SaaS applications, but there are few enterprise-class data protection options that can scale to protect these applications and enable rapid, granular recovery," explains Kim King, Senior Director of Product Marketing at backup software provider HYCU. According to King, over 50 percent of successful ransomware attacks target SaaS applications.

Kerns confirms this view on data protection with SaaS: "Meeting enterprise requirements for protecting data in both the public cloud and on-premises is a challenge that requires effort and usually new software solutions." With reference to the fact that companies should learn from the mistakes of others, he adds: "There are cases where some believed that this effort was not necessary for data in a public cloud."

The public cloud - where there is shadow, there is also light.

However, despite the challenges posed by public clouds, several experts note that one of their advantages is the democratization of technologies that benefits smaller businesses. An example is given by Norfolk from Bloor Research: "In the past, there was a big difference between large companies with proper databases and small businesses with data stores that did not support Acid (Atomicity, Consistency, Isolation and Durability). Cloud technologies have leveled this out."

The current conditions also influence the storage technologies and services offered by providers. According to Serdyuk from Nakivo, the challenges in the area of security are being addressed by the development of even more sophisticated defensive measures against cyber attacks. “Providers are integrating advanced encryption mechanisms, access controls, and compliance features into their solutions. Many offer secure enclaves and hardware-based security to meet the evolving threat landscape. However, many storage solutions still lack comprehensive backup and recovery tools," he says.

The need to extract and categorize data from various sources is driving the development of software tools that automate this process. Serdyuk: "Management tools such as metadata tagging, version control and analytic functions are becoming increasingly important."

Multi-Cloud solutions: Response to modern requirements

Nowadays, companies also need data management software that supports both hybrid and multi-cloud infrastructures. "Providers who have recognized this are developing solutions that support easy integration with various cloud providers, on-prem infrastructures and mixed configurations. They also offer tools for seamless data migration and synchronization across various environments," says Serdyuk.

"We are seeing pressure for technology consistency across different environments. Some vendors are integrating their technology into the cloud," says Sinclair. An example of such a vendor is Netapp, whose on-prem storage and data management software is now also integrated into the public clouds AWS, Microsoft Azure, and Google Cloud. "Others are integrating third-party technologies like VM Ware or Red Hat Open Shift, which can be used at multiple locations," Sinclair adds.

In light of the complexities arising from the need to maintain data sovereignty and compliance with different data regulations that can apply to data storage across several public clouds across national borders, Signoretti says: "Providers are prioritising sovereign solutions for regulated industries such as healthcare and the public sector and are emphasising compliance in regions like EMEA and APAC. Although they're still subject to the Cloud Act, Microsoft and AWS have recently introduced sovereign cloud storage offerings." The Cloud Act (Clarifying Lawful Overseas Use of Data) is a US law enacted in 2018 that gives US and non-US authorities investigating crimes the right to access corporate data stored by service providers.

From a technical perspective, Craig Carlson, an advisor to the technical council of the Storage Networking Industry Association (short: Snia), points to the need to facilitate fast data access for AI systems: "AI is currently being addressed by looking at what can be done to bring networks to their highest performance while also being highly scalable. This work is being continued in groups like Ultra Ethernet." A panel called Ultra Ethernet Consortium is developing an architecture that is supposed to make Ethernet as fast as modern supercomputer connections, while also being highly scalable, as cost-effective as the current Ethernet, and backward compatible. Members of the highly promoted consortium include AMD, Arista, Broadcom, Cisco Systems, Huawei, HPE, and Intel.

With the further growth of data volumes, particularly in relation to AI and machine learning, entirely new demands are being placed on companies. "More data absolutely leads to increasingly complex challenges related to storage. Data growth increases the demands in all dimensions," says Tintri's Mowry.

Urgently needed adaptations will likely be provided through advancements in data management systems – the metadata tagging, version control, and analytics functions mentioned by Guilleaume. Norfolk suspects AI will push these and other developments: "The biggest challenges today lie within the context of AI and its appetite for data – as well as sustainability issues and the resource costs for massive amounts of data. Data quality also presents a major difficulty. Decisions should not be based on outdated, incorrect, or biased data. AI, in particular, does not cope well with training based on biased data."

Data storage and sustainability - where is the journey going?

According to Guilleaume, AI will drive advances in data mobility: "AI/ML will further accelerate the need for data mobility between the levels where data is stored and where it is analyzed." These advancements in storage management and mobility might not only be limited to AI usage. Carlson from Snia comments on this: "There is always a trickle-down of technology. Thus, technologies currently being developed for the highest-end AI data centers will become mainstream in a few years."

Sustainability also stands prominently on the list of challenges. Roy Illsley, Chief Analyst of the research firm Omdia, emphasizes: "How can we make data storage as green as possible? At some point, we will either have to change our lifestyle and the way we do things, or technology will help us. I think it will be a combination of both, which means we need to figure out how we can generate less data or know more precisely what data we have."

Arwani cites the impact of data storage on the environment, especially with regards to CO2 emissions and energy consumption, as one of the current challenges, along with platform interoperability and security. He quotes an estimate from the International Energy Agency (IEA) that data centers' electricity consumption was about one percent to 1.3 percent of global demand in 2022. The IEA predicts that data centers' energy consumption could increase three to four-fold by 2026. “These problems are more costly and complex to address as they demand not only technological advances but also awareness and changes in data management itself,” Arwani says.

Outlook: Which technology has potential for problem-solving?

On the hardware side, Carlson comments on the fact that the flash technology curve seems to be running out of steam, as it has become much harder for flash chip manufacturers to lower costs by packing even more data bits into each flash memory cell. "We are eager to see which technology will provide reliable high performance in memory in the next ten to 20 years," he says. "The long-term use of the current tape-disk-flash model may not be viable. Therefore, we are seeing the development of new and still very experimental technologies, such as DNA storage."

Unsurprisingly, Arwani from Biomemory believes that DNA storage will indeed be the solution: "Vendors are developing more environmentally friendly solutions, such as helium hard drives, which reduce energy consumption, or DNA storage technologies being developed by Biomemory and Catalog DNA. These technologies promise a storage density of one exabyte per gram and durability of several millennia. Furthermore, they open up the possibility of new application cases, such as the first space data centers."