Avalanche of Cloud-First Strategies in 2017

This article was written by by Aron Brand, CTO, Ctera Networks Ltd., on the blog of the company.

The Stateless Enterprise and Other Visions for 2018

In the enterprise world, the gradual, hesitant cloud adoption that we saw in 2016 has transformed into an avalanche of cloud-first strategies in 2017.

As critical business functions are being rapidly migrated to the cloud, we are seeing an increasing trend towards adoption of hybrid and multi-cloud technologies, where multiple cloud providers as well as private data centres are being meshed together, allowing the resolution of security and regulatory barriers and reducing dependence on any single cloud vendor.

This trend is further fueled by an important compelling event that affects every organization that processes the personal data of EU residents – the GDPR regulation which is becoming enforceable on 2018. GDPR involves massive fines which may exceed €20 million, for failing to adequately protect personal information. As a result, companies are now scrambling to find storage solutions which automate security processes and to comply with the very strict data sovereignty and data residency requirements of GDPR.

By ‘cloud-first’ I do not mean only shifting server applications. In fact, this cloud-first trend is being cleverly extended to end user data. IT departments everywhere have traditionally spent huge amount of efforts on managing endpoint device data. When an employee gets a new laptop, the IT guy needs to help him or her move their data from the old to the new. When a branch office server fails, or becomes obsolete, the IT guy or girl needs to drive over, and then spend the best part of the day restoring the data from a backup and getting everything running again. By stating that data is stored in the cloud and endpoint devices are only extensions thereof, companies are shifting towards the ‘stateless enterprise’ architecture – eliminating all the ‘state’ from those endpoint devices.

By moving the primary home of the data from the endpoint devices to a cloud, endpoint devices – whether laptops, desktops, file servers, or whatever – become merely a local cache of that cloud-based ‘golden copy’. Any changes are stored only temporarily on the device, while they are quickly and efficiently on-ramped to the organisation’s cloud. This shift results in reduction in the effort that IT departments are spending on maintaining and protecting endpoint devices.

Besides simplifying the IT department’s work, this shift towards a stateless architecture has another wonderful side effect – an elimination of the ‘dark data’ which was previously stored in employees’ laptops or desktops. Suddenly, all this ‘dark’ data is right at your fingertips – stored in the cloud- as a searchable, analysable and sharable repository.

And this leads me to the final piece of the 2018 puzzle: recent developments in text analytics and natural language processing which are bound to be exceptionally useful in the digital workplace of the future. Using these tools, tasks once reserved for humans can be augmented by machine intelligence to transform productivity of knowledge workers. According to McKinsey & Company, 45% of the activities individuals are currently paid to perform can be automated by using readily available technologies. The implications of this figure on human productivity are enormous.

IBM’s Watson, for example, can be used to quickly suggest the more effective language to be used approach a specific prospect customer, automatically drawing upon the entire available body of organisational data; and similar technologies based on machine learning can be used help to prevent human errors such as an employee inadvertently sharing a sensitive file with the wrong audience.