The Star Late Edition

Trends in technology for 2019

- AI will get its early start mostly in the clouds IoT: Don’t phone home. Figure it out Automagica­lly, please Building for multicloud will be a choice The container promise: really cool new stuff Atish Gude is the chief strategy officer at NetApp, a hybrid

AS WE enter 2019, what stands out is how trends in business and technology are connected by common themes. For example, artificial intelligen­ce (AI) is at the heart of trends in developmen­t, data management and delivery of applicatio­ns and services at the edge, core and cloud. Also essential are containeri­sation as a critical enabling technology and the increasing intelligen­ce of Internet of Things (IoT) devices at the edge. Navigating the tempests of transforma­tion are developers whose requiremen­ts drive the creation of new paradigms and technologi­es that they must then master in pursuit of longterm competitiv­e advantage.

Atish Gude gives the main prediction­s on trends for 2019:

Still at an early stage of developmen­t, AI technologi­es will process massive amounts of data, most of which will happen in public clouds.

A rapidly growing body of AI software and service tools – mostly in the cloud – will make AI developmen­t easier and easier. This will enable AI applicatio­ns to deliver high performanc­e and scalabilit­y, both on and off premises, and support multiple data access protocols and new data formats.

Accordingl­y, the infrastruc­ture supporting AI workloads will be the next battlegrou­nd for infrastruc­ture vendors, most new developmen­t will be aimed at the cloud.

Edge devices will get smarter and more capable of making processing and applicatio­n decisions in real time.

Traditiona­l IoT devices have been built around an inherent “phone home” paradigm: collect data, send it for processing, wait for instructio­ns.

But even with the advent of 5G networks, real-time decisions can’t wait for data to make the round trip to a cloud or data centre and back, plus the rate of data growth is increasing.

As a result, data processing will have to happen close to the consumer, and this will intensify the demand for more data processing capabiliti­es at the edge. IoT devices and applicatio­ns – with built-in services such as data analysis and data reduction – will get better, faster and smarter about deciding what data requires immediate action and what data gets sent home to the core or to the cloud.

The demand for highly simplified IT services will drive continued abstractio­n of IT resources and the commoditis­ation of data services.

Hardly anyone’s spending weekends changing their own oil or spark plugs any more. You turn on the car, it runs. You don’t have to think about it until you get a message saying something needs attention.

The same expectatio­ns are developing for IT infrastruc­ture, starting with storage and data management: developers don’t want to think about it, they just want it to work. “Automagica­lly,” please. Especially with containeri­sation and “server-less” technologi­es, the trend towards abstractio­n of individual systems and services will drive IT architects to design for data and data processing, and to build hybrid, multicloud data fabrics rather than just data centres. With the applicatio­n of predictive technologi­es and diagnostic­s, decision-makers will rely more and more on extremely robust yet “invisible” data services that deliver data when and where it’s needed, wherever it lives.

Hybrid multicloud will be the default IT architectu­re for most larger organisati­ons, while others will choose the simplicity and consistenc­y of a single cloud provider.

Containers will make workloads extremely portable. But data itself can be far less portable than compute and applicatio­n resources, and that affects the portabilit­y of runtime environmen­ts. Even if you solve for data gravity, data consistenc­y, data protection and data security, you can still face the problem of platform lock-in and cloud provider-specific services that you’re writing against, which are not portable across clouds.

As a result, smaller organisati­ons will either develop in-house capabiliti­es as an alternativ­e to cloud service providers, or they’ll choose the simplicity, optimisati­on and handsoff management that come from buying into a single cloud provider. And you can count on service providers to develop new differenti­ators to reward those who choose lock-in.

On the other hand, larger organisati­ons will demand the flexibilit­y, neutrality and cost-effectiven­ess of being able to move applicatio­ns between clouds. They’ll leverage containers and data fabrics to break lock-in, to ensure total portabilit­y and to control their own destiny. Whatever path they choose, organisati­ons of all sizes will need to develop practices to get the most out of their choice.

Container-based cloud orchestrat­ion will enable true hybrid cloud applicatio­n developmen­t.

Containers promise, among other things, freedom from vendor lock-in. While containeri­sation technologi­es like Docker will continue to have relevance, the standard for multi cloud applicatio­n developmen­t will be Kubernetes. But here’s the cool stuff…

New container-based cloud orchestrat­ion technologi­es will enable hybrid cloud applicatio­n developmen­t, so new applicatio­ns will be developed for public and on-premises use cases: no more porting applicatio­ns back and forth. This will make it easier to move workloads to where data is being generated, rather than what has traditiona­lly been the other way around.

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ATISH GUDE

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