The nature of work is always transitioning, evolving and changing, writes Alan Campbell, Senior Director & General Manager, UK & Ireland at Nutanix.

Today, we have seen the proliferation, popularisation and eventual propagation of cloud computing, mobile device ubiquity and new algorithmically-enriched approaches to Artificial Intelligence (AI) and Machine Learning (ML)... all of which have further changed the nature of work.

Encoding workflows into data

The sum consequence of much of the development on the post-millennial technology curve is a new approach to digitally-driven work. To explain this shuddering generalisation, digital work means tasks, processes, procedures and higher-level workflows that can be encoded into data in order for their status to be tracked, analysed and managed.

Part of the total estate of big data that now hovers over all digital assets in the modern workplace, digital workflows can now be built that are more intelligently shared between humans and machines.

Where processes are accurately definable, typically repeatable and easily replicable, we now have the opportunity to use autonomous software controls such as Robotic Process Automation (RPA) and chatbots to shoulder part of our daily tasks. Although there is a period of process mining and process discovery that we need to perform before we can switch on the autonomous advantage, once we do so we can start to focus human skills on more creative higher-value tasks.

Where all of this gets us is to a point where we can be intelligently granular about how we place elements of our total digital workload across data services, across application resources, across cloud backbones and ultimately, across people.

A broader wider cloud backbone

To enable digital work, we still have some challenges to overcome i.e. we need to be able to communicate between each other as humans and machines in a consistent yet essentially decoupled way. Because not every work task has had its genome decrypted, we are still searching for ways to encapsulate certain aspects of enterprise workflows.

This is tough because we’re aiming towards a moving target i.e. market swings and the dynamism of global trade. But, as we start to build new work systems, we can start to operate workflows that are intelligently shared across different interconnected cloud services, for a variety of core reasons.

Enterprises can now create a layered fabric of work elements and functions shared across different Cloud Services Providers (CSPs), sometimes separated-out on the basis of different cloud contract costs, sometimes for reasons related to geographic latency or regulatory compliance, or often dispersed across more than one cloud due to the various optimisation functions (processing, storage, transactional Input/Output capability, GPU accelerated etc.) that exist in different services.

If private on-premises cloud combined with public cloud is what we now understand to be the de facto ‘most sensible’ approach we know as hybrid cloud, then this (above) deployment scenario is one move wider. Where workloads are placed across clouds, we are in hybrid territory; but where individual data workflows are dispersed across and between different cloud services, we get to poly-cloud.

Visible benefits, invisible infrastructure

The architectural complexity of interconnected cloud services that are established around these terms is not hard to grasp. In order to make this type of lower substrate diversity manageable, cost-effective and above all functional, enterprises will need to embrace a platform-based approach to hyperconverged cloud infrastructure.

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Most organisations struggle to effectively manage heterogeneous cloud environments and move workloads back and forth between and among them. Establishing visible benefits from this type of approach to cloud is only possible if the business is able to think of its cloud infrastructure as an invisible foundational layer.

Managing a multi-cloud and poly-cloud infrastructure means being able to simplify cloud management and operations requirements across an enterprise’s chosen estate of interconnected cloud services. With different providers all offering different software toolsets, different management dashboards, different configuration parameters and so on, there is no point-and-click solution without a hyperconverged higher platform layer in place.

Bandwidth requirement diversity

As theoretical as some of the discussion here sounds, many practical examples already exist. South Africa’s largest bank Nedbank has been bold with its cloud-based approach designed to cope with cost-effectively delivering upon its diverse bandwidth requirements.

Needing low-latency remote worker provision for its 2,000-strong developer function in India (but capable of straddling less performant latency parameters for other functions), the company had to build systems capable of superior service that would be a win-win for staff and customers alike.

Nedbank represents a future where flexibility, rapid service, reliability, performance, low-carbon footprints and utility-based billing are central. In ICT terms, that means a hybrid approach where users are served across a gamut of models and IT can centrally provision based on changing needs and without compromises to data protection or quality of service.

As we stand in 2022, it’s difficult to present any analysis of the heterogeneous cloud mission without mentioning the obviously disruptive effects of the global pandemic. The pandemic has changed how nearly all organisations operate and multi-poly-cloud supports this new way of working.

Distributed distributaries

Well over half of the respondents (61%) in the IDC InfoBrief “From Digital Culture to Value Realisation” say they’re focused on offering more flexible work setups because of the pandemic.

Most organisations report that while their remote workforces may shrink or grow, they are here to stay for the foreseeable future. Multi-cloud and all its poly-cloud tributaries and distributaries offer the most agile IT environment for supporting this flexibility by distributing data to diverse geolocations for user proximity, and business continuity.

As essentially virtualised as the ether that drives the abstracted world cloud computing is, we know that C-suite managers and directors will need some kind of grounding to go forward with if any of the analysis presented here is to help shape operational roadmaps.

It is perhaps useful to think of cloud computing not as an IT function, but as a business operating model in and of itself. That business model is typified by flexibility, scalability, power, choice, manageability and control if it is executed diligently.

Future-proofed work strategy in this arena means being able to strategically match both human and machine workflows to the cloud service they should best reside upon for all the reasons discussed here. It will also enable us to accommodate for future changes that we don’t even know about yet.

Let’s not forget that disruption is constant.

About the author

Alan Campbell is the Senior Director & General Manager, UK & Ireland at Nutanix. Nutanix is a cloud computing company that sells software, configures cloud services (including desktops as a service, disaster recovery as a service, and cloud monitoring) as well as providing software-defined storage.