Cloud computing has come to occupy a central locus in the data management ecosystem, much more so than it did even a couple months ago. In the wake of patent economic instabilities, global health concerns, and unparalleled need for remote access, many organizations are struggling to simply keep their lights on to retain what customers they still have.

Advanced analytics only helps so much with the necessities of reducing costs and provisioning IT resources in immensely distributed settingswhich is the crux of the requirements for maintaining operations in such an arduous business climate.

Although Artificial Intelligence will likely always be considered cool, the cloudand not AIis the indisputably pragmatic means of staying in business in an era in which budget slashing and layoffs (even of IT personnel) are a disturbingly familiar reality.

The cloud is the single most effective way to address contemporary concerns of:

What were once incentives for cloud migration are rapidly becoming mandates for contemporary IT needs. However, the cloud is fairly complex, [there are] a lot of cloud services, a lot of moving parts, reflected Privacera CEO Balaji Ganesan. By understanding the options available for overcoming the inherent complexities of the cloudinvolving data governance and security, integration, and data orchestationorganizations can perfect this paradigm to thrive in the subsequent days of economic uncertainties.

Public Cloud Strengths

Most companies know the three main public cloud providers are Amazon, Azure, and Google. Fewer realize these provide the foundation for serverless computing; only a chosen few realize they have the following respective strengths that are determinative when selecting providers.

Cloud Orchestration

The hybrid and multi-cloud idiom typifies todays cloud architecture by allowing organizations to positionand accessresources where theyre cheapest and work best: whether theyre in data centers, central clouds, or at the edge. The downside of this flexibility is its inherent complications, which is why there needs to be a way to manage all this complexity and this challenge of different locations, explained Kubermatic CEO Sebastian Scheele. Cloud native approaches with orchestration platforms like Kubernetes or Docker are foundational to automating the management of a thousand or even ten thousand clusters in a scalable way, from a single glass, and having a central management control over your whole organization, Scheele notedwhich encompasses all cloud resources. Orchestrating the containers widely used to build and deploy cloud applications is influential for implementing common use cases that make the cloud an efficient cost-saver, including:

Data Integration

A fundamental cloud architecture need that orchestration solutions dont resolveand possibly exacerbate with their dynamic portabilityis data integration. In fact, the most pressing consequence of the increasing distribution of the data landscape the cloud supports is the need to integrate IT resources, because the cloud alone doesnt provide integration, Shankar cautioned. Instead, the many varieties of clouds, their hybrids, and their innumerable connectors simply reinforce the need to integrate data for almost any singular use case.

Additionally, theres what Shankar termed third party data. For example, various forms of commerce involving retailers and wholesalers and so on, things are being returned, things need to be recalled, Shankar mentioned. All these need to go back to people that supplied them. So its a huge connected network and you need the ability to bring them all together. Data virtualization has emerged as a consistently credible means of integrating data into a single glass pane while simultaneously rectifying differences in schema, format, and structure variations.

Moreover, it provides an abstraction layer to view and access these resources so the data themselves dont actually move for enterprises to integrate them. In this respect, any form of the cloud simply becomes another source to be virtualized alongside others in a comprehensive data fabric. You come to this one logical layer and then you ask for the data, Shankar specified. It then goes and figures out where the data resides, whether on-premises, in the cloud, data at rest, data in motion, structured data, or unstructured data, and gives it all back to you in one single format that you can use.

Data Governance

Virtualization technologies have multiple means of facilitating data governance standards like data quality. Other solutions expressly designed for the cloud use different methods for ensuring governance protocols are preserved, regardless of where data are. Options functioning as a central interface between organizations and their cloud resources can point to these sources, understand data, and enable a central way of managing policies and enforcing them locally, Ganesan disclosed. Although this approach works best with data at rest for analytics and statistical AI, it obsoletes the need to move data.

Many of the clouds governance considerations involve sensitive data or personally identifiable information. Formidable solutions in this space rectify these issues across all cloud deployments in three ways, including:

Chief Value Proposition

The clouds worth to the modern enterprise is remarkably simple, yet undeniable: it enables them to do more with less. It empowers them to scale better, store data cheaper, and access IT resources much faster than they could if everything were on premise. Moreover, they effectuate these boons with considerably less overhead, technical expertise, and impediments to agility than theyd otherwise have with on-premise deployments.

Still, the clouds greatest boon is likely its remote, ubiquitous access to IT serviceswhich is at a premium today. By solving its requirements for governance and security, data integration, and streamlined orchestration, organizations have the most efficient means of meeting their IT needs while significantly decreasing their associated risks.

About the Author

Jelani Harper is an editorial consultant servicing the information technology market. He specializes in data-driven applications focused on semantic technologies, data governance and analytics.

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Not Just Another Trend: The Postmodern Cloud Computing Imperative - insideBIGDATA