Taming multicloud chaos

No matter which cloud vendors they use, businesses need a digital platform that creates a unified data model

Integrate a digital platform that creates a unified data model in order to tame multi-cloud chaos.

Moving data from on-prem to the cloud represents one of the most exciting innovations in corporate IT. It can also be very messy, especially with the emergence of so many cloud providers, each with their own distinct technologies and protocols.

One solution for the enterprise is to move to a single digital platform to manage all IT assets, regardless of whether they’re stored on one vendor’s cloud or shared among the big four: Google, Amazon, IBM, or Microsoft. A unified data platform can also boost efficiency, speed time to market, and generate better customer service.


companies describe IT environment future as multicloud with low interoperability

Companies should carefully consider the risks of migrating data to multiple clouds. Storing some data on Azure and then moving some data to AWS is a recipe for chaos and unexpected complexity. To protect the integrity of IT assets, companies need to deploy a single digital platform to oversee and manage its data, no matter the cloud provider. Only then can companies fully take advantage of the innovations that cloud technology provides.

System patchwork

To lower costs, many companies have opted to store data on multiple clouds. The result is a patchwork of systems that don’t effectively communicate with one another. About 40 percent of companies describe the IT environment they envision for the next two years as multicloud with low interoperability, according to a study by IDC.

The use of so many cloud platforms with little or no interoperability means a heightened risk of material disruptions or even systemwide shutdowns. Companies need tools that can spot these disruptions and prevent them from happening.

Reduce licensing headaches

The solution to multicloud chaos is a single digital platform that can map out IT assets across various cloud providers, allowing users to glean real-time insights from various workflow streams, such as asset management, security, and cost compliance.

For example, many organizations spend significant sums on enterprise software licenses that they don’t use. Managing these licenses can be tough because software asset management (SAM) teams still wrestle with spreadsheets and cumbersome manual processes.

The problem has become especially acute as companies migrate their data from on-prem data centers to the cloud. Licenses often restrict users to a specific platform or a service, which means companies must pay additional fees to the vendor for the same software if they want to move data from an onsite server to, say, Amazon Web Services or Azure. Some software makers have even sued customers for moving data and its accompanying software from on-prem to a cloud provider without obtaining a new license.

Moving to the cloud is a complex endeavor, but the technology exists to make that transition both cost effective and less stressful.

Spot trouble in advance

A single data platform, armed with more advanced predictive software, can also help companies spot operational problems before they happen.

With traditional AIOps, employees need to know everything that can go wrong ahead of time. Modern AIOps, such as ServiceNow’s Predictive AIOps, performs unsupervised learning, which means the software teaches itself to spot abnormalities as they occur. This allows the Ops team to fix problems before they result in material disruptions.

Since the pandemic, many companies have adopted a mobile-first strategy, which means designing digital experiences for smartphones rather than simply running desktop apps on mobile devices.

The problem with mobile apps is that if users experience a slow connection or cannot log into the system, they will simply go on to their next task without contacting customer service. These “silent” usability issues frustrate users over time and can lead them to change service providers.

Typically, the IT team becomes aware of these issues only when the number of cases hits a certain threshold. Predictive AIOps technology can intuitively predict those usability issues before the abnormalities hit the pre-set threshold.

Let’s say your predictive AIOps tool is monitoring an online banking app. If customers are having trouble accessing the app with their mobile device, the tool could flag this to the IT Ops team before the system crashes altogether.

Here’s another example: A customer tries to book a room on a hotel app, but the system tells him it can’t process the transaction. The customer books the room again only to discover that the system did indeed process the first transaction. He has now paid for the same room twice.

The unhappy customer then has to call the customer service number to cancel the original order. Predictive AIOps can alert the hotel about the double-booking anomaly before it becomes a widespread problem.

A platform of platforms

Moving to the cloud is a complex endeavor, but the technology exists to make that transition both cost effective and less stressful.

A single digital platform can help companies manage their data regardless of what cloud provider they use and predict problems before they happen.