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People often talk about the cloud as if there were only one. In reality, there are many clouds, each operated by its own cloud service provider (CSP) and with its own strengths and weaknesses.
Cloud personalization involves mixing and matching multiple clouds to create the perfect IT environment for a business. In the latest episode of the IBM Cloud podcast, hosts Ian Lynch and Steve Choquette talk to Marvin Goodman, manager for AI and analytics analyst relations at IBM Cloud, to find out how it’s done.
When cloud-based services first hit the market, enterprises quickly began migrating many of their basic workloads, hoping to take advantage of the cloud’s scalability and cost savings. After that initial rush of enthusiasm, many companies paused.
They realized it was more difficult than expected to transition many workflows, since they had specific requirements that made them harder to move to a cloud environment. Some applications needed specific kinds of compute functionality. Others needed integration with established software. A few organizations found running applications on a cloud provider’s servers made it more difficult for network administrators to track criteria such as latency and performance.
There was another key confounding factor: location.
Where’s my cloud data?
As developments such as mobile computing continue to drive applications toward the edge of the network, companies have been forced to think more carefully about where they run their services. They must process some data close to the point of consumption while shipping other parts back to the enterprise for processing.
The issue of data sovereignty only intensifies the emphasis on location. Even if a company doesn’t have its own policies governing data storage locations, its industry or government probably does. Germany, for example, mandates that customer data on German residents be stored manually, Goodman notes. These regulatory and security issues may mean that some data never moves to the cloud at all, especially in heavily regulated areas including finance and health care.
Still, that doesn’t mean that companies can’t mix on-premises and off-premises data processing and have them work together harmoniously. As enterprises define the best strategies for getting these workloads into the cloud, the parameters for evaluating CSPs are shifting. Basic qualities such as reliability and scalability are now the norm, not nice-to-haves. These qualities are expected and assumed as customers turn their attention to more sophisticated, nuanced requirements. That means “one size fits all” no longer cuts it as a cloud approach.
The power of cloud personalization
Today, companies have to ensure alignment between their core business and their CSP. Goodman points out that the workloads companies are transitioning to the cloud are increasingly industry specific, each carrying subtly different requirements, and many of them are critical to the business’s operations.
That’s why enterprises want a broad spectrum of control options and features, ranging from simple virtual machines to event-based serverless programming and catalogs of APIs for add-on services in areas such as artificial intelligence (AI). They also want to avoid vendor lock-in where possible.
In this climate, CSPs will need to reassure companies that they fundamentally know their business and can offer more than a simple commodity approach. Understanding cloud architecture will not be enough. Providers have to demonstrate that they understand enterprise IT architecture and domain-specific business needs.
Businesses will continue to rely on different cloud providers’ strengths in different areas. Goodman predicts that multicloud management will be a top pain point in 2019 as enterprises find themselves working with upwards of four or five different cloud providers, each servicing different technical or application-specific needs.
The opportunity and the responsibility lies with cloud service providers to help companies manage the complexity inherent in those relationships. The reason companies initially hesitated when moving some workloads to the cloud was that they were too complex to move in the first place. If providers want those workloads, they need to simplify the process of transitioning to the cloud.
CSPs and customers can complement and help each other, but a productive conversation between them has to begin with an assessment of the workload involved, the nature of the data that it’s storing and its requirements in areas such as privacy, performance and compliance. Together, they can create personalized cloud architectures that will provide the perfect home for every workload.
Check out the episode of the IBM Cloud Podcast to learn more about Goodman’s thoughts on cloud personalization and sharpen your skills at Think 2019.