Consider application modernization and focusing on data, analytics and AI when building out your respective cloud strategy. Image: alice_photo/Adobe Stock Cloud is now the centerpiece of enterprise IT, even in Continue Reading
Consider application modernization and focusing on data, analytics and AI when building out your respective cloud strategy.
Cloud is now the centerpiece of enterprise IT, even in organizations where a majority of workloads remain in a user data center. But moving the cloud doesn’t necessarily deliver modernization, let alone a platform for innovation. As IT budgets tighten, technology decision-makers must find ways to economize while opening a path to productivity and innovation. Achieving that goal requires a strategic approach and an embrace of cloud-native technologies.
Cloud strategy starts by determining which workloads are not cloud-ready — cases where data sovereignty, security and latency (and, in some cases, costs) rule out public cloud in the near- to medium term. Simply transitioning the rest of your applications and data to cloud can result in greater resilience, but without modernization, it is simply a change in data centers.
When developing a cloud strategy for their enterprise, tech decision-makers should focus on organizational enablement and outcomes. In doing so, there are several considerations to bear in mind.
IT modernization is the goal; cloud is just one means to that end.
Cloud engendered new ways of organizing compute with cloud-native technologies such as Kubernetes and serverless. Start with those modern platforms — whether in your data center or in the public cloud — for more efficient use of IT resources with greater dynamism and scale.
Kubernetes provides a flexible platform to build on new technologies, from ModelOps for AI to deploying compute at the edge in retail, manufacturing and transportation. Kubernetes also transcends the cloud/on-premises divide with hybrid solutions from public cloud providers and multicloud development platforms to orchestrate containerized applications.
Application modernization is central to cloud strategy.
The task of standing up a data center app in the cloud is usually straightforward, but it’s often just a step sideways. Containerize existing applications where possible to enable them to run on Kubernetes platforms. If apps are monolithic and heavily customized, you can move functionality such as user interfaces into new applications in containers that can incorporate new features. New application development based on containers and a modern development toolchain can be more easily aligned to business or organizational goals and focused on new products or services.
Data, analytics and AI/ML are now the strategic focus.
Cloud infrastructure is being commodified through open source efforts such as Kubernetes and a price war among the major cloud players, aside from differentiators such as custom silicon or 5G capabilities. Cloud providers are battling it out to be a platform for data and analytics and infusing AI wherever they can into cloud services.
Although the AI-enabled search wars are grabbing attention, enterprises should put data, analytics and AI at the center of their cloud strategy with an emphasis on business intelligence. Stakeholders across every large business or government entity are calling on IT leaders for guidance. Success depends in large part on systematic delivery and avoidance of service-by-service sprawl amid a scramble to implement the latest AI tech.
Developer enablement isn’t an add-on.
Application teams sniffed at the early editions of cloud provider development platforms — but not anymore. Function as a service gave developers an appetite for building directly on cloud infrastructure; now, serverless containers, edge development platforms and integrated developer toolchains are attractive for entire classes of applications.
Sometimes the resulting dependencies on cloud provider infrastructure are worth it — other times, they’re not. The answer depends on your cloud strategy. If faster time to market is the priority, a proprietary cloud service might be the best approach. If portability is the overriding goal, look elsewhere. Increasingly, that’s an app-by-app choice within a cloud environment. To help developers innovate, put the right application development environment on the right cloud.
Contemporary IT strategy considers multicloud, hybrid and edge.
Enterprises may be single-cloud users today and for the near- to medium term. Nevertheless, effective cloud strategy means taking a vendor-neutral approach that can incorporate multiple clouds.
For example, a cloud customer may consider Amazon Web Services or Google Cloud Platform as the primary cloud provider. But if they sign up for Microsoft 365, they get a free Azure Active Directory account. If they turn on the pay-only Azure AD features, they’re suddenly Azure users.
When a developer chooses to build an app on a content developer network, that customer becomes an edge user, too. If a cloud provider’s Kubernetes cluster manager controls a few clusters running in the data center, that’s hybrid. Making these deployments on an incremental basis can result in unnecessary costs without any other gains. An intentional, strategic approach creates an innovation platform.
Cloud security and governance don’t have to hamper innovation.
The notion that security and governance inhibit IT innovation has always been overdone. In the cloud era, it is irrelevant. A cloud center of excellence that incorporates all stakeholders — from risk management to auditors to vendor management, as well as business units or departmental groups — helps align IT with overall organizational goals. Adopting a cloud service that can’t pass muster for oversight groups is a waste of time, money and resources. Internal alignment is a precondition for allowing sufficient resources for developers to innovate.
By taking this more expansive approach to cloud strategy, organizations can lay the basis for innovation on multiple fronts by automating operations, enabling developers and putting actionable data, analytics and AI into the hands of business users.
To access further Forrester insights about how enterprises can modernize their tech faster with cloud, visit here.
Lee Sustar is a principal analyst at Forrester, focusing on public cloud, containers, modernization and the wider transition to cloud-native computing and practices. Key markets that Lee covers include multicloud container development platforms, public cloud enterprise container platforms and public cloud infrastructure and development platforms. A graduate of Northwestern University, Lee has more than two decades of experience in information, cybersecurity and cyber risk management.
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