The benefits delivered by the cloud model have become so well established that most IT and businesspeople can easily cite many of them: rapid application deployment, open-ended scalability, greater flexibility, faster responsiveness, lower capital and operational expenses, anywhere/anytime access… and the list goes on.
While many organizations had already experienced these and other cloud benefits as part of their day-to-day operations, however, the sudden emergence of the COVID-19 pandemic brought the cloud’s value into sharper relief. Offices were shut down, employees were dispersed to work from their homes, and many IT and business processes were thrown into turmoil – and for many the cloud proved essential to survival.
Looking back, it’s easy to argue that the prior decade-plus span of cloud adoption proved critical in helping many organizations successfully traverse the pandemic’s disruptions. Often, remote employees stayed productive and IT pros managed and secured dispersed IT operations thanks to pre-existing – or rapidly implemented – cloud services deployments.
Given this recent history, it’s no surprise that growing numbers or organizations are now embracing “cloud-first” IT policies. Broadly speaking, such policies position cloud-based solutions as the preferred option for new application deployments, data storage needs, and most ongoing IT infrastructure and service activities.
As discussed in an earlier post, however, simply moving existing applications into cloud environments isn’t the same as creating “cloud-native” solutions. The latter exploit such technologies as containers, Kubernetes orchestration, and Helm charts to allow organizations to create component-based applications. These applications, in turn, are more flexible, portable, and easier to deploy than monolithic legacy applications.
Another key attribute delivered by cloud-native solutions is one that resides at the top of many IT wish lists: increased automation. The open-sourced technologies typically used to create cloud-native software inherently embrace and provide process automation throughout the development, deployment, and management of containerized applications.
The reason for this characteristic, in essence, is because cloud-native technologies and techniques were born into a world in which automation had already become a high priority. By contrast, the earlier virtual machine (VM) deployment construct often requires IT departments to separately add automation solutions – including some that are vendor-specific – to different elements of their VM-based infrastructure after initial deployment.
Still, in order to realize the benefits of the cloud-native approach, an organization needs a broad range of skills and knowledge. Some of the required skills are fairly technical in nature, including expertise in Kubernetes and Helm chart development, or the ability to enhance existing applications with cloud-native technologies and modules.
Other necessary skills encompass everything from cultivating and coordinating tight relationships between the organization’s IT and business units and tackling cultural challenges. For example, in traditional software process, the development team produces the code, and the operations team then determines and implements the code’s ultimate configuration. In the cloud-native model, by contrast, the developers create and embed the software’s configuration into Helm charts, thereby assuming one of the roles previously held by the operations team.
Given the range and variety of skills, knowledge, and experience required to successfully adopt a cloud-native approach, many organizations will require assistance from third-party partners. In this regard, few partners can match HCL Software in its scope of cloud-native solutions and expertise.
In fact, to develop its growing portfolio of containerized software products – the HCL Solutions Factory (SoFy) – HCL Software went through an extensive process of evaluating a wide collection of applications, and then deciding how to enhance or recreate them using cloud-native technologies. To help standardize and aid these efforts, HCL created a detailed cloud-native maturity model, which serves as a best-practices guide for undertaking the cloud-native journey.
In a forthcoming post, we’ll explore some of the decisions organizations face when moving to cloud-native solutions, and will identify the core elements of HCL’s cloud-native maturity model.
For further information about HCL Software, its product portfolio, and its cloud-native expertise, visit.