Eficode has added an analytics module to a DevOps platform it makes available as a managed service.
Tuomas Keränen, product manager for Eficode ROOT, said Eficode ROOT Insights provides different types of end users with access to an analytics module designed to make it easier to understand how changes to a software development project will impact delivery timetables. To make that capability more accessible throughout the organization, Eficode has created dashboards for specific types of end users such as project managers.
Eficode has crafted a DevOps platform from various tools and platforms to create a toolchain based on best practices it has defined that the company then manages on behalf of end customers. Organizations can choose to have that DevOps platform hosted on-premises or in a public cloud. That approach frees organizations to devote more time and resources to building applications versus managing the DevOps platforms, said Keränen. Eficode ROOT Insights is provided as a complement software-as-a-service (SaaS) application.
As DevOps continues to evolve, it’s apparent that an alternative approach that relies on external IT service providers to manage the underlying platforms is gaining traction. Many IT organizations simply don’t have the expertise required to build and maintain a DevOps platform. The trade-off is that the best practices are defined by the external service provider, which means the IT organization needs to bend its culture to align with those best practices.
Another factor that potentially will push organizations toward managed DevOps services is analytics. As the amount of data that needs to be collected to drive analytics applications steadily increases, it becomes apparent that DevOps analytics applications are going to be invoked more easily as SaaS applications. Once an IT organization moves down that path, it’s not too long before the case is made for using the analytics platform to also host the DevOps platform. In addition, as machine learning algorithms and other forms of artificial intelligence (AI) are applied to DevOps, the volume of data required to drive an AI model may require an organization to rely more on external service providers to provide that expertise.
It’s not at all clear how many organizations may prefer a managed service approach to DevOps. Many of the earlier adopters of DevOps have built custom workflows that are designed specifically to optimize their software development life cycle. However, the adoption of DevOps has been uneven at best. As managed DevOps services proliferate, the number of organizations that can effectively embrace DevOps should increase significantly.
Of course, managing the tension between internal and external IT service providers is nothing new. However, given the complexity of DevOps processes, relying on a managed service requires a level of collaboration that is not easy to achieve. Just as importantly, once an organization decides to partner with a provider of a managed DevOps service, unraveling that relationship later may prove to be all but impossible.
