Traditional enterprise application platforms are usually built with Java Enterprise technologies and this is the case as well for OpsRamp. However, in machine learning (ML) world, Python is the most commonly used language, with Java rarely used. To develop ML components within enterprise platforms, such as the AIOps capabilities in OpsRamp, we have to run ML components as Python microservices and they communicate with Java microservices in the platform.

While open source technologies have seen widespread adoption over the last two decades, there is no denying the huge market share that proprietary (closed source) software commands in the enterprise. The largest software vendors like Microsoft, Oracle, IBM, SAP, and VMware have a variety of products that are market leaders in their respective technology categories.

In my previous post on new approaches to managing hybrid cloud environments, I discussed the issues that commonly arise for IT operations teams. While hybrid cloud gives IT great flexibility to design infrastructure that’s uniquely suitable to diverse business and user requirements, it also brings about more complexity. Hybrid and multi-cloud businesses generate significantly more IT event data and its coming from many more places now.

In the world of IT operations and infrastructure management, the year 2019 was full of jaw-dropping deals in the startup community and notable strategy shifts among the major cloud and tech players. Suffice to say that CIOs and VPs of infrastructure are faced with the ongoing challenge of delivering business value and agility amid heightened IT complexity.

The hype has gone off the charts for AI and machine learning tools' potential in IT organizations. It’s time to temper expectations and move towards a sensible adoption path. Artificial intelligence is not fairy dust sprinkled on a data center, despite the enthusiastic proclamations of many IT operations vendors today. A couple of years ago, AI was the bride atop the wedding cake. It was perfect, with promises to render obsolete errors and out-of-control performance issues.

How critical are open source applications for modern application and infrastructure modernization? Red Hat’s The State of Enterprise Open Source report found that more than two-thirds of IT leaders believe that open source software has a very important role to play in the enterprise and 59% of respondents expect to increase their use of open source in the next 12 months.

OpsRamp recently attended the Gartner IT Infrastructure, Operations, and Cloud Strategies Conference, where analysts addressed the future of digital operations management. In the opening keynote, and throughout many of the sessions, Gartner talked about how infrastructure technologies are increasingly becoming disruptive and endemic to business strategy.

The difference between machine learning for business and machine learning for consumers is that for business applications, you must deal with requirements that casual users won’t encounter.

In recent months, the major cloud and tech players have been unfurling their latest products and strategies to win enterprise dollars. One trend that’s catching fire is hybrid infrastructure management: the need to support a mix of on-premises, private cloud, and public cloud resources.

Today on the blog, we feature a conversation with Michael Krigsman, an industry analyst and host of CxOTalk. He has been named a top CIO and IT influencer by several industry organizations. Michael writes extensively on the evolution of customer experience, and why technology is more critical to the delivery of competitive, compelling digital experiences than ever before. MK: Customer experience is a significant driver of revenue over time.