Multi-Cloud is fast becoming the norm in the enterprise. At Rishidot Research, we estimate that most organizations will use more than one cloud provider by 2020. A recent survey by RightScale of 1,000 IT professionals found 85% of enterprises now have a multi-cloud strategy, up from 82% in 2016. Multi-cloud is fast becoming the de […]
AIOps: Few Considerations For Enterprise Decision Makers
AIOps is fast becoming the next big buzzword and is about using AI as the driver for operations. The early use of machine learning is in the area of observability while some vendors like Swim.ai use deep learning to offer intelligence at the edge. We expect to see more vendors using machine learning or deep […]
Anaconda, The Cloud Native Platform For ML/AI Workloads
The two sweeping trends in Modern Enterprise today are Machine Learning and Cloud Native. Our research shows that by 2020, most modern enterprise decision-makers will be focussed on scalable machine learning systems to meet their needs. Scalability is driven by cloud native, with docker based containers and Kubernetes playing a major role, and Python is […]
Research Brief: Observability and Modern Enterprise
Summary The term Observability is fast moving towards the peak of the hype cycle but it is critical to managing the cloud native architectures in any modern enterprise. In this research brief, we stake out our position on the evolution of Observability in IT operations and highlight the potential of using machine learning and artificial […]
AI In Observability: Splunk Goes Further Bringing AI To Their Products
The role of Machine Learning and Artificial Intelligence in Observability is one of the focus area of research for us in Rishidot Research. It is our strong belief that using ML and AI on Observability data is absolutely necessary for the next generation observability products because Cloud native makes enterprise IT more distributed adding multiple […]
Virtual Panel: The role of ML/AI in Observability
Yesterday, we organized a virtual panel on the role of ML and AI on Observability. Our guests for the panel include: Andy Mann from Splunk Aneel Lakhani from Honeycomb Eric Wright from Turbonomic Rob Hirschfeld from RackN Andi and Eric took a more progressive view on the role of ML and AI while Aneel took […]
Swim.ai: AI, Observability and Edge Computing
With IoT becoming the norm across many industries, manufacturing to retail to public utilities to supply chain to many verticals across the spectrum, it becomes important to focus on the intelligence needed to ensure that this truly distributed system of devices are working seamlessly. In fact, we would even claim that the role of IT […]
The increasing role of ML/AI In Observability
With Cloud Native becoming the hot topic in the modern enterprise space, the focus is shifting from the nature of underlying infrastructure for cloud native applications to topics like monitoring, log analytics, tracing, etc.. Not just the tools but the focus is also shifting on what one should be doing with these tools in the […]
Automation to Autonomic Computing: AI’s Increasing Role In Operations
Autonomic computing is not new. It has been in vogue since 2001 after IBM talked about it. But it has been in the sidelines ever since, as a research project with little mainstream attention. Industry conversation has centered on automation with cloud as the underlying fabric. Even though analytics has been playing a critical role […]