Jean Atelsek is a senior research analyst working across the Cloud & Managed Services Transformation channel and digital economics unit of 451 Research, a technology research group within S&P Global Market Intelligence. She covers vendors and technologies that manage or optimize public and private cloud total cost of operations, performance or consumption. This includes FinOps products, platforms and providers that help organizations forecast, analyze and optimize cloud spending based on data collected from the IT environment. In the cloud-native universe, Jean focuses on container-native software and platforms, serverless architectures, service mesh, and the converging worlds of observability, runtime policy enforcement and application networking. She also covers technology accelerators for application modernization, including the application of natural language processing and generative AI to effect code translation. As a maintainer of the quarterly Cloud Price Index, Jean tracks benchmark pricing for a selection of infrastructure and managed services around the world. With data collected from millions of hyperscaler SKUs, she looks at trends in pricing, service additions and regional expansion plans for the major public cloud providers. Prior to joining S&P Global Market Intelligence, Jean worked at Omdia in the telecom, networks and consumer technology sectors. She holds a BA from Oberlin College.
Linking generative AI models to the agents that are going to use them now has a standard for queries in the Model Context Protocol. Suddenly, all sorts of things are vying to be your data source of choice. What could go wrong?
Developer experience is an area where AI applications are showing significant return on investment, but there are significant hurdles to overcome in both changing established development patterns and integrating AI tooling.
Managing IT costs has always been a challenge, and the FinOps movement aims to address this issue. Analysts Jean Atelsek and Melanie Posey return to the podcast to discuss their research and insights from the FinOps X conference with host Eric Hanselman.
FinOps vendors face the same challenge as enterprises when marshaling customer data to make it accessible and consistent. Their progress on this score shows how companies in other segments may lean into the AI ecosystem, with silos of domain-specific data that can interact with other domains.
The company's platform accelerates legacy and mainframe modernization projects by helping software organizations understand their own code. It is building IP specific to legacy programming languages such as COBOL and PL/I to transform those languages' business rules and logic flows into AI-ready primitives that can be used for modern deployment.
The company's flagship SonarQube product is evolving into a suite of software for analyzing, securing and governing source code in a developer-friendly way. Sonar has made a series of acquisitions in recent months to incorporate IP for reducing friction in the development process with "actionable code intelligence."
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