Kyndryl Expands Distributed Cloud Services With Google Cloud

Published: 2026-04-22 13:50:36 ET KD

Published on 04/22/2026 at 01:50 pm EDT

Kyndryl announced the expansion of its Distributed Cloud services with Google Cloud, designed to help enterprises transform with AI and modernize applications across private cloud, on-premises data centers, and edge computing environments. Kyndryl will provide end-to-end cloud and IT services ? from consulting and implementation to managed services ?

helping enterprises build and operate distributed cloud environments consistently across hybrid and multicloud infrastructures. Under the expanded collaboration, Kyndryl cloud and IT experts will help enterprises integrate Google Distributed Cloud (GDC) with Kubernetes-based application modernization on Google Kubernetes Engine (GKE), enabling organizations to run cloud-native workloads where their data sovereignty, regulatory or performance goals demand ? while maintaining control over where data resides and how it is governed.

Kyndryl's Distributed Cloud services provide a unified operating model that standardizes governance, security and lifecycle management across environments ? enabling workloads to run locally using Google Distributed Cloud to meet their sovereignty, latency and data residency goals. This approach also gives organizations the flexibility to place and move workloads across on-premises, private cloud, and public cloud environments as requirements evolve.

To support Kubernetes- and container-based application modernization, capabilities such as Gemini Enterprise can serve as an intelligent assistant to streamline the process, reduce complexity and accelerate adoption. Kyndryl's Distributed Cloud capabilities with Google Distributed Cloud help enterprises: · Accelerate application modernization through Kubernetes and containerization · Support data-intensive and AI-driven workloads closer to where data is generated. Together, Kyndryl and Google Cloud are enabling enterprises to accelerate innovation, improve cost efficiency, and enhance operational resilience as they scale AI and data workloads across distributed environments.