Google Cloud demand rises

Google Cloud is gaining business as companies buy more artificial intelligence computing, pack more software onto Google Kubernetes Engine, and line up for Google’s Tensor Processing Units. (siliconangle.com) At Google Cloud Next in April 2026, company and industry speakers pointed to demand for the full stack: custom chips, rented compute, storage, networking, data tools and security controls. Google’s event coverage highlighted new infrastructure and Google Kubernetes Engine sessions aimed at artificial intelligence workloads. (cloud.google.com) (siliconangle.com) A Tensor Processing Unit is Google’s in-house artificial intelligence chip, the hardware that runs model training and model responses in the cloud. Google said its Ironwood Tensor Processing Unit can scale to 9,216 chips in one superpod, and the company has positioned it for high-volume inference, the step where a model answers a user request. (blog.google 1) (blog.google 2) Google Kubernetes Engine is the company’s managed version of Kubernetes, the software that spreads applications across many servers like an air-traffic system routing planes. Google has been pitching it as the control layer for artificial intelligence clusters, including tools to run inference on the same infrastructure as other workloads and to manage large groups of accelerated virtual machines as one unit. (cloud.google.com 1) (cloud.google.com 2) The growth numbers in circulation are large. SiliconANGLE reported Alphabet’s cloud business grew 48% from a year earlier in the fourth quarter of 2025 and that cloud backlog rose 55% from the prior quarter, figures it cited as the fastest growth among the three biggest cloud providers. (siliconangle.com) As more companies move artificial intelligence systems into production, they also need tighter controls over who can touch data, models and infrastructure. Google’s architecture guidance for identity governance focuses on unused accounts, excess permissions, group-based access and approval flows for cloud resources. (docs.cloud.google.com) They also need observability, the logs, metrics and traces that show whether a system is healthy or failing. Google’s observability documentation says those services are built to collect and correlate telemetry from applications and the infrastructure underneath them, including Google Kubernetes Engine environments. (docs.cloud.google.com 1) (docs.cloud.google.com 2) Google is also trying to turn chip demand into a broader platform sale. Its cloud pitches around Ironwood pair the Tensor Processing Units with storage, networking, BigQuery data tools, Vertex AI services and security products, so customers buy an operating environment rather than a single accelerator. (cloud.google.com) (siliconangle.com) That puts Google more directly against Amazon Web Services and Microsoft Azure in the market for artificial intelligence infrastructure. The contest is no longer just about renting servers; it is about whether a cloud can supply chips, orchestration software, identity controls and monitoring tools in one approved setup that large companies can deploy at scale. (siliconangle.com) (cloud.google.com)