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Google's cloud: strong in data, Kubernetes, and AI, with its own billing personality.
Quick Definition
Google Cloud Platform (GCP) is Google's public cloud, offering compute, storage, data analytics, AI/ML, and Kubernetes services. Known for data and machine-learning strengths, GCP uses consumption and committed-use pricing and is a core platform in multi-cloud FinOps.
Google Cloud Platform is the third of the big three hyperscalers, behind AWS and Azure. It is best known for data and analytics services like BigQuery, for AI infrastructure, and for Kubernetes, which Google created and runs as the managed GKE service.
GCP's billing model has distinctive features. Sustained use discounts apply automatically when workloads run most of the month, no purchase required. Committed use discounts mirror reserved capacity elsewhere. Per-second billing and custom machine sizes give finer control than rivals in places, but BigQuery's consumption pricing surprises teams that scan large datasets carelessly.
Example. A retail company keeps its main systems on AWS but runs analytics on BigQuery because its analysts query terabytes interactively. It becomes a multi-cloud shop through workload fit rather than strategy.
Cost discipline on GCP follows the same fundamentals as anywhere: allocate, rightsize, commit carefully. The AWS vs Azure vs GCP comparison frames the platform choice, and the Purplle case study shows $200K of GCP savings found in one month.
Automatic discounts GCP applies when a workload runs a large share of the month. They require no commitment or planning.
Sometimes, by service and region. List prices differ less than architecture and discount strategy do. Compare your actual workload.
Analytics, Kubernetes, and AI tooling. BigQuery and GKE are frequently the reason companies adopt GCP at all.