Cloud
GCP
Google Cloud — strongest in data, analytics and machine learning (BigQuery, Vertex AI) and in Kubernetes, which Google originally created. Its networking and data tooling are excellent and pricing is competitive. It trails AWS and Azure in raw breadth and enterprise reach, so ecosystem depth varies by service.
Purpose
Google Cloud Platform is Google's public cloud, running on the same infrastructure as Search and YouTube. Its standout strengths are data and machine learning — BigQuery for serverless analytics at any scale, Vertex AI — and Kubernetes, which Google created and offers as the reference managed service (GKE).
When to Use It
Data-heavy products and analytics platforms gravitate to BigQuery; ML-centric teams to Vertex; container-native architectures to GKE, widely considered the most polished managed Kubernetes. Its global network and straightforward pricing appeal to startups.
Trade-offs
It trails AWS and Azure in service breadth, enterprise sales reach and third-party ecosystem, and Google's reputation for retiring products gives some enterprises pause. Skills and patterns transfer from the other clouds with modest translation.
Implementation
Core services: Compute Engine (VMs), Cloud Run (serverless containers — often the simplest deployment story in any cloud), GKE, Cloud Storage, Cloud SQL and BigQuery. Organise by projects, manage access with IAM, define with Terraform, and route data work through BigQuery to feel the platform's real advantage.