Google Cloud Platform (GCP)
Google Cloud Platform (GCP) is a public cloud computing platform that provides infrastructure, platform, and managed services for running applications, data workloads, and Artificial Intelligence (AI) at global scale.
- Infrastructure-as-a-Service (IaaS) for compute, storage, and networking
- Platform services for application development, containers, and APIs
- Managed data, analytics, and databases (data management and analytics)
- AI and Machine Learning (ML) services (AI infrastructure and ML platforms)
- Security, identity, and management tools for cloud governance (cloud security and operations)
More About Google Cloud Platform (GCP)
Google Cloud Platform (GCP) provides enterprise customers with on-demand compute, storage, networking, data, and AI services deployed on Google-managed global infrastructure. Organizations use GCP to host applications, build digital services, and run analytics and ML workloads without operating their own physical data centers. GCP is organized into service domains that align with common enterprise IT categories such as compute, storage, networking, data platforms, AI, security, and operations.
In the compute domain (cloud infrastructure), GCP offers virtual machines, managed container platforms, and serverless execution environments that support a range of operating systems and runtimes. These services integrate with Virtual Private Cloud (VPC) constructs, load balancing, and autoscaling to support multi-tier and microservices architectures. Many deployments follow standard reference architectures such as three-tier web applications, container-based services, and hybrid connectivity back to on-premises (on-prem) environments via VPNs or dedicated interconnects.
For data workloads, GCP provides managed relational and non-relational databases, object storage, file storage, and data warehousing services (data management and analytics). These offerings support SQL-based analytics, streaming ingestion, and batch processing with integration to Extract, Transform, Load (ETL) and data pipeline tooling. Enterprises use these services to build data lakes, data warehouses, and lakehouse-style environments, often combining structured and unstructured data for reporting, business intelligence, and ML model training.
GCP includes AI and ML services (AI infrastructure and ML platforms) that expose pre-built APIs as well as managed platforms for training and serving custom models. These services are designed to work with GCP’s storage and data platforms, enabling workflows that span data ingestion, feature engineering, training, and online or batch inference. Underlying AI infrastructure options include specialized hardware configurations for model training and inference.
Security and identity capabilities (cloud security) are integrated across GCP services, including identity and access management, key management, secrets handling, network security controls, and logging. These features support enterprise governance models, policy-based access control, and alignment with compliance requirements. Monitoring, logging, and operations tools (observability and cloud management) provide telemetry, metrics, and traces for applications and infrastructure, which enterprises use for troubleshooting, capacity planning, and reliability engineering.
From a marketplace and directory perspective, Google Cloud Platform (GCP) is categorized primarily as a hyperscale public cloud provider, with solution areas spanning cloud infrastructure, application platform services (PaaS), data management and analytics, AI infrastructure and ML platforms, security and identity, and observability and cloud management. Its services are used across industries for workloads such as transactional applications, web and mobile backends, analytics platforms, AI applications, and hybrid or multi-cloud architectures.