Google Cloud Platform
Google Cloud Platform (GCP) is Google's suite of cloud computing services, offering infrastructure, platform, and software services for building, deploying, and scaling applications. It includes compute (virtual machines, containers, serverless), storage (object storage, databases), networking, data analytics, machine learning, and developer tools. GCP competes with AWS and Azure as a major public cloud provider. For non-technical readers, GCP provides computing resources on demand, like renting powerful computers, storage, and services from Google instead of buying and maintaining your own. Businesses use it to run websites, store data, process information, and build applications without managing physical hardware. You pay for what you use, and can scale up or down as needs change. GCP is known for its strengths in data analytics (BigQuery), machine learning, and Kubernetes (which Google created). It benefits from Google's global network infrastructure and experience running services at massive scale. While smaller in market share than AWS or Azure, it's particularly popular among data-intensive and analytics-focused organisations.
Official WebsiteWhen to use Google Cloud Platform
Choose GCP when you need cloud infrastructure, particularly if your workloads involve data analytics, machine learning, or Kubernetes. It's appropriate for startups benefiting from generous free tiers, enterprises seeking multi-cloud options, and organisations already using Google Workspace.
GCP is particularly strong for big data and analytics workloads, where tools like BigQuery offer competitive advantages. Consider it alongside AWS and Azure based on your specific requirements, existing skills, and pricing.
Why choose Google Cloud Platform?
Teams choose GCP for its technical excellence in specific areas: BigQuery for analytics, Kubernetes Engine for container orchestration, and machine learning services. Google's network infrastructure provides excellent global performance. Pricing is often competitive, particularly for data-intensive workloads. The platform appeals to technically sophisticated teams who value its engineering-focused approach.