Cloud & DevOps
Google Cloud
Google Cloud (Google Cloud Platform, or GCP) is Google's suite of cloud computing services, covering compute, storage, networking, databases, data analytics, and machine learning infrastructure.
What Google Cloud is used for
Google Cloud provides the building blocks for running software without owning servers: virtual machines on Compute Engine, containers on Google Kubernetes Engine, serverless workloads on Cloud Run and Cloud Functions, and managed databases like Cloud SQL and Firestore. It is particularly known for data and AI services, with BigQuery for large-scale analytics and Vertex AI for machine learning. Organizations use it to host applications, process data pipelines, and build AI-powered products.
Why it matters for business software
Cloud choice shapes cost, capability, and hiring for years. Google Cloud's strengths in analytics, Kubernetes, and machine learning make it a strong fit for data-heavy products and AI features, and its serverless options let smaller teams run production systems with little operations overhead. Like its competitors it offers global regions, compliance certifications, and pay-as-you-go pricing, so the decision usually comes down to workload fit, existing tooling, and team expertise.
How Wizcoder AI Labs uses it
We build and operate client workloads on Google Cloud within our cloud and DevOps practice, and often choose it for analytics-driven platforms and AI workflow projects that benefit from BigQuery and Vertex AI.
Related terms
Where we use Google Cloud
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