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Cloud

Google Cloud

Google's cloud, strongest in data, analytics, AI and Kubernetes.

  • Public cloud (IaaS, PaaS)
  • Typical project: 2–6 months
  • Google

Overview

Google Cloud is the third of the big three. It is known for data and AI: BigQuery, a serverless data warehouse; Vertex AI and the Gemini models; and GKE, managed Kubernetes from the company that created Kubernetes.

Enterprises often pick it for analytics-heavy workloads or alongside Google Workspace. Its partner ecosystem is smaller than those of AWS and Azure, so check delivery capacity in your region.

Names you'll meet

  • BigQuery
  • Google Kubernetes Engine
  • Vertex AI
  • Gemini
  • Looker

What's inside

  1. 1

    Compute

    Compute Engine VMs, Cloud Run for serverless containers, GKE for Kubernetes.

  2. 2

    Data

    BigQuery, Dataflow, Pub/Sub and Spanner.

  3. 3

    AI

    Vertex AI to build and run models, including Gemini.

  4. 4

    Analytics

    Looker for governed BI on top of BigQuery.

Is it right for you?

Best for

  • Analytics platforms built around BigQuery
  • Containerised apps on GKE or Cloud Run
  • AI projects using Gemini and Vertex AI

Think twice if…

  • You need a large local partner bench; it is thinner in some regions
  • Your business apps are mostly Microsoft; Azure ties in more closely

Typical projects

  1. BigQuery data platform2–6 months
  2. Container platform on GKE8–20 weeks
  3. Migration from on-premises or another cloud4–9 months

Typical ranges, not quotes. Scope, data and team size move them most.

Roles you'll hire

  • Cloud architect
  • Data engineer
  • Kubernetes / platform engineer
  • ML engineer
Browse available talent

Questions to ask a vendor

  1. 1Which Google Cloud Specializations do you hold?
  2. 2How many certified Professional Cloud Architects work on accounts like ours?
  3. 3Do you have a reference running BigQuery at our data volume?
  4. 4How will you keep query costs predictable?

Find Google Cloud partners

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