Google Cloud solutions for data, containers and AI
Google Cloud provides compute, storage, databases and a strong set of data and AI services. It is a particularly good fit for analytics-heavy workloads, containerised applications and teams already using Firebase or Google Workspace.
Services such as Cloud Run make it simple to deploy containers without managing servers, BigQuery handles large-scale analytics well, and Google Kubernetes Engine is a mature managed Kubernetes option. Its service catalogue is smaller than AWS in some niche areas, and regional availability varies by service. We design around managed services, codify infrastructure and keep workloads portable in containers so you are not tied to one provider without good reason.
What we build with Google Cloud
- Cloud Run and GKE deployments
- BigQuery data warehousing
- Firebase and Google Cloud integration
- AI and Vertex AI integrations
- Migrations and cost optimisation
Google Cloud questions
What is Google Cloud best at?
It is strong for data analytics, managed containers and AI services. The right choice still depends on your team, existing tools and the services you need.
Can we run our existing containers on Google Cloud?
Yes. Containerised applications usually move to Cloud Run or GKE with modest changes, mainly around configuration, secrets and networking.
Who owns the Google Cloud project and billing account?
You do. Projects and billing are created under your own organisation, and our team is given IAM roles that you can review or remove at any time.
How do you keep Google Cloud costs under control?
We set budgets and alerts, label resources by project, choose scale-to-zero services such as Cloud Run where they fit and watch BigQuery query costs, which can grow quickly if left unchecked.
How is access managed on Google Cloud?
Through IAM roles granted to groups rather than individuals, dedicated service accounts per workload and organisation policies that block risky settings such as public storage buckets.
Can you migrate our data warehouse to BigQuery?
Yes. We map your existing schemas, move historical data in stages, rewrite queries and reports where needed and run both systems side by side until the numbers match.
Cloud Run or GKE?
Cloud Run suits stateless web services and APIs with far less to operate. GKE makes sense when you need fine control over networking, long-running workloads or many interdependent services.
How do you handle backups and disaster recovery on Google Cloud?
We use automated database backups with point-in-time recovery, versioned storage buckets and multi-zone or multi-region deployments sized to the downtime your business can tolerate.
Can we choose where our data is stored on Google Cloud?
Yes. Resources are created in the regions you select, and organisation policies can restrict which locations your team is allowed to use.
Can you add Google's AI services to our application?
Yes. We connect your application to Vertex AI and related services through secure service accounts, keeping your data in your own project and monitoring usage and cost.
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