BigQuery
A serverless warehouse — you write the query; there is no cluster to size or keep running.
Teams with spiky analytics load and data already in Google's estate.
We build and run on thisThe platform most of our data engineering lands on.
We design, build and run workloads on Google Cloud — BigQuery warehouses, GKE clusters, Vertex AI pipelines. Where you commit to spend, we can place that commitment through our partnership rather than leaving you at list.
Not a boxed licence — we design and operate workloads here, and can place your committed spend through us.
What we work with
The products, and who each one suits.
6 listed
Google Kubernetes Engine (GKE)
Managed Kubernetes, in Standard mode where you want the controls or Autopilot where you do not.
Anything containerised that has outgrown a single virtual machine.
Vertex AI
Google's managed platform for training, tuning and serving models, Gemini included.
Teams putting a model into production rather than into a notebook.
Cloud Run
Containers that scale to zero and bill by request.
APIs and internal services with uneven traffic.
Cloud SQL and AlloyDB
Managed PostgreSQL and MySQL; AlloyDB is the higher-throughput PostgreSQL option.
Applications that need a relational database somebody else patches at 2am.
Looker
A BI layer with a modelled semantic layer, so a metric has one definition.
Organisations tired of four spreadsheets disagreeing about revenue.
What buying through us changes
A partnership is only worth what it changes.
Better than list
On committed Google Cloud spend. Where you commit, we place that commitment through our partnership rather than you signing direct at list.
Named contacts
An escalation path into Google Cloud, not a support queue. Quota increases, region questions and the billing line nobody can explain go to a person.
Startup credits
Google runs a startup programme with cloud credits attached. We sponsor the application and write the technical case — the award is Google's call.
How we help
The work around the product.
- Landing zone — organisation, folders, projects, IAM and a billing structure set up before the first workload arrives.
- Migration — we assess what lifts, what gets rebuilt and what should stay where it is, with the cost difference attached to each.
- BigQuery modelling — partitioning, clustering, slot reservations and query patterns that keep the bill flat as volume grows.
- GKE build and run — cluster design, Terraform, Argo CD delivery, autoscaling and an upgrade cadence somebody owns.
- Cost engineering — committed use discounts, rightsizing, idle resource removal and a monthly review written in plain English.
- Security baseline — VPC Service Controls, CMEK where it is warranted, and logging that lands somewhere your auditor can reach.
Where this is not the answer
Google Cloud is not automatically the right platform. If your estate is Microsoft-centred, or the one managed service you need only exists on AWS, we will say so before you plan a migration around it. We are also not Google's support desk — for a product defect the fix is theirs; our part is getting it in front of the right person and staying on it.
Also in this category
Cloud & infrastructure
Next step
Buying Google Cloud? Talk to us first.
Tell us what you are trying to do and we will come back with the sizing, the licensing and the price — from a partner, within two working days.