Google Cloud for data and apps.
We use Google Cloud for two jobs. Building a warehouse in BigQuery that answers real business questions, and shipping apps quickly on Cloud Run and Firebase.
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Google Cloud solutions what you can buy from us.
What we deliver on Google Cloud.
We pick Google Cloud for specific reasons, not as a default. BigQuery takes most of the engineering out of an analytics build. There is no cluster to size and no capacity to plan, so a small team can stand up a warehouse that answers real questions in weeks.
Cloud Run does the same for services: containers that scale to zero between peaks, which is the right economic shape for seasonal and bursty workloads. And Firebase remains the fastest credible route to auth, push and offline sync for a consumer product.
- BigQuery analytics platform Land your operational systems into BigQuery on an incremental schedule, modelled around the questions the business actually asks, with dashboards on top. No cluster to size. BigQuery Looker Studio ELT
- Cloud Run application delivery Containerised services that scale to zero between peaks, with Pub/Sub for asynchronous work and the estate written down as Terraform. The right shape for bursty and seasonal load. Cloud Run Pub/Sub Terraform
- Firebase mobile and web backends Auth, push and offline sync shipping in weeks, with the domain logic kept behind a documented API so the parts that later outgrow Firebase were never entangled with it. Firebase Firestore Cloud Messaging
- Vertex AI applications Model inference running inside your own project and region, with source documents in Cloud Storage under customer-managed keys and every request logged for review. Vertex AI Document AI CMEK
- Kubernetes on GKE Managed clusters for workloads that genuinely need them, with autoscaling, workload identity and a deployment pipeline your team can operate without a platform hire. GKE Autoscaling CI/CD
- Migration to Google Cloud Assessment, staged migration and a reversible cutover for teams moving off self-managed servers or consolidating onto a platform they already buy elsewhere. Assessment Migration Cost modelling
All product names, logos and brands are property of their respective owners and are used here to identify the solutions Zethic Technologies LLP delivers under its partnerships.
How we work on Google Cloud.
Pick the part you care about.
A warehouse the business actually queries
Modelled around the cross-system questions people ask, not a faithful copy of the source schemas.
- Incremental loads from your operational systems
- Partitioning and clustering so queries stay cheap
- Dashboards in Looker Studio on top
- Cost controls and query alerts before the surprise
Services that cost nothing when idle
Cloud Run and Pub/Sub with retry and dead-letter handling, suited to bursty and seasonal work.
- Containerised services scaling to zero
- Pub/Sub for asynchronous processing
- GKE where a managed cluster is genuinely needed
- Terraform for the whole estate
Firebase speed, without the ceiling
Ship fast on Firebase while keeping domain logic behind an API that can outlive it.
- Auth, push and offline sync from day one
- Firestore for client-facing data
- Domain logic in Cloud Run, not security rules
- A migration path that does not need a rewrite
Inference inside your own project
Vertex AI keeps model calls in a region and project you control, under agreements you already hold.
- Grounded retrieval over your own content
- Document AI for extraction workloads
- Customer-managed keys on source data
- Every request logged for review
Why us for Google Cloud.
What you get from working with us.
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Your project, your keys
We work inside your Google Cloud project with scoped service accounts, customer-managed keys where the data class needs them, and the estate written down as Terraform.
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Modelled for real questions
The difference between a warehouse that gets queried and one that gets a ticket is whether it was modelled around what the business asks. We start there.
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Firebase with an exit
Domain logic sits behind a documented API from day one, so the parts that will later outgrow Firebase were never entangled with it. Speed now, without a rewrite later.
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Cost is designed in
BigQuery is cheap when modelled and expensive when not. Partitioning, clustering and query alerts go in before anyone gets a surprise, not after.
Google Cloud FAQs
It is cheap when modelled and expensive when not, and the difference is almost entirely partitioning, clustering and whether queries scan what they need. We model for the questions being asked and put cost controls and query alerts in before anyone gets a surprise.
Yes, and it is a common reason people call us. What we normally find is business logic sitting in client-side security rules where nobody can test it. The way out is to move that logic behind a proper API service first, then decide about the database separately. Doing both at once is what turns this into a rewrite.
Yes. Claude models are available through Vertex AI, so inference runs inside your own project and region under agreements you already hold. For teams with data-residency constraints that is often the deciding factor, and we will raise it early rather than late.
Yours. We take scoped service accounts with the permissions the work needs, and the project, the Terraform state and the pipelines stay under your control. There is nothing to hand back because nothing was ever held.
For analytics-heavy work BigQuery is often the shortest path, and Cloud Run suits bursty services well. If identity already lives in Entra ID and the organisation is set up to operate Microsoft, Azure usually wins on total cost. We deliver all three and have no margin either way.
Tell us what you are trying to build.
Whether the platform is already decided or still an open question, a senior engineer will reply within one working day. No SDR, no slideware.
Already on a platform
Inherited a setup, or hitting its limits? We start with an audit of what runs, what it costs, what is exposed and whether backups restore.
Still deciding
We take no licence margin, so the recommendation follows your constraints. The honest answer is often the platform you already pay for.
Want to partner with us
Referral, joint delivery, or a product company needing an implementation team. Say which and a senior person will pick it up.
Tell us what you are trying to build.
Whether the platform is already decided or still an open question, a senior engineer will reply within one working day. No SDR, no slideware.