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Shivacha — Simplifying Tech Solutions
Shivacha CloudCloud Architecture, Migration & Operations

Google Cloud Development

Build on Google Cloud — GKE, Cloud Run, BigQuery, AI services, networking and security architecture.

Production · multi-region
Illustrative

Region Aactive

Load balancer · WAF
api web worker
Postgres primary Object storage

Region Bstandby

Load balancer · WAF
api web worker
Postgres replica Object storage

Async replication · automated failover · backups tested

Observability

MetricsLogsTracesSLO alerts

Security

IAMSecretsPrivate networkIaC

Overview

Google Cloud is strong in data, analytics, AI and Kubernetes. We design and build on Google Cloud: organisation and project structure, networking, GKE and Cloud Run workloads, BigQuery data platforms, AI service integration, security controls and cost management — defined as code and designed for operability.

Common use cases

  • Data and analytics platformBigQuery-centric analytics.
  • Kubernetes workloadsGKE-based platforms.
  • Serverless containersCloud Run services.
  • AI workloadsModel serving and AI services.

Quick answers

Google Cloud Development at a glance

The essentials in brief. Every project is scoped individually — ask us for specifics.

What is google cloud development?
Build on Google Cloud — GKE, Cloud Run, BigQuery, AI services, networking and security architecture.
Who is it for?
Typically companies migrating to the cloud, teams whose releases are slow or risky, and organisations that need stronger reliability, security or cost control.
What does Shivacha provide?
  • Organisation design
  • Compute
  • Data
  • AI integration
  • Security
  • Infrastructure as code
Which technologies are used?
Google Cloud, BigQuery, Kubernetes, Terraform, Amazon Web Services, Microsoft Azure — chosen to fit your stack and constraints.
How does the process work?
Discovery & assessment → Landing zone → Migration waves → Optimisation → Managed operations.
What affects the cost?
  • Number of applications and environments
  • Compliance and data-residency requirements
  • Availability and recovery objectives
  • Existing automation and IaC maturity
  • Multi-cloud or hybrid scope
  • Ongoing managed-service needs
How long does it take?
Assessments take 2–4 weeks; platform builds and migrations are usually delivered in 2–6 month phases.
How do I get started?
Share a short brief in the form below, book a 30-minute call or message us on WhatsApp. A senior engineer replies within one business day; NDA on request.

Capabilities

What we deliver

Organisation design

Folders, projects and policies.

Compute

GKE, Cloud Run and Compute Engine.

Data

BigQuery, Cloud SQL and Pub/Sub.

AI integration

Model hosting and APIs.

Security

IAM, VPC Service Controls and KMS.

Infrastructure as code

Terraform-based environments.

Architecture

Engineered right from day one

The layers we typically design for cloud architecture, migration & operations, adapted to your stack and partners.

  • Right migration strategyNot everything should be refactored; not everything should be lifted.
  • Data residencyRegion choices aligned with regulatory and customer requirements.
  • Cost governanceTagging, budgets and alerts from day one.
  • Tested recoveryDisaster recovery exercised, not just documented.
Cloud Architecture, Migration & Operations · reference architecture
5Organisation
Accounts / subscriptionsGuardrailsBilling
4Network
VPCsPrivate connectivityDNSEdge
3Workloads
KubernetesServerlessVMsManaged data
2Resilience
Multi-AZBackupsDR regionsFailover
1Operations
MonitoringPatchingCost managementIncident response

Delivery

How an engagement runs

  1. 1

    Discovery & assessment

    Inventory, dependencies, performance baselines and cost model.

  2. 2

    Landing zone

    Account structure, network, identity and guardrails as code.

  3. 3

    Migration waves

    Rehost, replatform or refactor per workload with rollback plans.

  4. 4

    Optimisation

    Rightsizing, reserved capacity and architecture improvements.

  5. 5

    Managed operations

    Ongoing monitoring, patching, backups and incident response.

Security

Security built into delivery

Controls we apply by default on this kind of work — not a separate phase at the end.

Infrastructure as code

Every change reviewed, versioned and reproducible.

Identity & network

Least-privilege IAM, private networking and zero-trust access.

Secrets & encryption

Central secrets management and encryption by default.

Monitoring

Alerting, audit logs and incident runbooks from day one.

Dedicated team

Cloud Engineering Team

Cloud architects and engineers for AWS, Azure and Google Cloud.

FAQ

Frequently asked questions

Is Google Cloud good for AI workloads?

It offers strong AI infrastructure and managed services; the best choice depends on your existing stack and requirements.

Are you a Google Cloud partner?

We do not claim formal partner status; our engineers work extensively with Google Cloud.

Which cloud should we choose?

It depends on your workloads, existing licences and contracts, team skills, data residency and specific managed services you need. We provide a neutral comparison and recommendation.

Can you reduce our cloud bill?

Usually. Common savings come from rightsizing, scheduling non-production environments, storage lifecycle policies, commitment discounts and architectural changes. We quantify opportunities after an assessment rather than promising percentages up front.

Next step

Discuss Enterprise Deployment.

Tell us about your google cloud development requirements — goals, timeline and constraints. We will reply with questions, an approach and next steps.

  • Senior engineer reads every enquiry
  • Reply within one business day
  • NDA on request

Prefer to talk first?

Book a 30-minute call, or message the nearest team on WhatsApp.

Book a Call

Your details are used only to reply to this enquiry.

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