Google Cloud Setup

Google Cloud Platform (GCP) is purpose-built for data, machine learning, and scalable container orchestration. With industry-leading tools like BigQuery, Vertex AI, and Google Kubernetes Engine (GKE), GCP provides a powerful foundation for modern applications. At SoniNow, we design and deploy GCP environments that leverage the platform's native strengths — delivering high-performance compute, intelligent storage, and a robust security model — all while keeping costs predictable.

Compute Engine

Google Compute Engine offers virtual machines running on Google's global infrastructure with unique advantages like live migration, custom machine types, and sustained-use discounts.

Machine Types and Configuration

GCP's custom machine types allow you to define exactly the vCPU and memory your workload needs — no more fixed instance families. We start with a baseline recommendation using GCP's Machine Type Recommender, which analyses historical usage and suggests optimal configurations. For standard workloads, E2 or N2 machine families provide excellent price-performance. For high-memory data processing, M3 machines offer up to 16 TB of memory.

Live Migration and Maintenance

GCP VMs benefit from live migration, which means Google's infrastructure moves your running instance to another host during maintenance without reboot. This provides exceptional uptime for stateful workloads. For workloads that require full control over maintenance events, we can configure sole-tenant nodes or set maintenance behaviour to "Migrate" or "Terminate" as appropriate.

Preemptible and Spot VMs

For batch processing, CI/CD workloads, and fault-tolerant data pipelines, we use Preemptible VMs (which last up to 24 hours) or Spot VMs (with no maximum runtime). These provide discounts of 60–91% compared to standard VMs. We design fallback strategies using instance groups with proportional preemptible and standard VMs.

Instance Groups and Load Balancing

Managed Instance Groups (MIGs) provide auto-healing and autoscaling based on CPU utilisation, load balancing capacity, or custom metrics. We configure multi-regional MIGs behind Google's Global HTTP(S) Load Balancer, which provides a single anycast IP address and routes traffic to the closest healthy backend — reducing latency and improving resilience.

Cloud Storage

Google Cloud Storage offers unified object storage with a single API for any volume of data, from frequently accessed content to archival data.

Storage Classes

Cloud Storage provides four primary classes: Standard (hot data, millisecond access), Nearline (30+ days), Coldline (90+ days), and Archive (365+ days). We configure Object Lifecycle Management policies to automatically transition objects between classes based on age and access patterns, potentially reducing storage costs by 60–80% for cold data.

Bucket Design and Permissions

Buckets are organised by use case — data-lake-raw, data-lake-processed, backups-prod, static-assets — with uniform bucket-level access enabled for consistency. We use IAM conditions to enforce access policies such as "only allow access from the production VPC" or "require encryption with a specific CMEK key."

Transfer Service and Backup

For migrating existing data, we use Storage Transfer Service for online transfers from AWS S3, Azure Blob Storage, or HTTP/HTTPS sources. For on-premises bulk data, we use Transfer Appliance. Automated backups are configured via Cloud Scheduler triggering scripts or via third-party backup solutions integrated with Cloud Storage versioning.

VPC Networking

Google Cloud's Virtual Private Cloud (VPC) is a global, software-defined networking resource that spans all regions without requiring peering or VPNs between them.

Global VPC and Subnet Mode

We design VPCs using custom mode subnets, carefully planning CIDR ranges to avoid overlap with on-premises networks. Since GCP VPCs are global, a single VPC can span multiple regions — simplifying network architecture for multi-regional deployments. VPC Flow Logs are enabled for network monitoring and security analysis.

Firewall Rules and Cloud Armor

GCP firewall rules are stateful and implemented at the edge of the VPC — they do not consume instance resources. We define hierarchical firewall rules (organisation-level, folder-level, project-level) that enforce security baselines. For web application protection, we deploy Cloud Armor with WAF rules, OWASP Top 10 protections, and adaptive DDoS shielding.

Hybrid Connectivity

Cloud VPN connects on-premises networks to GCP via IPSec tunnels with SLA-backed 99.9% availability. For higher bandwidth and lower latency, Cloud Interconnect provides dedicated connections from 50 Mbps to 100 Gbps. Network Connectivity Center aggregates multiple VPN and interconnect connections into a hub-and-spoke topology.

IAM and Security

Google Cloud's Identity and Access Management is deeply integrated with Google's identity infrastructure.

Resource Hierarchy and Policy Inheritance

GCP's resource hierarchy (Organization → Folders → Projects → Resources) enables policy inheritance. We structure this hierarchy around business units and environments — for example, a Production folder with inherited policies enforcing audit logging, MFA for all users, and location restrictions.

IAM Roles and Conditions

We follow the principle of least privilege using predefined roles (e.g., roles/storage.objectViewer) rather than primitive roles (roles/editor, roles/viewer). IAM Conditions add temporal, resource-based, and request-based constraints — for example, "grant compute.instanceAdmin only for instances tagged staging and only between 9 AM and 5 PM IST."

Security Command Center

Security Command Center (SCC) provides continuous monitoring of your GCP organisation for vulnerabilities, misconfigurations, and threat detection. We configure SCC with Event Threat Detection and Container Threat Detection for real-time security alerts. Cloud Audit Logs with Data Access audit logs track every API call for compliance and forensics.

Managed Services and Big Data

GCP truly shines with its managed analytics and AI services. We integrate your GCP setup with BigQuery for serverless data warehousing, Cloud Run for serverless container execution, Cloud Functions for event-driven compute, and Vertex AI for machine learning pipelines. Google Kubernetes Engine (GKE) provides managed Kubernetes with auto-pilot mode for hands-off cluster operations.

From a startup's first project to a multinational's enterprise organisation, SoniNow builds GCP environments that are secure, cost-optimised, and ready to leverage the full power of Google Cloud.