GCP consulting and hands-on support

GCP (Google Cloud Platform) is a public cloud platform for running application and data workloads on elastic, globally distributed infrastructure. It is commonly used by platform, DevOps, data, and security teams to provision environments, modernize legacy systems, and standardize governance across multiple projects with clear cost controls. For an overview of services, see https://cloud.google.com/.

GCP is often adopted through a landing-zone approach that defines organization structure, networking, identity, and logging up front, then scales using infrastructure as code (frequently Terraform) and CI/CD automation to keep environments consistent across teams.

• Compute options for VM-based and containerized applications
• Managed Kubernetes with Google Kubernetes Engine (GKE)
• Storage and managed databases for transactional and analytical workloads
• Networking, IAM, and policy controls for secure multi-project setups
• Centralized logging, monitoring, and alerting for operational visibility

GCP (Google Cloud Platform) is a public cloud platform for running application and data workloads on elastic, globally distributed infrastructure. It is commonly used to reduce operational overhead with managed services while supporting secure, scalable architectures and cost governance.

• Global regions and Google’s backbone network support low-latency delivery, resilient multi-zone designs, and disaster recovery patterns.
• Flexible compute options across VMs, Kubernetes, and serverless containers allow teams to match runtime choices to workload requirements.
• Managed Kubernetes with GKE enables standardized cluster operations, policy controls, and scalable container platforms.
• Serverless services such as Cloud Run simplify deployment for stateless services and event-driven workloads with per-request scaling.
• BigQuery provides a managed, scalable analytics warehouse with separation of storage and compute for predictable performance tuning.
• Streaming and batch data processing services support modern data pipelines without managing underlying infrastructure.
• IAM, service accounts, and Workload Identity enable least-privilege access and safer workload-to-service authentication patterns.
• Security capabilities including encryption by default, Cloud KMS, and organization policies support governance for regulated environments.
• Networking primitives such as VPC, shared VPC, Cloud VPN, and Interconnect support secure connectivity to on-prem and multi-cloud environments.
• Infrastructure automation integrates well with Terraform, enabling repeatable landing zones, standardized projects, and policy guardrails.
• Centralized observability with Cloud Logging and Monitoring supports SLO-based operations, faster incident response, and auditability.
• Billing exports, budgets, and alerts help attribute spend, detect anomalies, and optimize costs across projects and teams.

GCP is often a strong fit for organizations prioritizing analytics platforms, container orchestration, and managed data services. It benefits from early governance design, especially around organization and folder structure, IAM boundaries, and shared networking, to avoid project sprawl and unintended access paths.

Common alternatives include AWS and Microsoft Azure, plus Kubernetes-centric platforms such as OpenShift for hybrid deployments.

Our experience with GCP helped us build repeatable delivery patterns, automation, and operational guardrails that we apply to help clients run secure, scalable, and cost-controlled cloud platforms.

Some of the things we did include:

• Designed and provisioned GCP landing zones with Terraform/Terragrunt, including org/folder hierarchy, project factories, IAM baselines, Shared VPC, and clear separation of environments.
• Implemented governance controls using Organization Policies, standardized labels, budget alerts, and audit-ready logging aligned to the Google Cloud Architecture Framework.
• Planned and executed application and data migrations to GCP using dependency mapping, phased cutovers, runbooks, and rollback plans, including hybrid connectivity via Cloud VPN and Interconnect where needed.
• Built container platforms on GKE with hardened cluster baselines, node pool strategies, autoscaling, and GitOps-style delivery integrated with Kubernetes operating practices.
• Delivered CI/CD for applications and infrastructure, including artifact promotion, environment-specific releases, and automated security/quality checks tied to IaC changes.
• Set up observability with Cloud Monitoring and Cloud Logging, including SLOs, alert routing, dashboards, and metrics integration with Prometheus for teams standardizing on a unified monitoring stack.
• Hardened security posture with least-privilege IAM, Workload Identity patterns, Secret Manager adoption, network segmentation, and incident-ready audit trails across critical projects.
• Implemented data platforms on BigQuery and Cloud Storage, including ingestion pipelines, partitioning/clustering strategies, dataset governance, and query cost controls for analytics at scale.
• Designed high-availability and disaster recovery approaches across regions, including backup/restore automation, recovery runbooks, and regular recovery testing to validate RTO/RPO targets.
• Optimized cloud spend with rightsizing, commitment recommendations, budget guardrails, and chargeback/showback reporting so teams could forecast and control costs reliably.

This experience helped us accumulate significant knowledge across multiple GCP use-cases—from greenfield builds to migrations and ongoing optimization—and enables us to deliver high-quality GCP setups that are maintainable, observable, and ready to scale.

Some of the things we can help you do with GCP include:

• Assess your current GCP environment and deliver a prioritized report covering architecture, reliability, security posture, and cost drivers.
• Define an adoption roadmap and target operating model, including org/project structure, networking, IAM strategy, and policy guardrails.
• Design and implement a production-ready landing zone with standardized accounts, VPC patterns, logging, and shared services.
• Build repeatable GCP foundations using Infrastructure as Code with Terraform, including modular patterns and controlled promotion across environments.
• Standardize delivery with CI/CD and GitOps-style workflows to reduce lead time, improve change safety, and enforce approvals.
• Implement security and compliance controls such as least-privilege IAM, key/secret management, network segmentation, and centralized audit logging.
• Establish observability with metrics, logs, traces, SLOs, and actionable alerting to improve incident response and service reliability.
• Optimize performance and spend through rightsizing, autoscaling, commitment planning, and chargeback-ready tagging and cost allocation.
• Plan and execute migrations to GCP with cutover runbooks, testing strategy, rollback plans, and post-migration stabilization.
• Enable your teams through hands-on workshops, pairing, and operational runbooks so they can operate and evolve the platform confidently.