GCP Consulting

GCP (Google Cloud Platform) is a public cloud platform for building, running, and operating 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.

GCP is typically implemented through a landing-zone model that defines organization structure, networking, identity, and logging up front, then expands using infrastructure as code (often Terraform) and CI/CD automation. For an overview of Google’s cloud services, see https://cloud.google.com/.

• Compute and container services for VM-based and Kubernetes-based applications
• Managed storage and databases for transactional and distributed workloads
• Networking, IAM, and policy controls for secure multi-project environments
• Centralized logging, monitoring, and alerting for operational visibility
• Analytics and data processing services for batch, streaming, and warehousing

Running and maintaining a physical data center requires significant time and effort, with limited resources compared to the extensive options offered by various Cloud providers. In certain situations, managing physical infrastructure cannot be avoided due to security or budget constraints. Nonetheless, the diverse array of top-notch services provided by cloud providers, along with their seamless integrations and user-friendly interfaces, make them an excellent option for developing software applications.

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 and compliance controls using Organization Policies, standardized labels/tags, budget alerts, and audit-ready logging aligned to the Google Cloud Architecture Framework.
• Executed application and data migrations to GCP using phased cutovers, dependency mapping, 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 across architecture, reliability, security, and cost drivers.
• Define an adoption roadmap and landing zone design (org structure, projects, VPC networking, IAM, policies) aligned to your operating model.
• Implement production-ready GCP foundations using Infrastructure as Code with Terraform for repeatable, auditable environments.
• Standardize application and platform delivery with CI/CD and GitOps-style workflows to reduce lead time and improve change safety.
• Establish security and compliance guardrails including least-privilege IAM, secret/key management, centralized logging, and vulnerability scanning.
• Build observability with metrics, logs, traces, SLOs, and actionable alerting to improve incident response and reliability.
• Optimize performance and spend through rightsizing, autoscaling, committed use planning, and chargeback-ready cost allocation.
• Plan and execute migrations to GCP with cutover runbooks, testing, rollback strategies, and post-migration stabilization.
• Improve operational maturity with runbooks, on-call practices, automation, and troubleshooting support for production issues.
• Enable your teams through hands-on workshops and working sessions so they can operate, secure, and extend the platform confidently.