Google Cloud Platform (GCP) — Data & AI Cloud
GCP environments stall when BigQuery costs spike, GKE clusters drift, and Vertex AI models sit unserved. Opsio's GCP managed services bring SRE discipline to your Google Cloud Platform — optimizing BigQuery slots, operating GKE with Autopilot, and deploying Vertex AI models so your data and engineering teams ship faster without firefighting infrastructure.
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GCP
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BigQuery
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GKE
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SRE Operations
What's Included
GKE Cluster Management & Autopilot
Production GKE operations including Autopilot mode configuration, node pool optimization, workload identity federation, network policies, horizontal pod autoscaling, and GKE Gateway API for ingress. We operate clusters with SRE practices — SLOs, error budgets, and incident management.
BigQuery Analytics Platform
End-to-end BigQuery administration covering dataset design, slot capacity management with reservations and autoscaling, BI Engine caching, materialized views, Looker integration, and cost controls. We typically reduce BigQuery spend through query optimization and governance.
Vertex AI & ML Operations
Production machine learning with Vertex AI including model training pipelines, model registry, online and batch prediction endpoints, feature store management, and GPU quota optimization. We deploy models to production with monitoring, A/B testing, and automated retraining.
GCP DevOps & Cloud Build
Full GCP DevOps services using Cloud Build for CI/CD, Artifact Registry for container and package management, Cloud Deploy for delivery pipelines, and Terraform modules for infrastructure provisioning. Pipeline templates ensure consistency across teams and environments.
GCP Security & Chronicle SIEM
Comprehensive security using Security Command Center for misconfiguration detection, Cloud Armor WAF rules, VPC Service Controls for data exfiltration prevention, and Chronicle SIEM for threat detection. Organization Policy constraints enforce compliance automatically.
GCP Cost Optimization & CUDs
FinOps practice leveraging Committed Use Discounts for compute and databases, sustained use discounts, preemptible and spot VMs, BigQuery slot reservations vs on-demand pricing, and active recommendations from the GCP Recommender API. Monthly cost reports with trend analysis.
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For us at Löfbergs, cybersecurity and compliance are a natural part of how we operate. The new EU NIS2 directive and Swedish Cybersecurity Act make it even more important to stay ahead. That is why we value our partnership with Opsio — their expertise and local presence give us the confidence and reliability our business-critical systems demand.
Löfbergs
Löfbergs Lila AB · Löfbergs
Expert Google Cloud Consulting for GCP Managed Services
GCP — the full form is Google Cloud Platform — is Google's enterprise cloud offering with over 150 services for compute, storage, data analytics, machine learning, and networking. GCP leads the industry in serverless data warehousing with BigQuery, container orchestration with GKE, and AI/ML capabilities with Vertex AI. For data-intensive organizations, GCP is often the strongest choice. Opsio's GCP managed services cover the entire platform: GKE cluster operations with Autopilot mode, BigQuery administration and slot optimization, Vertex AI model serving, Cloud Run serverless containers, Cloud SQL and Spanner databases, and security operations using Security Command Center, Cloud Armor, and Chronicle SIEM — all managed with Google SRE practices including SLOs, SLIs, and error budgets.
Our Google Cloud consulting services help organizations adopt GCP for new workloads or migrate from AWS and Azure — for VMware estates exiting Broadcom licensing, our migration playbook applies equally well to GCP as a landing zone. We build GCP DevOps pipelines using Cloud Build and GKE containerization, and Terraform-based infrastructure-as-code to ensure consistent, repeatable deployments across every environment from development through production. Larger consolidation programs are coordinated through our cloud migration services.
BigQuery cost management is where most GCP clients need immediate help. We optimize slot reservations, implement materialized views, configure BI Engine caching, and enforce query governance policies — the same FinOps discipline detailed in our cloud cost optimization playbook. Clients typically reduce BigQuery costs within the first month while improving query performance through partition pruning and clustering strategies, and our guide to choosing a GCP MSP walks through the evaluation criteria.
GKE operations require Kubernetes expertise combined with GCP-specific knowledge. We configure Autopilot for hands-off node management, workload identity for secure pod authentication, network policies for microsegmentation, and horizontal pod autoscaling tuned to your traffic patterns. Our SRE team monitors cluster health around the clock with custom SLO dashboards.
Security on GCP follows a defense-in-depth model. We deploy Security Command Center for vulnerability detection, Cloud Armor for WAF and DDoS protection, VPC Service Controls for data exfiltration prevention, and Chronicle SIEM for threat investigation. Compliance monitoring covers CIS Benchmarks, GDPR, SOC 2, and ISO 27001 with automated policy enforcement using Organization Policy constraints. Related Opsio services: Big Data Services — From Ingestion to Insight, GitLab CI/CD — DevSecOps Platform for End-to-End Delivery, and Azure Managed Services — Hybrid Cloud Done Right.
How Opsio Compares
| Capability | In-House Team | Other Provider | Opsio |
|---|---|---|---|
| GCP certifications | 1-2 certs typical | Varies widely | Full GCP stack certified |
| BigQuery optimization | Ad-hoc query tuning | Basic monitoring | Slot optimization + measurable savings |
| GKE operations | Developer-managed | Basic monitoring | SRE-operated with SLO dashboards |
| Vertex AI support | Data scientist self-service | Not offered | Production MLOps with monitoring |
| Security posture | Manual reviews | Basic SCC setup | SCC + Chronicle + VPC Controls |
| Cost governance | Monthly bill review | Quarterly audit | Continuous FinOps with CUD management |
| Typical annual cost | $250K+ (2-3 engineers) | $120-180K | $60-180K (fully managed) |
Ready to get started?
What You Get
Pricing & Investment Tiers
Transparent pricing. No hidden fees. Scope-based quotes.
GCP Architecture Assessment
$8,000–$18,000
1-2 week engagement
Migration & Implementation
$25,000–$75,000
Most popular — full migration
Managed GCP Operations
$5,000–$15,000/mo
Ongoing SRE operations
Transparent pricing. No hidden fees. Scope-based quotes.
Questions about pricing? Let's discuss your specific requirements.
Why Choose Opsio for Cloud Services
GCP managed services expertise
Certified operations across GKE, BigQuery, Vertex AI, and Cloud Run.
Google SRE practices
SLO, SLI, and error budget discipline applied to your environment.
BigQuery cost specialists
BigQuery savings through slot optimization and query governance.
GCP DevOps services
Cloud Build, Artifact Registry, and Terraform pipeline automation.
Multi-cloud capability
Unified management alongside AWS and Azure environments.
CUD and cost optimization
Committed Use Discounts, spot VMs, and sustained use management.
Not sure yet? Start with a pilot.
Begin with a focused 2-week assessment. See real results before committing to a full engagement. If you proceed, the pilot cost is credited toward your project.
Our 4-Phase Delivery Process
GCP Assessment & Strategy
Review current environment, evaluate GCP service fit, and design target architecture with cost projections. Deliverable: architecture blueprint and migration roadmap. Timeline: 1-2 weeks.
Foundation & Security
Deploy organization hierarchy, VPC networking with shared VPC, IAM policies, Security Command Center, logging, and monitoring foundation. Timeline: 2-3 weeks.
Migration & DevOps
Execute workload migration with Migrate for Compute Engine, configure BigQuery datasets, and build Cloud Build CI/CD pipelines with Terraform. Timeline: 4-8 weeks.
Operate & Innovate
24/7 SRE operations with BigQuery optimization, GKE cluster management, Vertex AI model serving, and continuous cost governance with monthly reporting. Timeline: Ongoing.
Key Takeaways
- GKE Cluster Management & Autopilot
- BigQuery Analytics Platform
- Vertex AI & ML Operations
- GCP DevOps & Cloud Build
- GCP Security & Chronicle SIEM
Industries Served by Opsio
Data & Analytics
BigQuery data warehouses with Looker dashboards and Dataflow pipelines.
AI & Machine Learning
Vertex AI production ML workloads with model monitoring and retraining.
SaaS & Technology
GKE and Cloud Run applications with auto-scaling and global load balancing.
Media & Entertainment
Content processing, transcoding, and delivery at global scale.
Google Cloud Platform (GCP) — Data & AI Cloud — FAQ
What does GCP stand for — what is the GCP full form?
GCP stands for Google Cloud Platform. It is Google's suite of cloud computing services offering over 150 products across compute, storage, data analytics, machine learning, and networking. GCP is particularly strong in serverless data analytics with BigQuery, container orchestration with GKE, and AI/ML with Vertex AI. The platform is used by organizations that prioritize data-driven decision making and AI capabilities. GCP also offers competitive pricing through sustained use discounts and committed use discounts. Its global fiber network provides low-latency connectivity between regions, making it an excellent choice for globally distributed applications and real-time data processing workloads.
What do Opsio's GCP managed services include?
Our GCP managed services cover 24/7 SRE operations for GKE clusters, BigQuery platform administration and cost optimization, Vertex AI model serving and monitoring, Cloud Run management, security monitoring with Security Command Center and Chronicle SIEM, cost optimization with CUDs and spot VMs, and GCP DevOps services including Cloud Build CI/CD pipelines and Terraform automation. Each service includes SLA-backed response times, proactive monitoring, and monthly reporting. Our GCP-certified engineers manage your environment end-to-end so your internal team can focus on building features and analyzing data rather than managing infrastructure.
How much do Google Cloud consulting services cost?
GCP architecture assessments are a one-time $8,000-$18,000 investment. Migration and implementation projects range from $25,000 to $75,000 depending on scope. Managed GCP operations range from $5,000 to $15,000 per month. Our CUD and BigQuery optimization practice typically reduces GCP spend compared with on-demand pricing. Regular FinOps reviews typically find savings that offset part of the management fee. For example, a data-intensive organization spending $30,000 monthly on BigQuery and GKE typically saves $8,000-$12,000 through slot reservations, committed use discounts, and workload right-sizing. We provide transparent monthly cost reports that detail savings by category and identify new optimization opportunities.
How does Opsio optimize BigQuery costs?
We analyze query patterns to determine optimal pricing model — on-demand versus flat-rate slot reservations. We implement materialized views for repeated queries, BI Engine caching for dashboard workloads, partition pruning and clustering for scan reduction, and query governance policies to prevent runaway costs. Clients typically lower BigQuery spend within the first month. For example, we identify expensive recurring queries that scan entire tables and add clustering keys or materialized views to reduce bytes processed by 80% or more. We also configure custom quotas per project and user to prevent individual queries from consuming excessive resources unexpectedly.
Can Opsio migrate workloads from AWS or Azure to GCP?
Yes. We use Migrate for Compute Engine for VM migrations, Database Migration Service for MySQL and PostgreSQL, and Transfer Service for storage migrations. Every migration includes application assessment, dependency mapping, rehearsal cutover, and performance validation. We also support multi-cloud architectures where GCP handles analytics while AWS or Azure runs other workloads. A common pattern is migrating data analytics and machine learning workloads to GCP for BigQuery and Vertex AI while keeping application workloads on AWS or Azure. Our cross-cloud networking expertise ensures secure, low-latency connectivity between environments through dedicated interconnects or VPN tunnels.
How does Opsio manage GKE clusters?
We configure GKE Autopilot for hands-off node management or Standard mode with custom node pools for specialized workloads. Operations include workload identity for secure authentication, network policies for microsegmentation, horizontal pod autoscaling, GKE Gateway API for ingress, and custom SLO dashboards. Our SRE team monitors cluster health 24/7 and handles node upgrades, security patches, and capacity planning proactively. For GPU-intensive workloads like machine learning inference, we configure dedicated node pools with appropriate accelerators. GKE's integration with Google's networking infrastructure provides superior pod-to-pod performance compared to other managed Kubernetes platforms in most benchmarks.
What GCP security services does Opsio implement?
We deploy Security Command Center Premium for vulnerability and threat detection, Cloud Armor for WAF and DDoS protection, VPC Service Controls for data exfiltration prevention, Chronicle SIEM for threat investigation, and Organization Policy constraints for compliance enforcement. Security posture is monitored continuously with weekly reporting against CIS, GDPR, and SOC 2 frameworks. For example, VPC Service Controls create security perimeters around sensitive BigQuery datasets and Cloud Storage buckets to prevent data from leaving authorized boundaries. Chronicle's petabyte-scale log analysis enables rapid threat hunting across your entire GCP environment with automated correlation of suspicious activity patterns.
What is the difference between GCP and AWS?
GCP excels in data analytics (BigQuery is unmatched for serverless warehousing), AI/ML (Vertex AI with TPU access), and Kubernetes (GKE originated from Google's internal Borg system). AWS leads in breadth of services (200+ versus 150+) and enterprise ecosystem. Many organizations use both — GCP for data and ML workloads, AWS for general compute and enterprise applications. GCP also offers competitive pricing with sustained use discounts that apply automatically without commitment. The choice depends on your primary workload types, team expertise, and existing vendor relationships. Opsio is certified across both platforms and helps you leverage each provider's strengths effectively.
Does Opsio support Vertex AI for production ML?
Yes. We deploy production ML workloads on Vertex AI including training pipelines, model registry, online and batch prediction endpoints, feature store management, model monitoring for drift detection, and GPU quota optimization. Our MLOps practice integrates Vertex AI with your CI/CD pipelines for automated model deployment and retraining workflows. For example, we configure automated retraining triggers when model performance degrades below defined thresholds, with champion-challenger testing before promoting new model versions. Our monitoring tracks prediction latency, feature distribution drift, and accuracy metrics against ground truth labels to ensure production models maintain their effectiveness over time.
How does Opsio handle GCP cost optimization beyond CUDs?
Beyond Committed Use Discounts, we leverage sustained use discounts for consistent workloads, preemptible and spot VMs for batch processing, BigQuery slot reservations for predictable analytics costs, Cloud Storage lifecycle policies for data tiering, and the GCP Recommender API for proactive right-sizing. Monthly FinOps reports track savings and identify new optimization opportunities. For example, we configure automated lifecycle policies that move infrequently accessed data from Standard to Nearline and eventually Coldline storage, reducing storage costs by up to 80%. We also identify idle resources such as unattached persistent disks and unused static IP addresses that accumulate unnecessary charges over time.
Still have questions? Our team is ready to help.
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Google Cloud Platform (GCP) — Data & AI Cloud
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