Tap into Google's world-class infrastructure, cutting-edge AI, and unrivalled data analytics capabilities. TotalCloudAI's certified architects design GCP solutions that turn your data into a competitive advantage -- from BigQuery analytics to Vertex AI and Kubernetes-native workloads on GKE.
Google Cloud Platform brings the same infrastructure that powers Google Search, YouTube, and Gmail to your enterprise workloads. GCP leads the industry in data analytics with BigQuery's serverless architecture processing petabytes in seconds, in AI/ML with Vertex AI and Google's Gemini foundation models, and in Kubernetes with GKE -- born from the same Borg technology that runs Google's own services. Google's premium-tier global network delivers the lowest latency and highest throughput between regions, whilst its commitment to sustainability means you are running on the cleanest cloud, with carbon-intelligent computing and 100% renewable energy matching. For organisations that prioritise data, AI, and open-source technologies, GCP is the clear choice.
Deep technical expertise across the full Google Cloud service catalogue.
We deploy Compute Engine instances with managed instance groups, GKE Autopilot clusters, Cloud Run serverless containers, and Cloud Functions. Our networking designs leverage VPC peering, Cloud Interconnect, Cloud NAT, and global HTTP(S) load balancers for high-performance, low-latency architectures.
We build end-to-end ML solutions on Vertex AI with AutoML, custom training pipelines, Model Garden for foundation models (Gemini, PaLM), and feature stores. Our MLOps implementations include model versioning, A/B serving, drift detection, and continuous training pipelines that keep models fresh.
We architect modern analytics platforms centred on BigQuery, with Dataflow for stream and batch processing, Dataproc for Spark workloads, Pub/Sub for messaging, and Looker for enterprise business intelligence. Our designs handle petabyte-scale datasets with sub-second query performance.
We implement Security Command Centre, Chronicle SIEM, BeyondCorp zero trust, Cloud Armor WAF, and VPC Service Controls. Our security architectures include organisation policies, asset inventory, and continuous compliance monitoring against CIS, ISO 27001, and GDPR benchmarks.
We set up Cloud Build CI/CD pipelines, Artifact Registry, Cloud Deploy for managed delivery, and Config Connector for Kubernetes-native IaC. Our GitOps workflows use Config Sync and Policy Controller for consistent, auditable cluster management across fleets.
We plan and execute migrations using Migrate to Virtual Machines, Database Migration Service, and Transfer Service. For modernisation, we refactor applications to Cloud Run or GKE, migrate data warehouses to BigQuery, and adopt Anthos for hybrid and multi-cloud Kubernetes management.
Our team holds industry-recognised Google Cloud certifications.
Production Kubernetes on GKE Autopilot with Anthos for multi-cluster, multi-cloud management, service mesh, and policy enforcement across hybrid estates.
Serverless, petabyte-scale analytics with BigQuery, including materialised views, BI Engine caching, ML predictions with BigQuery ML, and Omni for multi-cloud queries.
Custom ML model training, AutoML pipelines, model serving with online predictions, and generative AI applications using Google's Gemini foundation models.
Fully managed container runtime with automatic scaling, revision-based traffic splitting, and integration with Eventarc for event-driven serverless architectures.
Apache Beam-based stream and batch data processing with Dataflow, Dataproc for Spark/Hadoop, and Cloud Composer for orchestrated workflows.
Google-scale security analytics with Chronicle SIEM, Security Command Centre for asset protection, and Cloud Armor WAF for DDoS and bot mitigation.
Globally distributed, strongly consistent databases with Cloud Spanner, managed PostgreSQL/MySQL with Cloud SQL, and Firestore for serverless document databases.
Committed use discounts, sustained use discounts, preemptible VMs, billing export to BigQuery for custom cost analysis, and budget alerts with programmatic controls.
Automated build and deployment pipelines with Cloud Build, Cloud Deploy managed delivery, Artifact Registry, and Binary Authorisation for supply chain security.
Enterprise BI with Looker's semantic modelling layer, embedded analytics, and Looker Studio for self-service dashboards connected to BigQuery and other data sources.
A real-world enterprise architecture we build on GCP.
This architecture powers a real-time retail analytics platform processing millions of point-of-sale transactions, inventory events, and customer interactions daily across 500+ stores. Events are ingested via Pub/Sub into Dataflow streaming pipelines that enrich, transform, and load data into BigQuery in near real-time. Vertex AI models run demand forecasting and personalised product recommendations using feature data stored in Vertex AI Feature Store. Cloud Spanner serves as the transactional database for inventory management, providing global strong consistency across all store regions. The API tier runs on Cloud Run with auto-scaling from zero, fronted by a global HTTP(S) load balancer with Cloud Armor for bot protection. Looker provides executive dashboards with row-level security, and scheduled BigQuery ML models detect anomalous sales patterns for fraud prevention. The entire platform is managed with Terraform, deployed via Cloud Build, and monitored through Cloud Monitoring and Cloud Logging.
Pub/Sub, Dataflow, Cloud IoT, Transfer Service
Cloud Run, GKE Autopilot, Cloud Functions
BigQuery, Cloud Spanner, Cloud Storage, Firestore
Vertex AI, BigQuery ML, Looker, Dataproc
IAM, VPC SC, Cloud Armor, Chronicle, KMS
Cloud Build, Terraform, Cloud Deploy, Monitoring
A UK-based independent streaming platform needed to build a content recommendation engine and scalable video delivery infrastructure to compete with larger rivals. Their existing platform, hosted on shared infrastructure, suffered from buffering during peak hours, had no personalisation capabilities, and was unable to process the click-stream data needed to understand viewer behaviour.
The SolutionTotalCloudAI built the entire platform on GCP. Video transcoding was handled by Transcoder API with output stored in Cloud Storage and delivered via Cloud CDN. We built a real-time recommendation engine using Vertex AI with collaborative filtering and content-based models trained on viewer history ingested through Pub/Sub and processed in Dataflow. BigQuery served as the analytics backbone, enabling the product team to run complex viewer engagement queries in seconds. The application tier ran on GKE Autopilot with Cloud Armor protecting against DDoS attacks. We achieved 99.95% availability and reduced buffering incidents by 98%.
"The recommendation engine TotalCloudAI built on Vertex AI transformed our viewer engagement. Our subscribers now watch 34% more content, and the real-time analytics give us insights we never had before."
-- CTO, UK Streaming Platform
Absolutely. GCP powers some of the world's largest enterprises, including PayPal, HSBC, and Unilever. It offers enterprise-grade SLAs (99.99% for most services), comprehensive compliance certifications (ISO 27001, SOC 2, PCI-DSS, HIPAA), and advanced security features like BeyondCorp zero trust, VPC Service Controls, and Chronicle SIEM. Google's premium-tier global network provides the lowest inter-region latency of any cloud provider, making it ideal for globally distributed enterprise applications.
BigQuery is a fully serverless, petabyte-scale data warehouse that requires zero infrastructure management. Unlike Redshift or Synapse, there are no clusters to provision or resize. It offers separation of storage and compute, meaning you pay for queries and storage independently. BigQuery can process terabytes in seconds and petabytes in minutes, supports real-time streaming inserts, and includes built-in ML capabilities (BigQuery ML) so data analysts can build models using SQL. Its pricing model (on-demand or flat-rate slots) makes it extremely cost-effective for variable workloads.
Yes, we have extensive experience in cross-cloud migrations. We use GCP's Migrate to Virtual Machines for server workloads, Database Migration Service for MySQL and PostgreSQL databases, and Transfer Service for large data moves. We also map AWS/Azure services to their GCP equivalents (e.g., S3 to Cloud Storage, Lambda to Cloud Functions, RDS to Cloud SQL) and rebuild CI/CD pipelines on Cloud Build. Anthos can also manage workloads across clouds during a phased transition period.
Yes, Google Cloud has a region in London (europe-west2) with three availability zones, which is our recommended primary region for UK businesses requiring data residency. Additional European regions in Belgium, Netherlands, Finland, Frankfurt, Warsaw, Milan, Madrid, Paris, Turin, and Zurich provide excellent options for disaster recovery and low-latency serving to European customers. Google's private fibre network connects all regions with high bandwidth and low latency.
GCP is widely regarded as the leader in AI/ML cloud services. Vertex AI provides a unified platform for the entire ML lifecycle, from data labelling and feature engineering to model training, deployment, and monitoring. Google's Gemini foundation models are state-of-the-art, and Vertex AI Model Garden gives access to over 100 open-source and Google models. TPUs (Tensor Processing Units) offer purpose-built hardware for training large models at a fraction of GPU costs. BigQuery ML allows SQL-based model training, and Google's pre-trained APIs (Vision, Speech, Natural Language, Translation) make it easy to add AI capabilities without ML expertise.
GCP is often the most cost-effective cloud for compute and data workloads. Key advantages include automatic sustained use discounts (up to 30% off for running VMs more than 25% of the month, applied automatically without commitment), per-second billing, competitive committed use discount contracts, and preemptible VMs at up to 80% discount. BigQuery's on-demand pricing means you only pay for queries you run, making it far cheaper than provisioned data warehouses for variable workloads. Google also offers free egress to other clouds and competitive network pricing. Our clients typically see 20-40% savings compared to equivalent AWS or Azure deployments.
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