Platform

Google
Cloud

Google Cloud brings the infrastructure that powers Google's own products to everyone else. For businesses with data-intensive workloads, AI ambitions, or global scale requirements, that's a significant advantage.

Type

Hyperscale Cloud

Best for

Data & AI Workloads

Strength

Analytics & ML

Our use

Active

We use Google Cloud for its genuine strengths: world-class data and analytics infrastructure, leading AI and ML services, and a global network that delivers strong performance across regions. GCP's managed services — particularly around data warehousing, ML ops, and container orchestration — are among the best available. We choose it when the project's requirements align with where Google Cloud excels, not as a default.

Data-intensive applications and analytics platforms
AI and machine learning workloads using Vertex AI
Container-based applications on Google Kubernetes Engine
Serverless applications using Cloud Run and Cloud Functions
Firebase-powered mobile and web applications
Real-time data processing pipelines
Global web applications requiring low-latency delivery
BigQuery-based business intelligence and reporting systems
Compute
Compute Engine, Cloud Run, Cloud Functions, GKE
Storage
Cloud Storage, Persistent Disk, Filestore
Databases
Cloud SQL, Firestore, Bigtable, Spanner, Memorystore
Data & Analytics
BigQuery, Dataflow, Pub/Sub, Looker
AI and ML
Vertex AI, AutoML, Vision API, Natural Language API
DevOps
Cloud Build, Artifact Registry, Cloud Deploy

Google Cloud is the right choice for projects with significant data processing or analytics requirements, applications that benefit from Google's AI and ML services, Firebase-based mobile applications, and workloads that perform particularly well on Google's network infrastructure. It's also a strong choice for businesses already embedded in the Google Workspace ecosystem.

GCP engagements follow the same process as all our infrastructure work: architecture before configuration, security from the start, and full documentation on delivery. We make sure you understand the cost model, the monitoring setup, and the operational runbooks before we hand anything over.

Google Cloud's strength is in its data and AI services. When the project plays to those strengths, there's nothing better.

Building data-intensive or AI-powered software? Let's talk about Google Cloud.

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