Google Cloud Platform

Google Cloud Platform

Google Cloud Platform

Data-driven Google Cloud automation for scalable and intelligent operations

Data-driven Google Cloud automation for scalable and intelligent operations

Data-driven Google Cloud automation for scalable and intelligent operations

EZOps Cloud designs, operates and optimizes Google Cloud environments built for performance, analytics and automation at scale. From infrastructure automation to data engineering and Kubernetes orchestration, we build GCP foundations that accelerate delivery, strengthen governance and support long-term innovation.

What we deliver

From infrastructure automation and Kubernetes orchestration to data platforms and secure workload operations, we transform Google Cloud environments into scalable, analytics-ready systems engineered for innovation and continuous delivery.

Why choose EZOps Cloud

We transform Google Cloud into a data-centric execution platform. By unifying DevOps, data engineering and automation, we build workloads optimized for scalable delivery, analytics and AI-driven operations, enabling innovation without increasing operational overhead.

What you get

  • IaC automation and deployment pipelines.

  • Kubernetes orchestration with GKE.

  • Data platforms for analytics and AI workloads.

  • Security controls and workload governance.

  • FinOps and cost optimization.

Technical capabilities for data-driven GCP operations

Technical capabilities for data-driven GCP operations

Technical capabilities for data-driven GCP operations

Cloud Computing

Optimized GCP compute services for modern applications and scalable, containerized environments.

  • Compute Engine: Elastic virtual machines for any workload.

  • Google Kubernetes Engine (GKE): Managed Kubernetes at scale.

  • App Engine: Fully managed environment for running applications.

Cloud Storage

Google Cloud storage services for files, objects, and structured data with scalability and durability.

  • Cloud Storage: Global object storage for any data volume.

  • Cloud SQL: Managed relational databases for business apps.

  • Cloud Datastore: NoSQL database for flexible schemas.

  • Cloud Filestore: High-performance file storage for applications.

Database Services

Managed databases for real-time, transactional, and distributed workloads.

  • Cloud Bigtable: Scalable NoSQL database for high-throughput use cases.

  • Cloud Spanner: Globally distributed relational database with strong consistency.

  • Cloud Firestore: Real-time NoSQL document database.

  • Cloud Memorystore: In-memory data store for low-latency caching.

Network and Connectivity

GCP networking services for workload isolation, optimized routing, and hybrid connectivity.

  • Virtual Private Cloud (VPC): Private networking segmentation and control.

  • Cloud Interconnect: Dedicated connectivity to Google Cloud.

  • Cloud Load Balancing: Global load balancing and failover.

  • Cloud DNS: Scalable and managed DNS hosting.

Security and Identity

End-to-end security solutions for GCP, including identity management and threat protection.

  • Identity and Access Management (IAM): Fine-grained permission and identity policies.

  • Cloud Key Management Service (KMS): Encryption key lifecycle and access control.

  • Security Command Center: Centralized security posture and threat visibility.

  • Identity-Aware Proxy (IAP): Application-level authentication and access control.

Development and Deployment

Automated build pipelines, serverless frameworks, and container solutions for rapid delivery.

  • Cloud Build: Automated builds, tests and deployments.

  • Cloud Functions: Event-driven serverless compute.

  • Cloud Run: Fully managed container execution.

  • App Engine: Opinionated runtime for web and mobile applications.

Data Analytics and Big Data

GCP data services for processing, transforming, and analyzing enterprise data at scale.

  • BigQuery: Serverless data warehouse for analytics.

  • Dataproc: Managed Hadoop and Spark clusters.

  • Dataflow: Unified batch and stream data processing.

  • Dataprep: Visual data preparation and cleansing.

  • Pub/Sub: Real-time event ingestion at scale.

Application Services

GCP application services and APIs for modern digital experiences.

  • Cloud Endpoints: API gateway and lifecycle management.

  • Firebase: Platform for mobile and web applications with real-time sync.

FAQ

FAQ

FAQ

What makes GCP cloud engineering unique?

GCP excels in data-first architecture, autoscaling compute, ML-ready services and cost-efficient workload design. Cloud engineering ensures these capabilities are used securely, efficiently and at scale.

How does EZOps Cloud improve GCP performance and modernization?

We engineer GCP environments using IaC, VPC best practices, autoscaling services, managed databases and container-based workloads to improve speed, reliability and long-term scalability.

Can you help reduce GCP costs while maintaining performance?

Yes. We optimize compute, storage, networking and data pipelines using committed use discounts, rightsizing, workload tuning and architectural redesign to reduce spend without sacrificing performance.

How do you ensure security and compliance on GCP?

We implement identity boundaries, VPC segmentation, encryption, logging, IAM governance and continuous monitoring to ensure workloads remain secure-by-design and audit-ready across environments.

Do you support data engineering and analytics on GCP?

Yes. We design and optimize data pipelines, storage layers and analytics platforms using BigQuery, Dataflow, Pub/Sub and other cloud-native services tailored for large-scale datasets and ML workflows.

What makes GCP cloud engineering unique?

GCP excels in data-first architecture, autoscaling compute, ML-ready services and cost-efficient workload design. Cloud engineering ensures these capabilities are used securely, efficiently and at scale.

How does EZOps Cloud improve GCP performance and modernization?

We engineer GCP environments using IaC, VPC best practices, autoscaling services, managed databases and container-based workloads to improve speed, reliability and long-term scalability.

Can you help reduce GCP costs while maintaining performance?

Yes. We optimize compute, storage, networking and data pipelines using committed use discounts, rightsizing, workload tuning and architectural redesign to reduce spend without sacrificing performance.

How do you ensure security and compliance on GCP?

We implement identity boundaries, VPC segmentation, encryption, logging, IAM governance and continuous monitoring to ensure workloads remain secure-by-design and audit-ready across environments.

Do you support data engineering and analytics on GCP?

Yes. We design and optimize data pipelines, storage layers and analytics platforms using BigQuery, Dataflow, Pub/Sub and other cloud-native services tailored for large-scale datasets and ML workflows.

What makes GCP cloud engineering unique?

GCP excels in data-first architecture, autoscaling compute, ML-ready services and cost-efficient workload design. Cloud engineering ensures these capabilities are used securely, efficiently and at scale.

How does EZOps Cloud improve GCP performance and modernization?

We engineer GCP environments using IaC, VPC best practices, autoscaling services, managed databases and container-based workloads to improve speed, reliability and long-term scalability.

Can you help reduce GCP costs while maintaining performance?

Yes. We optimize compute, storage, networking and data pipelines using committed use discounts, rightsizing, workload tuning and architectural redesign to reduce spend without sacrificing performance.

How do you ensure security and compliance on GCP?

We implement identity boundaries, VPC segmentation, encryption, logging, IAM governance and continuous monitoring to ensure workloads remain secure-by-design and audit-ready across environments.

Do you support data engineering and analytics on GCP?

Yes. We design and optimize data pipelines, storage layers and analytics platforms using BigQuery, Dataflow, Pub/Sub and other cloud-native services tailored for large-scale datasets and ML workflows.

Reduce GCP complexity and accelerate cloud automation

Reduce GCP complexity and accelerate cloud automation

Reduce GCP complexity and accelerate cloud automation

GCP architecture diagram displaying autoscaling services, data workflows, managed cloud components and platform engineering best practices
GCP architecture diagram displaying autoscaling services, data workflows, managed cloud components and platform engineering best practices
GCP architecture diagram displaying autoscaling services, data workflows, managed cloud components and platform engineering best practices