Google Compute EngineGoogle
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About
Options for every business to train deep learning and machine learning models cost-effectively. AI accelerators for every use case, from low-cost inference to high-performance training. Simple to get started with a range of services for development and deployment. Tensor Processing Units (TPUs) are custom-built ASIC to train and execute deep neural networks. Train and run more powerful and accurate models cost-effectively with faster speed and scale. A range of NVIDIA GPUs to help with cost-effective inference or scale-up or scale-out training. Leverage RAPID and Spark with GPUs to execute deep learning. Run GPU workloads on Google Cloud where you have access to industry-leading storage, networking, and data analytics technologies. Access CPU platforms when you start a VM instance on Compute Engine. Compute Engine offers a range of both Intel and AMD processors for your VMs.
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About
Compute Engine is Google's infrastructure as a service (IaaS) platform for organizations to create and run cloud-based virtual machines.
Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications. Integrate Compute with other Google Cloud services such as AI/ML and data analytics. Make reservations to help ensure your applications have the capacity they need as they scale. Save money just for running Compute with sustained-use discounts, and achieve greater savings when you use committed-use discounts.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Artificial intelligence solution for businesses
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Audience
Data-driven global companies interested in a powerful infrastructure as a service (IaaS) platform that prefer cloud-based virtual machines over investing in server equipment of their own
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free ($300 in free credits)
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationGoogle
Founded: 1998
United States
cloud.google.com/ai-infrastructure
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Company InformationGoogle
Founded: 1998
United States
cloud.google.com/compute
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Alternatives |
Alternatives |
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Categories |
CategoriesGoogle Compute Engine offers robust AI infrastructure tailored for demanding machine learning and artificial intelligence workloads. Users can leverage a combination of virtual machines, GPUs, and TPUs to scale their AI models efficiently, ensuring faster model training and inference. The platform supports various frameworks and tools, allowing developers to optimize their AI processes at a global scale. New customers also receive $300 in free credits to explore and experiment with the power of Google Compute Engine's AI infrastructure, helping them accelerate their AI initiatives without upfront costs. Google Compute Engine's auto scaling feature automatically adjusts the number of virtual machine instances in response to fluctuations in traffic or workload demands. This ensures that applications maintain optimal performance without manual intervention and helps to reduce unnecessary costs by scaling down when demand is low. Users can configure scaling policies based on specific criteria, such as CPU utilization or request rate, to further customize how resources are allocated. New customers receive $300 in free credits, enabling them to test and fine-tune auto scaling for their unique workloads. Google Compute Engine enables users to access high-performance cloud GPUs that can be attached to virtual machines for resource-intensive workloads. Cloud GPUs are ideal for tasks such as machine learning, video rendering, 3D modeling, and scientific simulations, providing the power needed for demanding computations. Google offers a variety of GPU options, including NVIDIA Tesla K80s, P4s, T4s, and V100s, to meet specific performance needs. New customers get $300 in free credits to explore Cloud GPU resources and utilize them in a range of GPU-accelerated applications, helping them optimize performance and reduce time to results. Google Compute Engine offers comprehensive cloud management tools that provide users with control and visibility over their cloud infrastructure. These tools allow administrators to monitor the health of virtual machines, configure resources, automate deployment processes, and track billing and usage metrics. By utilizing Google Cloud's built-in tools, organizations can maintain operational efficiency while keeping costs under control. New customers can take advantage of $300 in free credits to explore and implement cloud management features, optimizing the performance and cost-effectiveness of their virtual environments. Google Compute Engine is a robust Infrastructure-as-a-Service (IaaS) offering that provides users with scalable compute resources through virtual machines. With Google Compute Engine, customers can provision resources on demand, paying only for what they use, allowing them to scale their infrastructure as needed for varying workloads. This eliminates the need for physical hardware, offering flexibility, security, and fast provisioning to meet business requirements. New customers receive $300 in free credits, enabling them to explore IaaS capabilities and test the versatility and scalability of Google Compute Engine's cloud infrastructure. Server virtualization on Google Compute Engine allows users to run multiple virtual machines on a single physical server, maximizing resource utilization and minimizing hardware costs. This technology provides flexibility in managing diverse workloads by isolating environments and enabling multi-tenancy, making it easier to deploy, manage, and scale applications. Virtualized servers on Google Compute Engine are fully customizable, allowing users to adjust resources such as CPU, memory, and storage based on specific application requirements. New customers get $300 in free credits to experiment with server virtualization, offering them the ability to scale their infrastructure dynamically while keeping costs in check. Google Compute Engine's virtual machines (VMs) provide users with customizable and scalable compute resources that can be tailored to specific needs. With support for a wide variety of operating systems, users can run Linux, Windows, and other environments, enabling flexibility for a broad range of applications. VMs can be easily configured with different CPU, memory, and storage options to suit the workload, offering both performance and cost-efficiency. New customers can take advantage of $300 in free credits to create and deploy virtual machines on Google Compute Engine, allowing them to experiment with different configurations and optimize their infrastructure. Virtualization on Google Compute Engine enables the creation of isolated virtual environments on a shared physical infrastructure. This technology allows users to maximize resource utilization and simplify workload management by creating multiple virtual machines (VMs) on a single host. Google Compute Engine’s virtualization capabilities offer users the ability to scale resources up or down based on real-time needs, providing both performance and cost-efficiency. With $300 in free credits, new customers can explore how virtualization can benefit their workloads and optimize their cloud infrastructure. |
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Infrastructure-as-a-Service (IaaS) Features
Analytics / Reporting
Configuration Management
Data Migration
Data Security
Load Balancing
Log Access
Network Monitoring
Performance Monitoring
SLA Monitoring
Cloud Management Features
Access Control
Billing & Provisioning
Capacity Analytics
Cost Management
Demand Monitoring
Multi-Cloud Management
Performance Analytics
SLA Management
Supply Monitoring
Workflow Approval
Server Virtualization Features
Audit Management
Health Monitoring
Live Machine Migration
Multi-OS Virtual Machines
Patching / Backup
Performance Log
Performance Optimization
Rapid Provisioning
Security Management
Type 1 / Type 2 Hypervisor
Virtual Machine Features
Backup Management
Graphical User Interface
Remote Control
VDI
Virtual Machine Encryption
Virtual Machine Migration
Virtual Machine Monitoring
Virtual Server
Virtualization Features
Archiving & Retention
Capacity Monitoring
Data Mobility
Desktop Virtualization
Disaster Recovery
Namespace Management
Performance Management
Version Control
Virtual Machine Monitoring
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Integrations
Google Cloud Platform
Vertex AI
Akto
BentoML
Centreon
Cloud Ops Group
CloudPanel
Fidelis Halo
Google Cloud GPUs
Google Cloud Memorystore
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Integrations
Google Cloud Platform
Vertex AI
Akto
BentoML
Centreon
Cloud Ops Group
CloudPanel
Fidelis Halo
Google Cloud GPUs
Google Cloud Memorystore
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