GPU Console
GPU Console
The Planck GPU Console is a powerful Infrastructure-as-a-Service (IaaS) interface that offers direct GPU rental and bare-metal server operations. It’s designed for developers, researchers, and enterprises who need instant, scalable access to decentralized GPU resources.
Core Capabilities:
Virtual Machines with NVIDIA GPUs:
Deploy VMs in minutes with root access and full control.
Select from a wide range of configurations including A100s, H100s, and 3090s.
Ideal for solo developers and agile teams training models or running AI workloads.
GPU Clusters with H100s and H200s:
Provision high-performance clusters with high-speed interconnects.
Optimized for distributed training and compute-heavy workloads.
Suited for enterprises and research labs tackling massive compute jobs.
Managed Kubernetes Clusters:
Containerized workloads with simplified orchestration.
Perfect for microservices-based AI applications.
Managed Ray Clusters:
Deploy distributed machine learning with hyperparameter tuning and training acceleration.
Tailored for data science teams requiring scalable ML infrastructure.
Object Storage:
Secure and scalable storage buckets for datasets, models, and outputs.
Integrated into the GPU Console for seamless access.
Advanced Infrastructure Features:
Private Intra-Cluster Networking:
Secure clusters via remote VPN overlays, isolating internal traffic from public internet.
Built on Tier 3 and Tier 4-equivalent data centers for speed, security, and reliability.
Enterprise-Grade Autoscaling:
Includes elastic scaling, load balancing, and automated resource allocation.
Supports managed databases and storage for cloud-native DevOps.
Uptime and Reliability Segmentation:
Two tiers: Retail for smaller, non-critical workloads, and Enterprise for high-uptime SLAs and disaster recovery.
Toward Industry Certification:
In partnership with Rollman Group, Planck is pursuing key infrastructure certifications.
Aims to be among the first decentralized compute networks with full compliance for regulated industries.
The GPU Console allows developers and enterprises to:
Access decentralized compute on demand
Scale compute workloads elastically
Reduce infrastructure costs by up to 90%
Accelerate innovation without traditional cloud complexity
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