Managed K8s with GPU Virtual Machine
Overview
FPT Cloud provides Kubernetes using NVIDIA GPUs with the following key features:
Flexible GPU configuration with multiple GPU types, optional GPU memory, applied per Worker Group.
Automated management and provisioning of GPU resources in Kubernetes with NVIDIA Operator.
Visualization and monitoring of GPUs using NVIDIA DCGM.
Automatically scale containers/nodes with Autoscaler when application demand for GPU resources increases/decreases.
Support GPU sharing with the Multi-Instance mechanism, helping to optimize GPU resource and cost usage.
FPT Cloud uses NVIDIA GPU Operator to provide tools for automatically managing all the software components needed to use GPUs on Kubernetes. GPU Operator allows users to use GPU resources just like they use CPUs in a Kubernetes cluster.
The Operator's components include:
NVIDIA Drivers (CUDA, MIG, etc.)
NVIDIA Device Plugin
NVIDIA Container Toolkit
NVIDIA GPU Feature Discovery
NVIDIA Data Center GPU Manager (Monitoring)
In the Hanoi and Saigon regions, FPT Cloud currently supports Kubernetes using NVIDIA A30 GPUs with the following MIG profiles:
Trên region Hanoi và Saigon, FPT Cloud hiện tại đang hỗ trợ Kubernetes sử dụng GPU Nvidia A30 với các MIG profile sau:
No.
GPU A30 Profile
Strategy
Number instance
Instance resource
1
all-1g.6gb
single
4
1g.6gb
2
all-2g.12gb
single
2
2g.12gb
3
all-balanced
mixed
2
1g.6gb
4
1
2g.12gb
5
none (no label)
none
0
0 (Entire)
In the Hanoi 2 and Japan regions, FPT Cloud currently supports Kubernetes using Nvidia H100 GPUs and Nvidia H200 GPUs
No.
GPU H100 SXM5
Strategy
Number instance
Instance resource
1
all-1g.10gb
single
7
1g.10gb
2
all-1g.20gb
single
4
1g.20gb
3
all-2g.20gb
single
3
2g.20gb
4
all-3g.40gb
single
2
3g.40gb
5
all-4g.40gb
single
1
4g.40gb
6
all-7g.80gb
single
1
7g.80gb
7
all-balanced
mixed
2 1 1
1g.10gb 2g.20gb 3g.40gb
8
none (no label)
none
0
0 (Entire)
No.
GPU H200 SXM5
Strategy
Number instance
Instance resource
1
all-1g.18gb
single
7
1g.18gb
2
all-1g.35gb
single
4
1g.35gb
3
all-2g.25gb
single
3
2g.25gb
4
all-3g.71gb
single
2
3g.71gb
5
all-4g.71gb
single
1
4g.71gb
6
all-7g.141gb
single
1
7g.141gb
7
all-balanced
mixed
2 1 1
1g.18gb 2g.35gb 3g.71gb
8
none (no label)
none
0
0 (Entire)
Example:
If you select the single strategy configuration: all-1g.6gb, the A30 GPU card on the worker is divided into 4 mig-devices with logical GPU resources (equal to ¼ of the physical GPU) and 6GB of GPU RAM.
If you select the single strategy configuration: all-1g.10gb, the H100 GPU card on the worker is divided into 7 mig-devices with logical GPU resources (equal to 1/7 of the physical GPU) and 10GB of GPU RAM.
Note:
MIG configuration applies to all cards attached to the worker. The MIG strategy on worker groups within the same cluster must be the same type (single/mixed/none).
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