More work
from the hardware you already have
A server usually sits idle not because there is no other work, but because nobody was willing to let the other work near it. A Grid gives your administrator the controls that make sharing safe, and a control plane that fills the gaps.
Booked is not the same as busy
Every card is allocated. The queue is still full. The gap between the two is where the next hardware purchase is hiding.
Sessions that never let go
A notebook opened at nine still holds half a card at noon. Nothing reclaims it.
Work that fights for the same card
A live endpoint and a training run share a GPU. Both run slower. Nothing separates them.
Jobs with no ceiling
A few large jobs take most of a card each. Nothing caps them, and nothing tells anyone.
This is not a scheduling problem. It is a trust problem: nobody could say who was allowed to sit next to whom.
One pool, kept full
Each team’s servers, each cloud account, each colo cage is its own island. A Grid makes them one pool, and the control plane keeps the pool full.
One pool, not many islands
Headroom in one team’s servers is available to another team’s job.
Work goes where there’s room
Each workload lands on the machine that fits, wherever in the Grid it is.
Idle becomes available
Quiet sessions are warned, then reclaimed. Capacity returns to whoever is waiting.
Failed machines stop taking work
A machine that drops out leaves the pool. The work moves to one that is healthy.
Who gets the card, how much, and when
The same hardware carries more of the organization when someone can set the rules for it. Each control is a decision your administrator makes.
Caps per person or group · memory, GPU count, cores, storage, monthly GPU-hours
Set before launch, not discovered on a bill.
Cards that can be split
Light users share a card without sharing a fate. Heavy users get whole ones.
Fair-share queuing
When the queue is full, the person who has used the least goes first.
Idle warned, then reclaimed
Capacity goes back to whoever is waiting, not to whoever forgot.
Production walled from training
Live endpoints on machines that training never touches.
Your machines. Kinesis capacity. One Grid.
Kinesis combines workload orchestration with access to additional compute capacity. Teams can bring supported machines they already own, add capacity supplied through Kinesis, and manage workloads through one service.
Kinesis is designed to reduce the work of assembling and operating separate infrastructure, scheduling, and usage-management tools. Customers can focus on running applications while Kinesis manages the supported compute environment.
Find out what your servers are doing when nobody is watching
Measure it first
The capacity assessment reads your own telemetry and shows how full your hardware is, when, and for whom. Read-only. Nothing moves until you say so.