Tell the platform what matters using simple controls. Every placement and operating decision follows from that, with no infrastructure for you to wire.
Kinesis runs your workload on the cheapest compute on the grid that meets its needs, and moves it when something cheaper appears.
Kinesis favors stable, proven supply and recovers your workload onto healthy compute when a node drops.
Kinesis places your workload close to where it's served and keeps it there as traffic shifts.
Kinesis spreads your workload across providers on purpose, so no single cloud is a dependency.
Bring your code from anywhere - your editor, your model, your repo. We take it from there.
Kinesis places your workload on the right CPUs or GPUs across a network of vetted providers, bills you for the compute you actually use, and abstracts away the VPCs, IAM hierarchies, and plumbing that usually stand between you and production. Commit your code and get a live URL.
Run a standard container across clouds, on-premises, and partner capacity. Nothing to rebuild, no provider to get stuck on.
Monitoring, scaling, recovery, certificates, and secrets are built in, so there’s no ops layer left to assemble.
You’re billed for what you actually consume, so idle capacity never reaches the invoice.
LESS OPS SURFACE
No VPC sprawl, no IAM trees, no security-group geometry. The platform handles networking, scaling, health checks, and rollbacks by default.
Fewer actions than a hyperscaler
TRUE-UTIL™ PRICING
Pay for cycles consumed, capped at Reserved
Bursty workloads save the most. Steady workloads pay the same as reserved would. Your bill tracks actual usage, not wall-clock time.
usage → billed
HARDWARE THAT FITS
CPU, GPU, big-iron, on-demand
A100, H100, H200 in 1–8× configs. Multi-card for training, single for inference, Flex for batch.
PORTABLE BY CONSTRUCTION
Standard containers
Normal Dockerfile, normal image. If Kinesis stops being the right answer, your app moves.
OBSERVABILITY BUILT IN
Logs, metrics, cost — one pane
Real-time logs, per-app utilization, per-workload spend. No glue code, no dashboards to set up.
FOR THE ARCHITECTS
How placement actually works
Kinesis continuously makes placement, scaling, pricing, and failure-handling decisions across a heterogeneous compute graph. Worth understanding if you care about the substrate.
Under the hood →However you build your app — in your editor, from your repo, with your own model, or a prompt — Kinesis runs it. Tell the platform what to optimize for and it handles the infrastructure underneath. No framework to adopt, no YAML to memorize, and a standard container you can always take elsewhere.
1 Bring your code
Push from your repo, your editor, or your CI — or generate it however you like. Standard containers, nothing new to adopt.
2 Set your intent
Tell Kinesis what matters: cost, reliability, latency, or multi-cloud. Plain language or a couple of controls.
3 Kinesis runs it
Placement, scaling, recovery, and monitoring are handled. You get a live URL.
Six paths in. Same runtime, same orchestration, same True-Util™ pricing on the other side.
Connect a repo. Push to ship.
Point Kinesis at your GitHub project. Every push builds, deploys, and rolls forward automatically, with the rest of the CI/CD loop handled.
Best for: teams · production workflows · continuous delivery
Bring an image from your registry.
Private or public — point us at the registry, pick a pricing model, run.
Best for: existing apps · proprietary environments · full control
Upload a Dockerfile or ZIP. We build.
Hand us the source; we build the image and run it. The clean container-native path.
Best for: reproducible builds · portability · open-source projects
Push an image file directly.
Already built locally? Upload the image and go live without setting up a registry.
Best for: quick proofs · offline builds · restricted networks
Start from a template.
Curated stacks — LLMs, vector DBs, web frameworks, batch runners. Configure and ship.
Best for: standard apps · low ops overhead · “show me the menu”
Or just describe it.
Describe the app you want and start from a standard container you can edit and own, your model or ours. Deploy when it is ready.
Best for: prototypes · MVPs · “I just want this idea to exist”
True-Util™ works the same way regardless of how much computing power you need. Pick the buying mode that matches your workload — the metering, caps, and telemetry are identical.
Serverless compute on the Kinesis grid. You pay for the compute, memory, storage, and bandwidth your workloads actually use, and never more than you would pay for the equivalent Dedicated machine. Spiky, variable, or hard-to-forecast workloads save the most.
Single-tenant compute that is yours for as long as you run it. Full control over the box, predictable billing, and the same Kinesis orchestration and telemetry as Serverless. For workloads where steady utilization is a given.
The low end is what you pay when the machine is idle. The high end is the Dedicated cap — competitive and the most you would pay on a traditional cloud.
28 vCPUs, 96 GB RAM per card · 1×, 2×, 4×, 8× configs
TRUE-UTIL™ SERVERLESS OR DEDICATED
24 vCPUs, 96 GB RAM
TRUE-UTIL™ SERVERLESS OR DEDICATED
4 vCPUs, 8 GB RAM · Spot-class for fault-tolerant work
TRUE-UTIL™ SERVERLESS
$100 in free credit. No credit card required. Deploy your first container in under five minutes — bring a GitHub repo, a Dockerfile, or just describe what you want
