Adaptive compute control / private preview
DynamicWay reads demand, topology and policy together—then continuously reshapes cluster capacity around the jobs that matter.
01Model training
02Data pipelines
03Batch inference
04Research compute
01 / Orchestration
Replace disconnected autoscalers and queue scripts with one explainable layer that balances delivery time, cost and infrastructure limits.
Forecast queue pressure per workload class and move capacity before deadlines compete for the same accelerators.
Score region, storage, fabric and accelerator shape together. Keep expensive transfers visible in every recommendation.
Encode budgets, residency, maintenance windows and team guarantees as boundaries the planner cannot cross.
LIVE CAPACITY PLAN / 14:32 UTC
Every proposed resize includes the signal, constraint, expected queue effect and rollback boundary. Operators approve the model—not a black box.
Read the operating method02 / Signals
DynamicWay joins demand and infrastructure telemetry into a compact decision record teams can inspect, challenge and improve.
p95 wait crossed the training SLO forecast.
+0.82Reserved GPU headroom available in eu-central.
+0.64Feature snapshot reached regional object storage.
+0.51Team quota leaves eight accelerator slots.
+0.37Observed across preview environments after four weeks
03 / Method
Adoption follows a controlled path. Each phase produces evidence before DynamicWay receives more authority.
OBSERVE / 7 DAYS
Connect read-only queue, scheduler and cost signals. Establish the baseline and expose capacity friction.
SIMULATE / 14 DAYS
Compare proposed moves with actual scheduler outcomes. Tune goals, limits and team-specific service levels.
ADAPT / CONTINUOUS
Enable approved actions one workload class at a time, with complete decision histories and instant pause controls.
OPERATING PRINCIPLES
Every action carries its evidence and expected effect.
Delivery, cost and policy remain explicit constraints.
Authority grows only when operators approve the evidence.
04 / Access
Private preview is designed for ML, data and platform teams operating mixed compute at meaningful scale. We start with one measurable scheduling problem.
A STRONG PREVIEW FIT
Multiple workload classes compete for shared CPU or accelerators.
Queue latency and utilization matter more than raw node count.
Platform owners need policy control and an auditable decision trail.
No rip-and-replace. DynamicWay works above your current scheduler and infrastructure providers.
05 / Questions
No. It coordinates capacity and policy around schedulers such as Kubernetes, Slurm or managed batch systems. Your scheduler remains the execution authority.
Yes. Observe and simulation modes are read-only. Teams can measure recommendation quality for as long as needed before approving any action.
The preview focuses on mixed Kubernetes and batch estates across private and public compute. We scope connectors during the first working session.
This preview form only simulates the request workflow. Submitted details are validated for the response and are not persisted by this site.
THE NEXT DECISION CYCLE
Start with one cluster, one pressure map and a result your team can verify.