DGDR Templates
Ready-to-apply DynamoGraphDeploymentRequest manifests for profiling and generating DynamoGraphDeployments.
A DynamoGraphDeploymentRequest (DGDR) describes a model, workload, hardware, and optional latency
targets. Dynamo profiles that intent and generates the DynamoGraphDeployment (DGD) that serves
traffic. Use these templates when you want Dynamo to choose a deployment configuration instead of
writing the complete DGD yourself.
Each manifest is embedded from
examples/deployments/dgdr/.
Open an example, use the copy button, and adjust its model, backend, hardware, and namespace before
applying it.
Prerequisites
- Install the Dynamo Kubernetes platform and operator.
- Create
hf-token-secretin the target namespace when the model requires authentication. - For namespace-restricted operator installations, set
hardware.gpuSku,hardware.vramMb, andhardware.numGpusPerNodeexplicitly.
Release installations select the matching profiler image when spec.image is omitted. For a local
operator build without a known release version, set spec.image to a compatible dynamo-planner
image.
Apply a template with:
Generate a DGD
rapid.yaml · Fast generation with AIConfigurator estimates
Uses simulated performance estimates to generate a DGD without benchmarking candidate engines on real GPUs.
thorough.yaml · Measure candidate configurations on GPUs
Deploys and benchmarks candidate configurations before selecting and generating the DGD.
planner.yaml · Generate a deployment with SLA-driven autoscaling
Adds a Planner configuration so the generated disaggregated deployment can adjust prefill and decode replicas at runtime.
moe-sglang.yaml · Profile a multinode MoE deployment
Uses SGLang and a 32-GPU budget for a large Mixture-of-Experts model. Adapt its hardware, scheduling, model-cache, and SLA settings before applying it.
Review and Customize the Generated DGD
review-before-deploy.yaml · Inspect the generated DGD first
Sets autoApply: false so the request stops after generation instead of creating the DGD.
generated-dgd-override.yaml · Add KV-aware routing
Merges an environment-variable override into the generated frontend component. Overrides can modify generated components but cannot add a new topology component.
Test and Inspect Profiling
mocker.yaml · Generate a simulated deployment
Replaces model-serving workers with mock workers for testing routing, profiling, and Planner behavior without serving the model on GPUs.
profiling-artifacts.yaml · Persist detailed profiler output
Replaces the profiling output volume with the existing dynamo-pvc claim so plots, logs,
configurations, and raw profiling data remain available after the Job completes.
Inspect the Result
Watch the request until it reaches Deployed or Ready:
For a request with autoApply: false, extract the generated DGD:
See Auto Deploy with DGDR for the task-oriented workflow and the DGDR Reference for field definitions, lifecycle phases, and validation behavior.