SDK Simulator User Guide#

The DPS SDK is a Kubernetes-based development environment for testing power management solutions without physical hardware. It ships with three deployment profiles so you can pick the right starting point for your goals.

Deployment Profiles#

  • Default - Blank DPS environment with no topology or simulators running. Recommended starting point for hands-on dpsctl exercises and API exploration.

  • Hardware Emulation - 144 emulated DGX GB300 nodes across 8 racks with pseudorandom hardware responses. Best for general API development, integration validation, and automated playbooks.

  • Workload-Aware - Same 144-node GB300 topology, but the BMC simulator calls a pluggable workload model over gRPC to return realistic GPU power traces. Best for power-aware analysis and workload optimization studies. See the Workload-Aware Simulation guide.

What’s Included#

Emulated Infrastructure (Hardware Emulation and Workload-Aware)#

  • 144 DGX GB300 Compute Nodes - Organized across 8 racks (18 nodes per rack)

  • Complete Power Distribution Hierarchy - Utility, Switchboard, Floor PDUs, Rack PSUs, Compute Systems

  • BMC Simulator - Provides Redfish API endpoints for all emulated nodes

For detailed information about the simulator’s datacenter topology, see the Simulator Topology Guide.

Policy Bundles (all profiles)#

The DPS server bootstraps the MaxP, MaxQ, and MaxLPS policy bundles regardless of which deployment profile you run, including Default. The SDK also includes sim/policy-bundles/sdk-site-balanced.yaml, a tutorial file that you load as the sdk-site-balanced bundle rather than a fourth server preset. It is distinct from the guide’s downloadable site-balanced example: the files and stored names differ, although their current policy payloads are identical.

The Simulator Playbooks guide covers loading and inspecting bundles as part of the Default-profile walkthrough.

Monitoring and Visualization#

  • Grafana Dashboards - Real-time metrics for datacenter power, resource groups, and system operations

  • Prometheus - Time-series metrics collection and alerting

  • Pyroscope - Continuous profiling for performance analysis

  • Web UI - Interactive interface for managing DPS

Automated Simulation Playbooks#

  • Resource Group Simulation - Automated workload lifecycle testing with configurable parameters

  • Grid Simulation - Domain-level power management and grid integration testing

  • Load Shedding Simulation - Power reduction events and recovery scenarios

  • Combined Simulations - Run multiple scenarios simultaneously for thorough testing

Use Cases#

The simulator is ideal for:

  • Learning DPS - Explore concepts, APIs, and workflows in a safe environment

  • SDK Development - Build and test custom integrations without hardware dependencies

  • Partner Integration - Develop grid or optimization integrations

  • Quick Start - Jump-start your custom datacenter deployment

Quick Start#

System Requirements:

  • Linux (Ubuntu/Debian) or macOS

  • Minimum 8 GB RAM, 20 GB free disk space

  • Internet connection for dependencies

Setup Instructions:

  1. Download and unarchive the DPS SDK files from the NVIDIA NVOnline Portal.

  2. Install SDK dependencies. From the SDK directory, run:

    cd dps-sdk
task setup

    This installs docker, kubectl, k3d, helm, helm-git, uv, and dpsctl.

  3. Deploy the Default profile. This is the recommended starting point - a blank DPS environment with no topology loaded:

    task deploy

  4. Configure your shell for dpsctl. Paste these exports once to avoid repeating connection flags on every command:

    export DPSCTL_HOST=api.dps.sdk
export DPSCTL_PORT=80
export DPSCTL_INSECURE_TLS_SKIP_VERIFY=true

  5. Continue with the Default-profile playbook. The Simulator Playbooks guide walks you through importing the topology, creating resource groups, and setting grid load targets with dpsctl.

Other Deployment Paths#

  • Hardware Emulation (automated playbooks):

    task sdk
task sim

    task sdk creates the k3d cluster and deploys DPS; task sim imports the topology and runs the combined resource-groups plus grid simulation.

  • Workload-Aware (realistic power traces): See the Workload-Aware Simulation guide for the full deployment flow.

Access Services#

After deployment, the SDK exposes these endpoints:

Service

URL

Default Auth

DPS API (gRPC)

api.dps.sdk

dps/dps

DPS Web UI

http://ui.dps.sdk

dps/dps

Grafana

http://grafana.dps.sdk

admin/dps

Prometheus

http://prometheus.dps.sdk

-

Alertmanager

http://alertmanager.dps.sdk

-

Pyroscope

http://pyroscope.dps.sdk

-

Next Steps#