Real-time Dashboard

The Strata Real-time Dashboard is a centralized observability platform for monitoring and managing distributed training jobs. Built with React and Tailwind CSS, it provides a high-fidelity view of the coordinator’s state, worker health, and data distribution metrics.

Accessing the Dashboard

By default, the dashboard is served alongside the coordinator.

Start the Coordinator: Run cargo run -p coordinator or use the provided Docker Compose setup.
Open URL: Navigate to http://localhost:3000 in your browser.

Dashboard Modes

Demo Mode: Uses simulated data to showcase UI capabilities without a running cluster.
Live Mode: Connects directly to the Coordinator's REST API to display real-time cluster state.

Key Observability Modules

1. System Metrics

The header and main overview panel display aggregate performance indicators derived from the ApiMetrics interface:

Checkpoint Throughput: Real-time write speeds to the storage backend (Local or S3).
Coordinator RPS: The number of gRPC requests handled by the coordinator per second.
Barrier Latency (p99): The tail latency for worker synchronization, critical for identifying stragglers.
Shard Assignment Time: Latency for the consistent hashing algorithm to distribute data.

2. Worker Fleet Management

This view tracks the lifecycle of every worker registered in the WorkerRegistry.

Status Tracking: Monitors if workers are Active, Idle, Checkpointing, or Recovering.
Resource Utilization: Displays GPU count and hardware metrics reported via heartbeats.
Heartbeat Monitor: Visualizes the last_heartbeat timestamp to help identify network partitions or worker crashes.

3. Data Distribution & Sharding

The dashboard visualizes how the ShardManager partitions datasets across the cluster:

Shard Assignments: Shows which shards (IDs and sample ranges) are assigned to specific workers.
Epoch Progress: Tracks the current epoch and step for each worker.
Data Preview: A specialized component that provides a representative view of the dataset (e.g., ImageNet labels or time-series features) currently being processed.

4. Checkpoint History

Monitor the persistence layer as training progresses:

Persistence Status: Tracks checkpoints as they transition from in_progress to completed.
Storage Metadata: Displays the S3/Local path, file size, and the specific worker that authored the checkpoint.

Task Management

The dashboard allows for remote orchestration of training tasks through the Tasks panel.

Starting a Task

You can submit a CreateTaskRequest via the UI by specifying:

{
  name: "imagenet-resnet50",
  type: "training",
  dataset_id: "ds-001",
  worker_count: 8,
  config: {
    "learning_rate": 0.001,
    "batch_size": 32
  }
}

Log Streaming

The dashboard provides a real-time log aggregator that filters messages by task_id or worker_id. Levels (INFO, WARN, ERROR) are color-coded for rapid debugging of distributed failures.

Configuration & API

The dashboard communicates with the coordinator via a RESTful API (defined in crates/coordinator/src/http_api.rs).

Environment Variables

To point the dashboard to a specific coordinator instance, set the following variable during build or deployment:

| Variable | Description | Default | | :--- | :--- | :--- | | VITE_API_URL | The base URL for the Coordinator REST API | /api |

Primary API Endpoints

If you wish to consume the dashboard data programmatically, the following endpoints are available: