Introduction to Dashboard

Monitor platform health, usage, and model quality from a single overview

Overview

The Dashboard module gives teams a single operational view of Bud AI Foundry. It combines request activity, model inventory, deployment readiness, cluster posture, and model quality signals so you can detect issues early and make faster routing or scaling decisions.

Key Features

Operational Summary Cards Track total requests, total models, running endpoints, inactive clusters, and project member footprint at a glance.

Built-in Time Windows Each major chart supports Last 24 Hrs, Last 7 Days, and Last 30 Days so you can compare short-term anomalies vs. longer trends.

Top-Model Intelligence See top models by usage, benchmark accuracy, and input/output token mix to balance cost, quality, and performance.

Project-Level Visibility API calls, latency, and throughput views are grouped by project to help you identify hotspots quickly.

What You Can Monitor

Area	What you see	Why it matters
Requests	7-day request total, trend sparkline, delta	Detect sudden usage spikes or drops
Models	Total model count with cloud/local split	Track inventory growth and hosting mix
Readiness	Endpoint, cluster, and project status cards	Spot infra risk before incidents
Performance	API calls, latency, throughput charts	Prioritize reliability and capacity work
Quality & Cost	Accuracy leaderboard + token metrics	Balance model quality and token spend

How It Fits in Daily Operations

1. Start in Dashboard to identify where trends changed.
2. Drill down to Models, Clusters, Projects, or Observability.
3. Take action (scale, reroute, investigate, or evaluate).
4. Return to Dashboard to confirm outcomes.

Getting Started

Quick Start

Learn core navigation and chart filters

Dashboard Concepts

Understand cards, deltas, and ranking logic

First Monitoring Workflow

Build a repeatable operations review