Security & API

Capacity Forecasting API

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Capacity Forecasting API

The Capacity Forecasting API provides predictive analytics for your Scalelite infrastructure, helping you plan for future capacity needs based on historical usage patterns.

Endpoint

GET /api/v1/instances/{instance_id}/forecast

Authentication

Include your API key in the request header:

X-API-Key: your-api-key-here

Example Request

curl -X GET \
  https://scalelitemanager.com/api/v1/instances/1/forecast \
  -H "X-API-Key: sk_live_abc123..."

Response Fields

Field	Type	Description
forecast_date	datetime	When the forecast was generated
forecast_horizon_days	integer	Number of days forecasted (default: 30)
disk_forecast	object	Disk usage predictions including current %, projected %, days until 80% full, and daily growth rate
capacity_forecast	object	Server capacity predictions with current/recommended server counts and peak participant estimate
meetings_forecast	object	Meeting volume predictions with average daily meetings and growth trend
recordings_forecast	object	Recording storage predictions including current count, projected growth, and storage needs
health_score	object	Predicted infrastructure health score (0-100) with trend direction
recommendations	array	Actionable recommendations based on forecast analysis

Disk Forecast Object

Field	Description
current_usage_percent	Current disk usage as percentage (e.g., 45.2)
projected_usage_percent	Projected disk usage at end of forecast horizon
days_until_80_percent	Estimated days until disk reaches 80% (warning threshold)
growth_rate_per_day	Average daily growth rate in percentage points

Capacity Forecast Object

Field	Description
current_servers	Number of BBB servers currently in your pool
recommended_servers	Recommended number of servers based on projected load
peak_predicted_participants	Estimated peak concurrent participants in forecast period

Example Response

{
  "success": true,
  "forecast": {
    "forecast_date": "2025-12-04T10:30:00",
    "forecast_horizon_days": 30,
    "disk_forecast": {
      "current_usage_percent": 45.2,
      "projected_usage_percent": 52.8,
      "days_until_80_percent": 45,
      "growth_rate_per_day": 0.25
    },
    "capacity_forecast": {
      "current_servers": 5,
      "recommended_servers": 6,
      "peak_predicted_participants": 450
    },
    "meetings_forecast": {
      "average_daily_meetings": 85,
      "projected_daily_meetings": 102,
      "growth_trend": "increasing"
    },
    "recordings_forecast": {
      "current_count": 1250,
      "projected_count": 1450,
      "storage_gb_needed": 125
    },
    "health_score": {
      "current": 85,
      "projected": 78,
      "trend": "declining"
    },
    "recommendations": [
      "Consider adding 1 server in the next 30 days",
      "Monitor disk usage - projected to reach 80% in 45 days",
      "Review recording retention policy to manage storage growth"
    ]
  }
}

How Forecasting Works

The forecasting engine uses linear regression analysis on your historical webhook data to identify trends:

Data Collection: Analyzes the last 30-90 days of webhook reports
Trend Analysis: Calculates growth rates for disk, meetings, participants, and recordings
Projection: Extrapolates trends forward by the forecast horizon (default 30 days)
Recommendations: Generates actionable insights based on projected thresholds

Forecasts are automatically refreshed when:

The existing forecast is older than 24 hours
A new webhook report is received with significantly different metrics
You explicitly request a refresh via the API

Error Responses

Status Code	Description
401	Invalid or missing API key
403	API key does not have access to this instance
404	Instance not found
500	Insufficient historical data for forecasting (need at least 7 days)

Use Cases

Capacity Planning: Predict when you need to add more BBB servers before performance degrades
Storage Management: Plan disk upgrades or implement retention policies before running out of space
Budget Planning: Forecast infrastructure costs based on projected growth rates
SLA Compliance: Ensure your infrastructure can meet expected demand peaks
Proactive Alerting: Set up alerts based on forecast thresholds

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