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Insights Models

Data models for Prisma Access Insights API responses.

Overview​

The Insights models provide structured data representations for the Prisma Access Insights API responses. These models ensure type safety, data validation, and consistent interfaces when working with alerts, metrics, and other telemetry data from your Prisma Access deployment.

Available Models​

Common Patterns​

Field Mapping​

Many Insights models use field aliases to provide more intuitive property names:

# API returns "alert_id", model exposes it as "id"
id: str = Field(None, alias="alert_id")

# API returns "message", model exposes it as "name"
name: Optional[str] = Field(None, alias="message")

Flexible Response Handling​

Insights models are designed to handle varying response formats:

# Models use ConfigDict to allow additional fields
model_config = ConfigDict(extra="allow")

# This allows the model to accept and preserve additional fields
# that might be returned by the API in future versions

JSON Field Parsing​

Some fields may contain JSON strings that need parsing:

@field_validator("metadata", mode="before")
def parse_json_string(cls, v):
    """Parse JSON string fields if needed."""
    if isinstance(v, str):
        import json
        try:
            return json.loads(v)
        except json.JSONDecodeError:
            return v
    return v

Model Categories​

Response Models​

These models represent data returned from the API:

  • Read-only fields like id, created_at, etc.
  • All fields from the resource
  • Timestamp and metadata fields

Statistic Models​

These models represent aggregated data:

  • Count fields
  • Grouping fields (severity, category, state)
  • Time-based aggregations

Enum Classes​

These provide constants for valid field values:

  • Severity levels (Critical, High, Medium, Low, etc.)
  • Status values (Raised, Cleared, etc.)
  • Other categorical values