Tenants

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Why Tenant Tracking Matters

• Usage Attribution: Know exactly which customer is driving costs, token consumption, and API calls
• Customer Support: When a customer reports an issue, instantly access their specific traces without sifting through logs
• SLA Monitoring: Track performance metrics per tenant to ensure service level agreements are met
• Cost Allocation: Generate accurate billing reports based on actual LLM usage per customer
• Anomaly Detection: Identify unusual patterns in specific tenant activity before they become problems

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Setting Up Tenant Tracking

from netra import Netra

# Set tenant context - all subsequent traces will be associated with this tenant
Netra.set_tenant_id("acme-corp")

# Your LLM calls are now attributed to "acme-corp"
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello"}]
)

import { Netra } from "netra-sdk";

// Set tenant context - all subsequent traces will be associated with this tenant
Netra.setTenantId("acme-corp");

// Your LLM calls are now attributed to "acme-corp"
const response = await client.chat.completions.create({
    model: "gpt-4",
    messages: [{ role: "user", content: "Hello" }]
});

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View Tenants List

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Available Controls

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Tenant List Columns

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Use Cases

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Customer Support

1. Search for their tenant ID in the Tenants view
2. Click View Traces to see all their recent activity
3. Identify the problematic trace and investigate the root cause

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Usage-Based Billing

1. Filtering the Tenants view by your billing period
2. Exporting cost data per tenant
3. Attributing LLM costs directly to each customer

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Performance Benchmarking

1. Sort tenants by trace count or cost
2. Identify outliers in latency or error rates
3. Proactively reach out to customers experiencing issues

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Related

• Users - Track individual user activity within tenants
• Sessions - Group related interactions into sessions
• Traces Overview - Deep dive into individual trace analysis