How to govern Costs in LangDock
A step-by-step guide to governing Costs in LangDock with Rencore: detect, review by owner and severity, and remediate with an audit trail.
Governing Costs in LangDock means finding where it goes wrong, reviewing the findings by owner and severity, and remediating with an audit trail. Rencore covers this concern for LangDock with the pre-built controls below, so it becomes a repeatable check rather than a one-off cleanup. The steps that follow apply the same detect, review, remediate loop to Costs.
Steps
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Inventory LangDock
Connect LangDock and let Rencore build a continuous inventory of its resources, owners, and configuration, so governance starts from what exists rather than a stale export.
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Detect with policies
Turn on the pre-built policies that cover Costs in LangDock to surface oversharing, sprawl, and misconfiguration on the first scan, before writing a single custom rule.
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Review by owner and severity
Use the LangDock reports to review findings by owner, category, and severity, and to share them with stakeholders who do not have a seat in the platform.
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Remediate and automate
Apply automations to fix findings at scale, route sensitive changes through approvals, and keep every action reversible and logged for the audit trail.
LangDock controls for Costs
Grounded in the Rencore catalog. See the full LangDock catalog on the LangDock connector page.
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LangDock Model has high request count
Detects models with more than 1000 requests in the reporting period.
Severity: Medium -
LangDock User has high agent usage
Detects user-agent combinations where the user sent more than 100 messages to a single agent.
Severity: Medium -
LangDock User has high model consumption
Detects user-model combinations where the user sent more than 500 messages using a single model.
Severity: Medium -
LangDock model usage distribution
Shows the distribution of requests across AI models
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Model usage by user
Shows the distribution of messages across AI models per user
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Token usage by model
Shows total prompt token consumption per model
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High Usage LangDock Models
Shows models with more than 1000 requests in the period
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High Agent Usage
Shows user-agent combinations with more than 50 messages in the period
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High Model Usage
Shows user-model combinations with more than 100 messages in the period
