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Monitor LiteLLM Proxy Budgets and Automate Provider Fallback Alerts via Slack

Orchestrate automated multi-LLM proxy token expenditure tracking, health failover gates, and Slack incident alerting in Kestra.

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AIBusinessCloud

Monitor LiteLLM Proxy Budgets & Automate Provider Fallback Alerts via Slack

Enterprise generative AI platforms increasingly deploy unified LLM proxy gateways (such as LiteLLM Proxy) to load balance inference calls across multiple foundation models (OpenAI, Anthropic, Mistral, Vertex AI). As traffic scales, engineering and FinOps teams face two critical risks: unexpected token spending surges and upstream provider outages causing silent downstream application failures.

This blueprint automates continuous health and budget surveillance for multi-model LLM proxy deployments. It evaluates accumulated token spending against organizational cost caps, tests primary provider route responsiveness, verifies automated failover availability, and dispatches rich status digests to your Slack operations channels.

How it works

  1. check_provider_health_and_spend (io.kestra.plugin.scripts.python.Script): Connects to the LiteLLM proxy management API to gather accumulated daily token metrics, calculates budget utilization percentages, checks provider route availability, and emits structured outputs via Kestra.outputs.
  2. evaluate_governance_gate (io.kestra.plugin.core.flow.If): Tests whether current daily spend exceeds the budget threshold or whether the primary provider is degraded. If anomalies exist, dispatches notify_governance_alert; otherwise, emits notify_governance_nominal.
  3. archive_spend_audit_log (io.kestra.plugin.scripts.shell.Commands): Persists operational metric snapshots to audit trails.
  4. alert_on_gateway_failure (errors block): Triggers immediately if network partitions, bad credentials, or runner crashes prevent communication with the proxy, notifying engineers with the execution ID.

What you get

  • Automated hourly spend and availability checks (0 * * * *).
  • FinOps cost protection preventing unanticipated multi-thousand-dollar LLM billing spikes.
  • Automated detection of provider failover from primary (openai/gpt-4o) to secondary models (anthropic/claude-3-5-sonnet).
  • Direct Slack visibility for engineering, product, and finance stakeholders.

Who it's for

  • AI Platform Engineers maintaining enterprise LLM proxy infrastructure and model routing.
  • FinOps and Cloud Cost Managers seeking granular controls over generative AI expenditures.
  • SRE Teams responsible for LLM availability and uptime SLAs.

Why orchestrate this with Kestra

Coordinating multi-provider AI infrastructure requires flexible scheduling, containerized runtime environments, secure API key isolation, and reliable alerting. Kestra coordinates LLM proxy health checks without requiring custom microservice daemons, providing native secrets storage and execution tracing for compliance.

Prerequisites

  • Running instance of LiteLLM Proxy (self-hosted Docker, Kubernetes, or LiteLLM Cloud).
  • Slack Incoming Webhook URL configured for incident dispatch.

Secrets

  • LITELLM_MASTER_KEY: Master API key for querying the LiteLLM proxy management API.
  • SLACK_WEBHOOK_URL: Slack Incoming Webhook endpoint for alerting.

Quick start

  1. Configure LITELLM_MASTER_KEY and SLACK_WEBHOOK_URL in your Kestra namespace secrets.
  2. Import this blueprint into your Kestra instance.
  3. Customize the primary_provider, fallback_provider, and daily_budget_usd inputs.
  4. Click Execute to trigger an on-demand verification of your gateway metrics.
  5. Keep the hourly_spend_check trigger active for continuous automated budget oversight.

How to extend

  • Automate model disabling via LiteLLM API when spending crosses 100% of the daily ceiling.
  • Route metrics into Google BigQuery, Snowflake, or Datadog for organization-wide AI billing dashboards.
  • Integrate PagerDuty for critical severity escalations when all upstream model providers fail.

Links

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