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Rails

7 items

ARTICLEDEV.to AI·4/13/2026

Monitoring and Observability for AI-Powered Rails Apps

This article discusses the crucial need for robust monitoring and observability in AI-powered Rails applications. It highlights unique challenges posed by AI workloads, such as high API latency, token cost overruns, non-deterministic failures, and rate limits, suggesting tools like Lograge and Logstash-event.

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ARTICLEDEV.to AI·12d ago

LLM Cost Tracking for Rails

This content introduces `llm_cost_tracker`, a new Rails Engine built to solve the challenge of attributing Large Language Model (LLM) costs within Rails applications. It aims to provide per-user, per-feature, per-tenant cost tracking for services like OpenAI or Anthropic, adhering to principles of no new infrastructure, no prompt storage, and no traffic redirection.

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