435f49738d
Technology forecast and strategic review restructure: - Remove 13 components (backstage, mongodb, activemq, vitess, airflow, camel, dapr, superset, searxng, langserve, trino, lago, rabbitmq) - Add 10 components (sigstore, syft-grype, nemo-guardrails, langfuse, reloader, matrix, ferretdb, litmus, livekit, coraza) - Rename product: Synapse → Axon (SaaS LLM Gateway) - Merge products: Titan + Fuse → Fabric (Data & Integration) - New product: Relay (Communication) - Replace Backstage with Catalyst IDP - Replace MongoDB with FerretDB (MongoDB wire protocol on CNPG) - Add supply chain security (Sigstore/Cosign, Syft+Grype) - Add AI safety and observability (NeMo Guardrails, LangFuse) - Add technology forecast 2027-2030 document - Full verification pass: zero stale references across all docs Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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| README.md | ||
LangFuse
LLM observability and analytics platform.
Category: AI Observability | Type: A La Carte
Overview
LangFuse provides tracing, evaluation, and analytics for LLM applications. It captures every LLM call with cost, latency, token usage, and evaluation scores. Complements Grafana (which handles infrastructure metrics) with AI-specific observability.
Key Features
- LLM call tracing (input, output, cost, latency, tokens)
- Prompt management and versioning
- Evaluation scoring and datasets
- User analytics and session tracking
- Cost attribution per model/user/feature
Integration
| Component | Integration |
|---|---|
| LLM Gateway | Automatic trace capture |
| Grafana | Infrastructure metrics complement |
| CNPG | PostgreSQL backend for traces |
| NeMo Guardrails | Traces guardrail activations |
Used By
- OpenOva Cortex - LLM observability for enterprise AI
Deployment
apiVersion: kustomize.toolkit.fluxcd.io/v1
kind: Kustomization
metadata:
name: langfuse
namespace: flux-system
spec:
interval: 10m
path: ./platform/langfuse
prune: true
Part of OpenOva