Self-hosted AI observability for LLM latency, tokens, cost, errors, and quality.
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AI Observability Platform is a self-hosted observability solution built for modern AI and LLM-powered applications. It helps developers, researchers, and organizations monitor model latency, token usage, estimated cost, errors, and quality signals in one unified platform. This containerized platform enables teams to run observability locally, integrate monitoring into production workflows, and build reliable, transparent, and cost-aware AI systems without vendor lock-in.
AI Observability Platform is composed of a few core services that work together:
Your AI Application
|
| @observe / score()
v
AI Observability SDK
|
| batched telemetry events
v
Collector API (FastAPI)
/ \
/ \
v v
PostgreSQL Redis
(traces, (real-time
scores, counters,
history) fast metrics)
\ /
\ /
v v
Grafana
(dashboards & analytics)
Pull the image: docker pull jahnavik186/ai-observability-platform
https://github.com/jahnavik186/AI-Observability-Platform
Jahnavi Kachhia
Global Product Owner, AI & ML | Open Source Contributor
Content type
Image
Digest
sha256:064c11255…
Size
65.3 MB
Last updated
6 months ago
docker pull jahnavik186/ai-observability-platform