docs: revise README
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README.md
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README.md
@@ -41,8 +41,6 @@ A remotely accessible Kubernetes home lab with OIDC authentication. Build a mode
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### Data & Analytics (Optional)
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### Data & Analytics (Optional)
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- **[JupyterHub](https://jupyter.org/hub)**: Interactive computing with collaborative notebooks
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- **[JupyterHub](https://jupyter.org/hub)**: Interactive computing with collaborative notebooks
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- **[MLflow](https://mlflow.org/)**: Machine learning lifecycle management with experiment tracking and model registry
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- **[KServe](https://kserve.github.io/)**: Model serving platform for deploying ML models on Kubernetes
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- **[Trino](https://trino.io/)**: Distributed SQL query engine for querying multiple data sources
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- **[Trino](https://trino.io/)**: Distributed SQL query engine for querying multiple data sources
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- **[Querybook](https://www.querybook.org/)**: Big data querying UI with notebook interface
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- **[Querybook](https://www.querybook.org/)**: Big data querying UI with notebook interface
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- **[ClickHouse](https://clickhouse.com/)**: High-performance columnar analytics database
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- **[ClickHouse](https://clickhouse.com/)**: High-performance columnar analytics database
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@@ -52,6 +50,15 @@ A remotely accessible Kubernetes home lab with OIDC authentication. Build a mode
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- **[Metabase](https://www.metabase.com/)**: Lightweight BI with simple configuration and clean, modern interface
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- **[Metabase](https://www.metabase.com/)**: Lightweight BI with simple configuration and clean, modern interface
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- **[DataHub](https://datahubproject.io/)**: Data catalog and metadata management
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- **[DataHub](https://datahubproject.io/)**: Data catalog and metadata management
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### Machine Learning (Optional)
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- **[MLflow](https://mlflow.org/)**: Machine learning lifecycle management with experiment tracking and model registry
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- **[KServe](https://kserve.github.io/)**: Model serving platform for deploying ML models on Kubernetes
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### LLM & AI Applications (Optional)
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- **[Langfuse](https://langfuse.com/)**: LLM observability and analytics platform for tracking and debugging AI applications
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### Orchestration (Optional)
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### Orchestration (Optional)
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- **[Dagster](https://dagster.io/)**: Modern data orchestration platform
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- **[Dagster](https://dagster.io/)**: Modern data orchestration platform
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@@ -195,6 +202,17 @@ Model serving platform for deploying ML models on Kubernetes:
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[📖 See KServe Documentation](./kserve/README.md)
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[📖 See KServe Documentation](./kserve/README.md)
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### Langfuse
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LLM observability and analytics platform:
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- **Trace Tracking**: Monitor LLM calls, chains, and agent executions with detailed traces
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- **Prompt Management**: Version and test prompts with playground interface
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- **Analytics**: Track costs, latency, and token usage across all LLM applications
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- **Keycloak Authentication**: OAuth2 integration with automatic user provisioning
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[📖 See Langfuse Documentation](./langfuse/README.md)
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### Apache Superset
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### Apache Superset
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Modern business intelligence platform:
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Modern business intelligence platform:
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@@ -427,6 +445,7 @@ kubectl --context yourpc-oidc get nodes
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# Airflow: https://airflow.yourdomain.com
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# Airflow: https://airflow.yourdomain.com
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# JupyterHub: https://jupyter.yourdomain.com
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# JupyterHub: https://jupyter.yourdomain.com
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# MLflow: https://mlflow.yourdomain.com
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# MLflow: https://mlflow.yourdomain.com
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# Langfuse: https://langfuse.yourdomain.com
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```
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```
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## Customization
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## Customization
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