SUMMARY.md

Table of contents

• Welcome to Aqueduct
• The Aqueduct Philosophy
• Quickstart Guide
• Installation and Configuration
  • Installing Aqueduct
    • Running on AWS EC2
    • Running on Google Compute Engine
    • Running on Kubernetes with Helm
  • Configuring Aqueduct
  • Configuring your Python environment
  • Updating Aqueduct
• Example Workflows
  • Quickstart Tutorial
  • Using Parameters
  • Churn Ensemble
  • MPG Regressor
  • Train and Inference
  • Diabetes Classifier
  • Sentiment Analysis
  • House Price Prediction
• Workflows
  • Creating a Workflow
  • Workflow Versions
  • Scheduling Workflwos
  • Editing a Workflow
  • Deleting a Workflow
• Resources
  • Data Systems
    • SQL Systems
      • Snowflake
      • Postgres
      • MySQL
      • MariaDB
      • SQLite
      • AWS Athena
      • AWS Redshift
      • Google BigQuery
    • Non-SQL Systems
      • AWS S3
      • Google Cloud Storage
      • MongoDB
    • Aqueduct Demo Database
  • Compute Systems
    • On-Demand Resources
      • On-Demand AWS EKS Clusters
      • On-Demand GKE Clusters
    • Aqueduct
    • Airflow
    • Conda
    • Databricks
    • Kubernetes
    • AWS Lambda
    • Apache Spark on AWS EMR
  • Container Registries
    • ECR
    • GAR
  • Managing Resources
• Integrations
• Operators
  • Creating a Python Operator
  • requirements.txt
  • File Dependencies
  • Configuring GPUs, CPUs, and Memory
  • LLMs
• Artifacts
• Parameters
  • Creating Parameters
  • Configuring Workflow Inputs
  • Parameterizing Loads
  • Parameterizing Saves
• Notifications
  • Email
  • Slack
• Metrics & Checks
  • Metrics: Measuring your Predictions
  • Checks: Ensuring Correctness
  • Preset Metrics & Checks
• API Reference
  • Aqueduct CLI
  • SDK Reference
    • package aqueduct
      • aqueduct.client
      • aqueduct.decorator
      • aqueduct.error
      • aqueduct.flow
      • aqueduct.schedule
      • aqueduct.llm_op
      • package aqueduct.artifacts
        • aqueduct.artifacts.bool_artifact
        • aqueduct.artifacts.generic_artifact
        • aqueduct.artifacts.numeric_artifact
        • aqueduct.artifacts.table_artifact
      • package aqueduct.models
        • aqueduct.models.integration
        • aqueduct.models.operators
      • package aqueduct.constants
        • aqueduct.constants.enums
        • aqueduct.constants.exports
        • aqueduct.constants.metrics
      • package aqueduct.resources
        • aqueduct.resources.airflow
        • aqueduct.resources.aws_lambda
        • aqueduct.resources.databricks
        • aqueduct.resources.dynamic_k8s
        • aqueduct.resources.ecr
        • aqueduct.resources.gar
        • aqueduct.resources.kubernetes
        • aqueduct.resources.google_sheets
        • aqueduct.resources.mongodb
        • aqueduct.resources.s3
        • aqueduct.resources.salesforce
        • aqueduct.resources.spark
        • aqueduct.resources.sql
  • Aqueduct LLM Reference
    • package aqueduct_llm
      • aqueduct_llm.dolly_v2_3b
      • aqueduct_llm.dolly_v2_7b
      • aqueduct_llm.llama_7b
      • aqueduct_llm.vicuna_7b
• Guides
  • Porting a workflow to Aqueduct
  • Debugging a Failed Workflow
• FAQs
• Ask AI