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ee38046
gitignore claude files
fmercadop Jun 17, 2026
dc92d45
SEO: Step 0 — Config: shorten site title + fix homepage meta
fmercadop Jun 17, 2026
d4cea41
SEO: Step 1 — Custom pages: contact-us.md, sla.md
fmercadop Jun 17, 2026
a6c8fc8
SEO: Fix homepage hero — restore original H1 text
fmercadop Jun 17, 2026
7c0fff2
SEO: Step 2 — Getting Started: Account & Admin
fmercadop Jun 17, 2026
ca11ec0
SEO: Step 2b — Backfill sidebar_label for Step 2 pages
fmercadop Jun 17, 2026
3de120b
SEO: Step 3 — Getting Started: Developer
fmercadop Jun 17, 2026
38f9491
SEO: Step 4 — Best Practices: Datacoves & dbt
fmercadop Jun 17, 2026
9581e06
SEO: Step 5 — Best Practices: Git, Snowflake, VS Code
fmercadop Jun 17, 2026
66c065f
SEO: Step 6 — How-tos Airflow: Core
fmercadop Jun 17, 2026
8352e0b
SEO: Step 7 — How-tos Airflow: DAGs
fmercadop Jun 17, 2026
87745cc
SEO: Step 8 — How-tos Datacoves Admin: Part 1
fmercadop Jun 17, 2026
c931c93
SEO: Step 9 — How-tos Datacoves Admin: Part 2 + Metrics & Logs
fmercadop Jun 17, 2026
f76aee9
SEO: Step 10 — How-tos DataHub + DataOps + dbt
fmercadop Jun 17, 2026
112491f
SEO: Step 11 — How-tos Git + My Airflow + Snowflake + Superset + dbt
fmercadop Jun 17, 2026
6f47667
SEO: Step 12 — How-tos VS Code
fmercadop Jun 17, 2026
d6a76dc
SEO: Step 13 — Reference: Admin Menu
fmercadop Jun 17, 2026
1db6996
SEO: Step 14 — Reference: Airflow
fmercadop Jun 17, 2026
fe470d1
SEO: Step 15 — Reference: Datacoves + Security + VS Code + Tutorials
fmercadop Jun 17, 2026
72d0167
Update sidebar label in Git README
fmercadop Jun 18, 2026
27b1486
Update sidebar label in My Airflow README
fmercadop Jun 18, 2026
7c18621
Revise Airflow README sidebar label
fmercadop Jun 18, 2026
fe41f08
Update sidebar label
fmercadop Jun 18, 2026
c3ca01f
Revise security README
fmercadop Jun 18, 2026
629ff7c
Refine VS Code sidebar
fmercadop Jun 18, 2026
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3 changes: 3 additions & 0 deletions .gitignore
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Expand Up @@ -19,3 +19,6 @@ static/llms.txt
npm-debug.log*
yarn-debug.log*
yarn-error.log*

CLAUDE.md
PLAN.md
4 changes: 3 additions & 1 deletion docs/best-practices/datacoves/README.md
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---
title: Datacoves
title: Datacoves Platform Best Practices
sidebar_label: Datacoves
description: "Recommended practices for organizing and using Datacoves, including project folder structure and configuration guidance for enterprise data engineering teams."
sidebar_position: 1
---
# Best practices on datacoves
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4 changes: 3 additions & 1 deletion docs/best-practices/datacoves/folder-structure.md
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---
title: Folder structure
title: Datacoves Project Folder Structure Guide
sidebar_label: Folder Structure
description: "Learn the recommended repository layout for Datacoves: required folders like automate/dbt and orchestrate/dags, plus optional dbt-coves configuration paths."
sidebar_position: 1
---

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4 changes: 3 additions & 1 deletion docs/best-practices/dbt/README.md
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---
title: dbt
title: "dbt Best Practices: Tools, Packages & Guidelines"
sidebar_label: dbt
description: "An overview of dbt best practices in Datacoves: macro naming standards, open-source packages, coding tools like dbt-coves and SQLFluff, and governance checks."
sidebar_position: 2
---
# Overview
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4 changes: 3 additions & 1 deletion docs/best-practices/dbt/dbt-guidelines.md
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---
title: dbt guidelines
title: dbt Project Guidelines for Enterprise Data Teams
sidebar_label: Guidelines
description: "Coding standards and decision-making guidelines for dbt projects in Datacoves: model structure, source definitions, testing, and documentation best practices."
sidebar_position: 1
---

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4 changes: 3 additions & 1 deletion docs/best-practices/dbt/inlets-bays-coves.md
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---
title: What are Inlets, Bays, and Coves
title: "Inlets, Bays & Coves: Datacoves dbt Layer Model"
sidebar_label: "Inlets, Bays & Coves"
description: "Understand Datacoves' three-tier dbt architecture: Inlets for raw source data, Bays for intermediate transformations, and Coves for analytics-ready output."
sidebar_position: 3
---

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4 changes: 3 additions & 1 deletion docs/best-practices/dbt/object-naming.md
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---
title: Object Naming Standards
title: dbt Object Naming Standards in Datacoves
sidebar_label: Object Naming Standards
description: "Naming conventions for dbt models, sources, tests, and macros in Datacoves to ensure consistency and maintainability across large data engineering teams."
sidebar_position: 2
---

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4 changes: 3 additions & 1 deletion docs/best-practices/git/README.md
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---
title: Git
title: Git Best Practices for Datacoves Data Projects
sidebar_label: Git
description: "Best practices for using Git in Datacoves: branching strategies, commit conventions, and workflow recommendations for data engineering teams."
sidebar_position: 3
---
# Git Overview
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4 changes: 3 additions & 1 deletion docs/best-practices/snowflake/comparing-tables.md
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---
title: Comparing Tables Across Environments
title: Compare Snowflake Tables Across dbt Environments
sidebar_label: Comparing Tables
description: "How to compare row counts, column values, and data distributions across dev, staging, and production Snowflake environments in your dbt workflow."
sidebar_position: 5
---

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4 changes: 3 additions & 1 deletion docs/best-practices/snowflake/security-model.md
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---
title: Security Model
title: Snowflake Security Model for Datacoves Projects
sidebar_label: Security Model
description: "Best practices for Snowflake role-based access control, user management, and security configuration for data engineering teams using Datacoves."
sidebar_position: 2
---

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4 changes: 3 additions & 1 deletion docs/best-practices/snowflake/time-travel.md
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---
title: GDPR and Time-Travel
title: Snowflake Time Travel & GDPR Best Practices
sidebar_label: Time Travel & GDPR
description: "How to use Snowflake Time Travel for data recovery while managing GDPR compliance, including data retention policies and personal data handling guidance."
sidebar_position: 3
---

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4 changes: 3 additions & 1 deletion docs/best-practices/vscode/README.md
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---
title: VS Code
title: VS Code Best Practices for Datacoves Developers
sidebar_label: VS Code
description: "Tips and best practices for using VS Code in the Datacoves Transform tab, including extensions, settings, and productivity recommendations for dbt teams."
sidebar_position: 5
---
# VS Code Best Practices and Tips
4 changes: 3 additions & 1 deletion docs/best-practices/vscode/tips.md
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---
title: VS Code Tips
title: VS Code Tips and Tricks for Datacoves Users
sidebar_label: Tips & Tricks
description: "Productivity tips and keyboard shortcuts for VS Code in Datacoves: navigation, multi-cursor editing, terminal tricks, and dbt workflow optimizations."
sidebar_position: 138
---
# VS Code Tips and tricks
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4 changes: 3 additions & 1 deletion docs/getting-started/Admin/configure-airflow.md
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---
title: Airflow - Configure
title: Airflow Setup Guide for Datacoves Administrators
sidebar_label: Configure Airflow
description: "Step-by-step guide to configure Airflow in Datacoves: set up service connections, repository structure, and notification integrations for scheduling dbt jobs."
sidebar_position: 2
---
# Configuring Airflow
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---
title: Configure Git Repository Using dbt-coves
title: Initialize a Datacoves Repository with dbt-coves
sidebar_label: Configure Git Repository Using dbt-coves
description: "Use dbt-coves setup to scaffold a fully configured Datacoves project with dbt, Airflow, CI/CD pipelines, SQLFluff, and data warehouse adapters in one command."
sidebar_position: 12
---
# Initial Datacoves Repository Setup
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4 changes: 3 additions & 1 deletion docs/getting-started/Admin/configure-repository.md
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---
title: Configure Git Repository
title: Configure Your Git Repository for Airflow DAGs
sidebar_label: Configure Git Repository
description: "Set up the required folder structure in your git repository for Airflow: create orchestrate/dags, the airflow_development branch, and a profiles.yml file."
sidebar_position: 8
---
# Update Repository for Airflow
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4 changes: 3 additions & 1 deletion docs/getting-started/Admin/creating-airflow-dags.md
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---
title: Airflow - Creating Dags
title: Creating Your First Airflow DAGs in Datacoves
sidebar_label: Create Airflow DAGs
description: "Learn to write Airflow DAGs in Datacoves: run dbt with Python DAGs or auto-generate them from YAML definitions using dbt-coves generate airflow-dags."
sidebar_position: 3
---
# Creating Airflow Dags
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4 changes: 3 additions & 1 deletion docs/getting-started/Admin/user-management.md
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---
title: User Management
title: "Datacoves User Management: Invite, Edit & Remove"
sidebar_label: User Management
description: "Invite new users to Datacoves, manage their project and environment permissions, and remove accounts when access is no longer needed."
sidebar_position: 20
---
# User Management
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4 changes: 3 additions & 1 deletion docs/getting-started/create-account.md
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---
title: Account Pre-reqs
title: Account Prerequisites for Setting Up Datacoves
sidebar_label: Create Account
description: "What you need before your Datacoves setup call: data warehouse credentials, git repository access, dbt version, and authentication method for SSO."
sidebar_position: 1
---
# Configure your account with Datacoves
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4 changes: 3 additions & 1 deletion docs/getting-started/developer/snowflake-extension.mdx
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---
title: Snowflake Extension
title: Snowflake VS Code Extension in Datacoves
sidebar_label: Snowflake Extension
description: "Video guide to the Snowflake VS Code extension in Datacoves: sign in, browse database objects, run queries, and use autocomplete directly in the browser IDE."
sidebar_position: 3
---
# Getting Started with the Snowflake Extension
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4 changes: 3 additions & 1 deletion docs/getting-started/developer/transform-tab.mdx
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---
title: Transform Tab
title: Getting Started with the Datacoves Transform Tab
sidebar_label: Transform Tab
description: "Video walkthrough of the Datacoves Transform tab: configure VS Code settings, set up your terminal, navigate the editor, and reset your environment."
sidebar_position: 4
---
# Getting Started with the VS Code in the browser via the Transform Tab
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4 changes: 3 additions & 1 deletion docs/getting-started/developer/using-git.mdx
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---
title: Using Git
title: "Git Basics in Datacoves: Branches and Changes"
sidebar_label: Using Git
description: "Essential Git commands for Datacoves developers: create and switch branches, stage and commit changes, stash work, undo commits, and use aliased shortcuts."
sidebar_position: 5
---
# Getting Started with Git - Branches and Changes
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---
title: Working with dbt in Datacoves
title: "Working with dbt in Datacoves: Models & Testing"
sidebar_label: Working with dbt
description: "Create, run, and test dbt models in Datacoves using the VS Code IDE, dbt-coves source generation, lineage views, and the Power User extension."
sidebar_position: 6
---
# Getting Started with dbt in Datacoves
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---
title: Lineage View

title: Explore dbt Lineage Graphs in Datacoves VS Code
sidebar_label: Lineage View
description: "Use the Datacoves Lineage View panel to visualize dbt model dependencies, run or test models directly from the graph, and adjust node expansion depth."
---
# Lineage View

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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/create-dag-level-docs.md
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---
title: DAGs - Add Dag Documentation
title: Add Documentation to Airflow DAGs in Datacoves
sidebar_label: Add Documentation
description: "How to add Markdown documentation directly to Airflow DAGs in Datacoves so operators can read context in the Airflow UI and Grid view."
sidebar_position: 20
---
# How to Add Docs at the DAG Level in Airflow
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/dynamically-set-schedule.md
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---
title: DAGs - Dynamically Set Schedule
title: Dynamically Set Airflow Schedule Intervals
sidebar_label: Dynamic Schedule
description: "Use environment variables or Airflow Variables to dynamically configure DAG schedule intervals in Datacoves for flexible pipeline orchestration."
sidebar_position: 22
---
# How to Dynamically set the schedule Interval
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/external-python-dag.md
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---
title: DAGs - Calling External Python Scripts
title: Call External Python Scripts from Airflow DAGs
sidebar_label: External Python Scripts
description: "Use DatacovesBashOperator to run external Python scripts from Airflow DAGs in Datacoves, with custom packages pre-installed in the worker environment."
sidebar_position: 21
---
# External Python DAG
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/generate-dags-from-yml.md
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---
title: DAGs - Generate DAGs from yml
title: Generate Airflow DAGs from YAML with dbt-coves
sidebar_label: Generate from YAML
description: "Use dbt-coves to auto-generate Airflow Python DAG files from simple YAML definitions, reducing boilerplate and standardizing pipeline creation."
sidebar_position: 23
---
# Generate DAGs from yml
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/get-current-branch-name.md
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---
title: DAGs - Get Current Git Branch Name from a DAG Task
title: Get the Git Branch Name from an Airflow DAG Task
sidebar_label: Get Git Branch Name
description: "Retrieve the current git branch name from within an Airflow DAG task in Datacoves for branch-specific logic or conditional pipeline behavior."
sidebar_position: 24
---
# Retrieving the Current Branch Name in a Git Repository
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/retry-dbt-tasks.md
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---
title: DAGs - Retry dbt jobs
title: Retry Failed dbt Tasks in Airflow DAGs
sidebar_label: Retry dbt Tasks
description: "Configure automatic retries for failed dbt tasks in Airflow DAGs in Datacoves, including retry count, delay settings, and email-on-retry behavior."
sidebar_position: 29
---
# Retry a dbt task
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/run-adf-pipeline.md
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---
title: DAGs - Run ADF Pipelines
title: Trigger ADF Pipelines from Airflow in Datacoves
sidebar_label: Run ADF Pipeline
description: "Use Azure Data Factory operators in Airflow DAGs within Datacoves to trigger and monitor ADF pipelines as part of your data orchestration workflow."
sidebar_position: 26
---
# Use Microsoft Azure Data Factory Operators
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/run-airbyte-sync-jobs.md
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---
title: DAGs - Run Airbyte sync jobs
title: Trigger Airbyte Syncs from Airflow in Datacoves
sidebar_label: Run Airbyte Syncs
description: "Orchestrate Airbyte data syncs from Airflow DAGs in Datacoves using the Airbyte provider, with examples for triggering connections and monitoring status."
sidebar_position: 27
---
# Run Airbyte sync jobs
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/run-databricks-notebook.md
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---
title: DAGs - Run Databricks Notebooks
title: Run Databricks Notebooks from Airflow DAGs
sidebar_label: Run Databricks Notebook
description: "Trigger and monitor Databricks Notebook runs from Airflow DAGs in Datacoves using the Databricks provider operator with cluster configuration."
sidebar_position: 30
---
# Run Databricks Notebooks
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/run-dbt.md
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---
title: DAGs - Run dbt
title: "Run dbt from Airflow in Datacoves: DAG Examples"
sidebar_label: Run dbt
description: "Use the Datacoves dbt decorator or operator to run dbt commands from Airflow tasks, with full examples for dbt run, dbt test, and dbt build."
sidebar_position: 28
---
# How to run dbt from an Airflow worker
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/run-fivetran-sync-jobs.md
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---
title: DAGs - Run Fivetran sync jobs
title: Trigger Fivetran Syncs from Airflow in Datacoves
sidebar_label: Run Fivetran Syncs
description: "Orchestrate Fivetran connector syncs from Airflow DAGs in Datacoves using the Fivetran provider, with connection ID configuration and monitoring."
sidebar_position: 31
---
# Run Fivetran sync jobs
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/s3-to-snowflake.md
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---
title: DAGS - Load from S3 to Snowflake
title: Load S3 Files into Snowflake with Airflow
sidebar_label: S3 to Snowflake
description: "Use Airflow in Datacoves to load files from Amazon S3 into Snowflake using the S3ToSnowflakeOperator, with staging area and copy options."
sidebar_position: 25
---
# Loading S3 Files into Snowflake
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/test-dags.md
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---
title: DAGs - Test DAGs
title: Test Airflow DAGs in Your CI/CD Pipeline
sidebar_label: Test DAGs
description: "How to run automated Airflow DAG tests in your CI/CD pipeline using pytest and the Datacoves CLI to catch import errors before deploying to production."
sidebar_position: 32
---
# Run DAG tests in your CI/CD
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/DAGs/use-variables-and-connections.md
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---
title: DAGs - Using Variables and Connections
title: Use Airflow Variables and Connections in DAGs
sidebar_label: Variables & Connections
description: "How to access and use Airflow Variables and Connections in Datacoves DAGs, with best practices for avoiding performance issues during DAG parsing."
sidebar_position: 33
---
# Variables and Connections
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/README.md
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---
title: Airflow - What to know
title: "Airflow in Datacoves: Key Things to Know First"
sidebar_label: What to know
description: "Important notes before writing Airflow DAGs in Datacoves: Ruff linting, Datacoves decorators, and My Airflow for faster personal DAG development."
sidebar_position: 1
id: airflow-index
---
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/api-triggered-dag.md
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---
title: Airflow - Trigger a DAG using Datasets
title: How to Trigger an Airflow DAG Using Datasets
sidebar_label: Trigger DAG via Datasets
description: "Step-by-step guide to triggering Airflow DAGs via dataset events in Datacoves, enabling data-driven pipeline orchestration without time-based schedules."
sidebar_position: 6
---
# How to Trigger a DAG using Datasets
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/customize-worker-environment.md
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---
title: Worker - Custom Worker Environment
title: Set Up a Custom Environment for Airflow Workers
sidebar_label: Worker - Custom Environment
description: "Configure a custom Docker image for Airflow workers in Datacoves to include specific Python packages, libraries, or dependencies your DAGs require."
sidebar_position: 39
---
# How to set up a custom environment for your Airflow workers
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/initial-setup.mdx
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---
title: Airflow - Initial setup
title: Airflow Configuration Guide for Datacoves Admins
sidebar_label: Initial Setup
description: "Configure Airflow in Datacoves: set DAG paths, git sync branch, Kubernetes executor settings, and environment-level service connections for dbt jobs."
sidebar_position: 1
---
import Tabs from '@theme/Tabs';
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/request-resources-on-workers.md
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---
title: Worker - Request Memory and CPU
title: Request Custom CPU & Memory for Airflow Workers
sidebar_label: Worker - Request CPU & Memory
description: "Configure Kubernetes resource requests for individual Airflow tasks in Datacoves to allocate specific CPU and memory limits per DAG task."
sidebar_position: 40
---
# How to request more memory or cpu resources on a particular DAG task
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4 changes: 3 additions & 1 deletion docs/how-tos/airflow/send-emails.md
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---
title: Notifications - Send Emails
title: Send Email Notifications on Airflow DAG Failure
sidebar_label: Notifications - Email
description: "Configure email alerts for Airflow DAG failures in Datacoves: set up SMTP integration, define recipient lists, and handle task-level notifications."
sidebar_position: 34
---
# How to send email notifications on DAG's failure
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