Curriculum planned

Stage 09 · Integration, CDC & Orchestration

Apache Airflow

A comprehensive Apache Airflow course covering DAG authoring, Task SDK, scheduling, dependencies, task mapping, assets and asset-aware scheduling, partitioning, backfills, sensors and deferrable work, executors, providers, XCom, secrets, testing, observability, API/server architecture, Kubernetes, HA, security, performance, upgrades, and production workflow governance.

Browse planned curriculum Back to all courses

38planned chapters

190reserved lesson paths

Intermediate → Advancedlearning level

Plannedcourse state

Coverage baselineApache Airflow 3.3.0 baseline (released July 6, 2026) with the Airflow 3 public authoring interface, airflow.sdk, service-oriented architecture, API server, Task Execution API, scheduler-managed backfills, assets and asset partitioning, event-driven scheduling, dynamic task mapping, modern executors, providers, Kubernetes deployment, and production orchestration practices

Course brief

Treat Airflow as an orchestration control plane rather than a data-processing engine: make dependencies, data assets, retries, backfills, idempotency, task isolation, metadata, and operational ownership explicit so scheduled workflows remain understandable years later.

A comprehensive Apache Airflow course covering DAG authoring, Task SDK, scheduling, dependencies, task mapping, assets and asset-aware scheduling, partitioning, backfills, sensors and deferrable work, executors, providers, XCom, secrets, testing, observability, API/server architecture, Kubernetes, HA, security, performance, upgrades, and production workflow governance.

This syllabus deliberately separates foundations, data/model semantics, internals, reliability, security, performance, operations, and production design so advanced material is not compressed into generic catch-all chapters.

By the end

You will be able to

Author Airflow 3.3 workflows through the stable airflow.sdk interface using tasks, task groups, dynamic mapping, assets, partitioned assets, parameters, and reusable components
Explain scheduler, DAG processor, API server, triggerer, executors, metadata database, Task Execution API, and the boundaries between orchestration and workload execution
Design reliable retry, timeout, SLA/SLO, backfill, catchup, sensor, deferrable, event-driven, XCom, secret, and idempotency patterns
Deploy and secure production Airflow with Local/Celery/Kubernetes/Edge-style execution concepts, providers, containers, HA components, observability, and capacity planning
Test, version, migrate, troubleshoot, optimize, and govern large DAG estates using CI/CD, policy, ownership, lineage/asset concepts, and controlled upgrade procedures

Complete planned syllabus

38 chapters · 190 lesson paths.

Every lesson path is reserved now but intentionally not linked until its lesson HTML is actually published. The sequence moves from foundations through advanced implementation, architecture, operations, reliability, security, tuning, and a production capstone.

01

Chapter 1

Airflow Foundations: Workflow Orchestration, Airflow 3.3.0, Workload Fit, Anti-Patterns, and Local Standalone Lab

5 lessons

01

Airflow Foundations: Workflow Orchestration, Airflow 3.3.0, Workload Fit, Anti-Patterns, and Local Standalone Lab: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter01/Lesson1.html

Planned02

Airflow Foundations: Workflow Orchestration, Airflow 3.3.0, Workload Fit, Anti-Patterns, and Local Standalone Lab: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter01/Lesson2.html

Planned03

Airflow Foundations: Workflow Orchestration, Airflow 3.3.0, Workload Fit, Anti-Patterns, and Local Standalone Lab: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter01/Lesson3.html

Planned04

Airflow Foundations: Workflow Orchestration, Airflow 3.3.0, Workload Fit, Anti-Patterns, and Local Standalone Lab: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter01/Lesson4.html

Planned05

Checkpoint Lab — Airflow Foundations: Workflow Orchestration, Airflow 3.3.0, Workload Fit, Anti-Patterns, and Local Standalone Lab: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter01/Lesson5.html

Planned

02

Chapter 2

Airflow 3 Architecture: Scheduler, DAG Processor, API Server, Triggerer, Metadata Database, Executors, Task Execution API, and Component Boundaries

5 lessons

01

Airflow 3 Architecture: Scheduler, DAG Processor, API Server, Triggerer, Metadata Database, Executors, Task Execution API, and Component Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter02/Lesson1.html

Planned02

Airflow 3 Architecture: Scheduler, DAG Processor, API Server, Triggerer, Metadata Database, Executors, Task Execution API, and Component Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter02/Lesson2.html

Planned03

Airflow 3 Architecture: Scheduler, DAG Processor, API Server, Triggerer, Metadata Database, Executors, Task Execution API, and Component Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter02/Lesson3.html

Planned04

Airflow 3 Architecture: Scheduler, DAG Processor, API Server, Triggerer, Metadata Database, Executors, Task Execution API, and Component Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter02/Lesson4.html

Planned05

Checkpoint Lab — Airflow 3 Architecture: Scheduler, DAG Processor, API Server, Triggerer, Metadata Database, Executors, Task Execution API, and Component Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter02/Lesson5.html

Planned

03

Chapter 3

Public Authoring Interface: airflow.sdk, DAG, @dag, @task, Stable Interfaces, Provider Boundaries, and Avoiding Internal APIs

5 lessons

01

Public Authoring Interface: airflow.sdk, DAG, @dag, @task, Stable Interfaces, Provider Boundaries, and Avoiding Internal APIs: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter03/Lesson1.html

Planned02

Public Authoring Interface: airflow.sdk, DAG, @dag, @task, Stable Interfaces, Provider Boundaries, and Avoiding Internal APIs: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter03/Lesson2.html

Planned03

Public Authoring Interface: airflow.sdk, DAG, @dag, @task, Stable Interfaces, Provider Boundaries, and Avoiding Internal APIs: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter03/Lesson3.html

Planned04

Public Authoring Interface: airflow.sdk, DAG, @dag, @task, Stable Interfaces, Provider Boundaries, and Avoiding Internal APIs: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter03/Lesson4.html

Planned05

Checkpoint Lab — Public Authoring Interface: airflow.sdk, DAG, @dag, @task, Stable Interfaces, Provider Boundaries, and Avoiding Internal APIs: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter03/Lesson5.html

Planned

04

Chapter 4

DAG Fundamentals: DAG IDs, Tasks, Dependencies, Topological Order, Parse-Time Behavior, Idempotency, and Deterministic Authoring

5 lessons

01

DAG Fundamentals: DAG IDs, Tasks, Dependencies, Topological Order, Parse-Time Behavior, Idempotency, and Deterministic Authoring: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter04/Lesson1.html

Planned02

DAG Fundamentals: DAG IDs, Tasks, Dependencies, Topological Order, Parse-Time Behavior, Idempotency, and Deterministic Authoring: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter04/Lesson2.html

Planned03

DAG Fundamentals: DAG IDs, Tasks, Dependencies, Topological Order, Parse-Time Behavior, Idempotency, and Deterministic Authoring: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter04/Lesson3.html

Planned04

DAG Fundamentals: DAG IDs, Tasks, Dependencies, Topological Order, Parse-Time Behavior, Idempotency, and Deterministic Authoring: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter04/Lesson4.html

Planned05

Checkpoint Lab — DAG Fundamentals: DAG IDs, Tasks, Dependencies, Topological Order, Parse-Time Behavior, Idempotency, and Deterministic Authoring: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter04/Lesson5.html

Planned

05

Chapter 5

TaskFlow API and Classic Operators: Decorated Tasks, Operators, Return Values, Context, Templating, and Choosing the Right Abstraction

5 lessons

01

TaskFlow API and Classic Operators: Decorated Tasks, Operators, Return Values, Context, Templating, and Choosing the Right Abstraction: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter05/Lesson1.html

Planned02

TaskFlow API and Classic Operators: Decorated Tasks, Operators, Return Values, Context, Templating, and Choosing the Right Abstraction: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter05/Lesson2.html

Planned03

TaskFlow API and Classic Operators: Decorated Tasks, Operators, Return Values, Context, Templating, and Choosing the Right Abstraction: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter05/Lesson3.html

Planned04

TaskFlow API and Classic Operators: Decorated Tasks, Operators, Return Values, Context, Templating, and Choosing the Right Abstraction: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter05/Lesson4.html

Planned05

Checkpoint Lab — TaskFlow API and Classic Operators: Decorated Tasks, Operators, Return Values, Context, Templating, and Choosing the Right Abstraction: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter05/Lesson5.html

Planned

06

Chapter 6

Scheduling Semantics: Logical Dates, Data Intervals, Timetables, Cron, Catchup, Start/End Dates, Time Zones, and DST

5 lessons

01

Scheduling Semantics: Logical Dates, Data Intervals, Timetables, Cron, Catchup, Start/End Dates, Time Zones, and DST: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter06/Lesson1.html

Planned02

Scheduling Semantics: Logical Dates, Data Intervals, Timetables, Cron, Catchup, Start/End Dates, Time Zones, and DST: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter06/Lesson2.html

Planned03

Scheduling Semantics: Logical Dates, Data Intervals, Timetables, Cron, Catchup, Start/End Dates, Time Zones, and DST: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter06/Lesson3.html

Planned04

Scheduling Semantics: Logical Dates, Data Intervals, Timetables, Cron, Catchup, Start/End Dates, Time Zones, and DST: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter06/Lesson4.html

Planned05

Checkpoint Lab — Scheduling Semantics: Logical Dates, Data Intervals, Timetables, Cron, Catchup, Start/End Dates, Time Zones, and DST: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter06/Lesson5.html

Planned

07

Chapter 7

Task Instances and States: Queued/Running/Success/Failed/Skipped/Deferred/Upstream States, Retries, Try Numbers, and State Transitions

5 lessons

01

Task Instances and States: Queued/Running/Success/Failed/Skipped/Deferred/Upstream States, Retries, Try Numbers, and State Transitions: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter07/Lesson1.html

Planned02

Task Instances and States: Queued/Running/Success/Failed/Skipped/Deferred/Upstream States, Retries, Try Numbers, and State Transitions: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter07/Lesson2.html

Planned03

Task Instances and States: Queued/Running/Success/Failed/Skipped/Deferred/Upstream States, Retries, Try Numbers, and State Transitions: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter07/Lesson3.html

Planned04

Task Instances and States: Queued/Running/Success/Failed/Skipped/Deferred/Upstream States, Retries, Try Numbers, and State Transitions: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter07/Lesson4.html

Planned05

Checkpoint Lab — Task Instances and States: Queued/Running/Success/Failed/Skipped/Deferred/Upstream States, Retries, Try Numbers, and State Transitions: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter07/Lesson5.html

Planned

08

Chapter 8

Retries, Timeouts, and Failure Policy: Retry Delay/Backoff, Execution Timeouts, Fail-Stop Patterns, Callbacks, Cleanup, and Poisoned Workloads

5 lessons

01

Retries, Timeouts, and Failure Policy: Retry Delay/Backoff, Execution Timeouts, Fail-Stop Patterns, Callbacks, Cleanup, and Poisoned Workloads: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter08/Lesson1.html

Planned02

Retries, Timeouts, and Failure Policy: Retry Delay/Backoff, Execution Timeouts, Fail-Stop Patterns, Callbacks, Cleanup, and Poisoned Workloads: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter08/Lesson2.html

Planned03

Retries, Timeouts, and Failure Policy: Retry Delay/Backoff, Execution Timeouts, Fail-Stop Patterns, Callbacks, Cleanup, and Poisoned Workloads: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter08/Lesson3.html

Planned04

Retries, Timeouts, and Failure Policy: Retry Delay/Backoff, Execution Timeouts, Fail-Stop Patterns, Callbacks, Cleanup, and Poisoned Workloads: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter08/Lesson4.html

Planned05

Checkpoint Lab — Retries, Timeouts, and Failure Policy: Retry Delay/Backoff, Execution Timeouts, Fail-Stop Patterns, Callbacks, Cleanup, and Poisoned Workloads: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter08/Lesson5.html

Planned

09

Chapter 9

Trigger Rules and Branching: all_success, none_failed, one_success, Branching, ShortCircuit, Skip Propagation, and Complex Dependency Semantics

5 lessons

01

Trigger Rules and Branching: all_success, none_failed, one_success, Branching, ShortCircuit, Skip Propagation, and Complex Dependency Semantics: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter09/Lesson1.html

Planned02

Trigger Rules and Branching: all_success, none_failed, one_success, Branching, ShortCircuit, Skip Propagation, and Complex Dependency Semantics: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter09/Lesson2.html

Planned03

Trigger Rules and Branching: all_success, none_failed, one_success, Branching, ShortCircuit, Skip Propagation, and Complex Dependency Semantics: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter09/Lesson3.html

Planned04

Trigger Rules and Branching: all_success, none_failed, one_success, Branching, ShortCircuit, Skip Propagation, and Complex Dependency Semantics: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter09/Lesson4.html

Planned05

Checkpoint Lab — Trigger Rules and Branching: all_success, none_failed, one_success, Branching, ShortCircuit, Skip Propagation, and Complex Dependency Semantics: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter09/Lesson5.html

Planned

10

Chapter 10

Task Groups and Reusable Workflow Structure: Grouping, Factories, Composition, Naming, Encapsulation, and Large-DAG Maintainability

5 lessons

01

Task Groups and Reusable Workflow Structure: Grouping, Factories, Composition, Naming, Encapsulation, and Large-DAG Maintainability: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter10/Lesson1.html

Planned02

Task Groups and Reusable Workflow Structure: Grouping, Factories, Composition, Naming, Encapsulation, and Large-DAG Maintainability: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter10/Lesson2.html

Planned03

Task Groups and Reusable Workflow Structure: Grouping, Factories, Composition, Naming, Encapsulation, and Large-DAG Maintainability: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter10/Lesson3.html

Planned04

Task Groups and Reusable Workflow Structure: Grouping, Factories, Composition, Naming, Encapsulation, and Large-DAG Maintainability: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter10/Lesson4.html

Planned05

Checkpoint Lab — Task Groups and Reusable Workflow Structure: Grouping, Factories, Composition, Naming, Encapsulation, and Large-DAG Maintainability: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter10/Lesson5.html

Planned

11

Chapter 11

Dynamic Task Mapping: Expand, Partial, Mapped Task Groups, Repeated Mapping, Filtering, Reduce Patterns, Limits, and Scheduler Cost

5 lessons

01

Dynamic Task Mapping: Expand, Partial, Mapped Task Groups, Repeated Mapping, Filtering, Reduce Patterns, Limits, and Scheduler Cost: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter11/Lesson1.html

Planned02

Dynamic Task Mapping: Expand, Partial, Mapped Task Groups, Repeated Mapping, Filtering, Reduce Patterns, Limits, and Scheduler Cost: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter11/Lesson2.html

Planned03

Dynamic Task Mapping: Expand, Partial, Mapped Task Groups, Repeated Mapping, Filtering, Reduce Patterns, Limits, and Scheduler Cost: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter11/Lesson3.html

Planned04

Dynamic Task Mapping: Expand, Partial, Mapped Task Groups, Repeated Mapping, Filtering, Reduce Patterns, Limits, and Scheduler Cost: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter11/Lesson4.html

Planned05

Checkpoint Lab — Dynamic Task Mapping: Expand, Partial, Mapped Task Groups, Repeated Mapping, Filtering, Reduce Patterns, Limits, and Scheduler Cost: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter11/Lesson5.html

Planned

12

Chapter 12

XCom and Inter-Task Data: Metadata vs Payloads, Serialization, Object Storage Backends, Size Constraints, Security, and Passing References Instead of Data

5 lessons

01

XCom and Inter-Task Data: Metadata vs Payloads, Serialization, Object Storage Backends, Size Constraints, Security, and Passing References Instead of Data: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter12/Lesson1.html

Planned02

XCom and Inter-Task Data: Metadata vs Payloads, Serialization, Object Storage Backends, Size Constraints, Security, and Passing References Instead of Data: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter12/Lesson2.html

Planned03

XCom and Inter-Task Data: Metadata vs Payloads, Serialization, Object Storage Backends, Size Constraints, Security, and Passing References Instead of Data: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter12/Lesson3.html

Planned04

XCom and Inter-Task Data: Metadata vs Payloads, Serialization, Object Storage Backends, Size Constraints, Security, and Passing References Instead of Data: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter12/Lesson4.html

Planned05

Checkpoint Lab — XCom and Inter-Task Data: Metadata vs Payloads, Serialization, Object Storage Backends, Size Constraints, Security, and Passing References Instead of Data: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter12/Lesson5.html

Planned

13

Chapter 13

Variables, Params, Connections, and Configuration: Runtime Inputs, Connection Types, Templating, Environment Separation, and Configuration Ownership

5 lessons

01

Variables, Params, Connections, and Configuration: Runtime Inputs, Connection Types, Templating, Environment Separation, and Configuration Ownership: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter13/Lesson1.html

Planned02

Variables, Params, Connections, and Configuration: Runtime Inputs, Connection Types, Templating, Environment Separation, and Configuration Ownership: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter13/Lesson2.html

Planned03

Variables, Params, Connections, and Configuration: Runtime Inputs, Connection Types, Templating, Environment Separation, and Configuration Ownership: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter13/Lesson3.html

Planned04

Variables, Params, Connections, and Configuration: Runtime Inputs, Connection Types, Templating, Environment Separation, and Configuration Ownership: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter13/Lesson4.html

Planned05

Checkpoint Lab — Variables, Params, Connections, and Configuration: Runtime Inputs, Connection Types, Templating, Environment Separation, and Configuration Ownership: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter13/Lesson5.html

Planned

14

Chapter 14

Secrets Backends: Environment/Kubernetes/Vault-Style Concepts, Connection/Variable Resolution, Rotation, Least Privilege, and Avoiding Secret Leakage

5 lessons

01

Secrets Backends: Environment/Kubernetes/Vault-Style Concepts, Connection/Variable Resolution, Rotation, Least Privilege, and Avoiding Secret Leakage: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter14/Lesson1.html

Planned02

Secrets Backends: Environment/Kubernetes/Vault-Style Concepts, Connection/Variable Resolution, Rotation, Least Privilege, and Avoiding Secret Leakage: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter14/Lesson2.html

Planned03

Secrets Backends: Environment/Kubernetes/Vault-Style Concepts, Connection/Variable Resolution, Rotation, Least Privilege, and Avoiding Secret Leakage: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter14/Lesson3.html

Planned04

Secrets Backends: Environment/Kubernetes/Vault-Style Concepts, Connection/Variable Resolution, Rotation, Least Privilege, and Avoiding Secret Leakage: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter14/Lesson4.html

Planned05

Checkpoint Lab — Secrets Backends: Environment/Kubernetes/Vault-Style Concepts, Connection/Variable Resolution, Rotation, Least Privilege, and Avoiding Secret Leakage: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter14/Lesson5.html

Planned

15

Chapter 15

Sensors and Deferrable Operators: Poke/Reschedule, Triggers, Triggerer, Async Waiting, Resource Efficiency, External Dependencies, and Event Semantics

5 lessons

01

Sensors and Deferrable Operators: Poke/Reschedule, Triggers, Triggerer, Async Waiting, Resource Efficiency, External Dependencies, and Event Semantics: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter15/Lesson1.html

Planned02

Sensors and Deferrable Operators: Poke/Reschedule, Triggers, Triggerer, Async Waiting, Resource Efficiency, External Dependencies, and Event Semantics: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter15/Lesson2.html

Planned03

Sensors and Deferrable Operators: Poke/Reschedule, Triggers, Triggerer, Async Waiting, Resource Efficiency, External Dependencies, and Event Semantics: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter15/Lesson3.html

Planned04

Sensors and Deferrable Operators: Poke/Reschedule, Triggers, Triggerer, Async Waiting, Resource Efficiency, External Dependencies, and Event Semantics: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter15/Lesson4.html

Planned05

Checkpoint Lab — Sensors and Deferrable Operators: Poke/Reschedule, Triggers, Triggerer, Async Waiting, Resource Efficiency, External Dependencies, and Event Semantics: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter15/Lesson5.html

Planned

16

Chapter 16

Assets: Asset Definitions, Producers/Consumers, Asset Events, Asset-Aware Scheduling, Metadata, Aliases, and Data-Oriented Orchestration

5 lessons

01

Assets: Asset Definitions, Producers/Consumers, Asset Events, Asset-Aware Scheduling, Metadata, Aliases, and Data-Oriented Orchestration: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter16/Lesson1.html

Planned02

Assets: Asset Definitions, Producers/Consumers, Asset Events, Asset-Aware Scheduling, Metadata, Aliases, and Data-Oriented Orchestration: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter16/Lesson2.html

Planned03

Assets: Asset Definitions, Producers/Consumers, Asset Events, Asset-Aware Scheduling, Metadata, Aliases, and Data-Oriented Orchestration: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter16/Lesson3.html

Planned04

Assets: Asset Definitions, Producers/Consumers, Asset Events, Asset-Aware Scheduling, Metadata, Aliases, and Data-Oriented Orchestration: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter16/Lesson4.html

Planned05

Checkpoint Lab — Assets: Asset Definitions, Producers/Consumers, Asset Events, Asset-Aware Scheduling, Metadata, Aliases, and Data-Oriented Orchestration: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter16/Lesson5.html

Planned

17

Chapter 17

Asset Partitioning: Partitioned Assets, Time/Category Keys, Partition Mappers, Fan-Out/Rollup, Wait Policies, Runtime Partitions, and Backfill Interaction

5 lessons

01

Asset Partitioning: Partitioned Assets, Time/Category Keys, Partition Mappers, Fan-Out/Rollup, Wait Policies, Runtime Partitions, and Backfill Interaction: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter17/Lesson1.html

Planned02

Asset Partitioning: Partitioned Assets, Time/Category Keys, Partition Mappers, Fan-Out/Rollup, Wait Policies, Runtime Partitions, and Backfill Interaction: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter17/Lesson2.html

Planned03

Asset Partitioning: Partitioned Assets, Time/Category Keys, Partition Mappers, Fan-Out/Rollup, Wait Policies, Runtime Partitions, and Backfill Interaction: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter17/Lesson3.html

Planned04

Asset Partitioning: Partitioned Assets, Time/Category Keys, Partition Mappers, Fan-Out/Rollup, Wait Policies, Runtime Partitions, and Backfill Interaction: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter17/Lesson4.html

Planned05

Checkpoint Lab — Asset Partitioning: Partitioned Assets, Time/Category Keys, Partition Mappers, Fan-Out/Rollup, Wait Policies, Runtime Partitions, and Backfill Interaction: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter17/Lesson5.html

Planned

18

Chapter 18

Event-Driven Scheduling: Asset Events, Message/Event Providers, Deferrable Patterns, Exactly-Once Illusions, Deduplication, and Event Bursts

5 lessons

01

Event-Driven Scheduling: Asset Events, Message/Event Providers, Deferrable Patterns, Exactly-Once Illusions, Deduplication, and Event Bursts: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter18/Lesson1.html

Planned02

Event-Driven Scheduling: Asset Events, Message/Event Providers, Deferrable Patterns, Exactly-Once Illusions, Deduplication, and Event Bursts: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter18/Lesson2.html

Planned03

Event-Driven Scheduling: Asset Events, Message/Event Providers, Deferrable Patterns, Exactly-Once Illusions, Deduplication, and Event Bursts: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter18/Lesson3.html

Planned04

Event-Driven Scheduling: Asset Events, Message/Event Providers, Deferrable Patterns, Exactly-Once Illusions, Deduplication, and Event Bursts: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter18/Lesson4.html

Planned05

Checkpoint Lab — Event-Driven Scheduling: Asset Events, Message/Event Providers, Deferrable Patterns, Exactly-Once Illusions, Deduplication, and Event Bursts: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter18/Lesson5.html

Planned

19

Chapter 19

Backfills in Airflow 3: Scheduler-Managed Backfills, Reprocessing Behavior, Concurrency, Date Ranges, Dry Runs, Partial Rebuilds, and Safe Reruns

5 lessons

01

Backfills in Airflow 3: Scheduler-Managed Backfills, Reprocessing Behavior, Concurrency, Date Ranges, Dry Runs, Partial Rebuilds, and Safe Reruns: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter19/Lesson1.html

Planned02

Backfills in Airflow 3: Scheduler-Managed Backfills, Reprocessing Behavior, Concurrency, Date Ranges, Dry Runs, Partial Rebuilds, and Safe Reruns: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter19/Lesson2.html

Planned03

Backfills in Airflow 3: Scheduler-Managed Backfills, Reprocessing Behavior, Concurrency, Date Ranges, Dry Runs, Partial Rebuilds, and Safe Reruns: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter19/Lesson3.html

Planned04

Backfills in Airflow 3: Scheduler-Managed Backfills, Reprocessing Behavior, Concurrency, Date Ranges, Dry Runs, Partial Rebuilds, and Safe Reruns: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter19/Lesson4.html

Planned05

Checkpoint Lab — Backfills in Airflow 3: Scheduler-Managed Backfills, Reprocessing Behavior, Concurrency, Date Ranges, Dry Runs, Partial Rebuilds, and Safe Reruns: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter19/Lesson5.html

Planned

20

Chapter 20

Datasets/Assets Migration and Compatibility: Airflow 2 Dataset Concepts, Airflow 3 Asset Model, Authoring Migration, and Semantic Differences

5 lessons

01

Datasets/Assets Migration and Compatibility: Airflow 2 Dataset Concepts, Airflow 3 Asset Model, Authoring Migration, and Semantic Differences: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter20/Lesson1.html

Planned02

Datasets/Assets Migration and Compatibility: Airflow 2 Dataset Concepts, Airflow 3 Asset Model, Authoring Migration, and Semantic Differences: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter20/Lesson2.html

Planned03

Datasets/Assets Migration and Compatibility: Airflow 2 Dataset Concepts, Airflow 3 Asset Model, Authoring Migration, and Semantic Differences: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter20/Lesson3.html

Planned04

Datasets/Assets Migration and Compatibility: Airflow 2 Dataset Concepts, Airflow 3 Asset Model, Authoring Migration, and Semantic Differences: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter20/Lesson4.html

Planned05

Checkpoint Lab — Datasets/Assets Migration and Compatibility: Airflow 2 Dataset Concepts, Airflow 3 Asset Model, Authoring Migration, and Semantic Differences: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter20/Lesson5.html

Planned

21

Chapter 21

Executors: LocalExecutor, CeleryExecutor, KubernetesExecutor, Edge Executor Concepts, Hybrid Workload Isolation, and Executor Selection

5 lessons

01

Executors: LocalExecutor, CeleryExecutor, KubernetesExecutor, Edge Executor Concepts, Hybrid Workload Isolation, and Executor Selection: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter21/Lesson1.html

Planned02

Executors: LocalExecutor, CeleryExecutor, KubernetesExecutor, Edge Executor Concepts, Hybrid Workload Isolation, and Executor Selection: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter21/Lesson2.html

Planned03

Executors: LocalExecutor, CeleryExecutor, KubernetesExecutor, Edge Executor Concepts, Hybrid Workload Isolation, and Executor Selection: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter21/Lesson3.html

Planned04

Executors: LocalExecutor, CeleryExecutor, KubernetesExecutor, Edge Executor Concepts, Hybrid Workload Isolation, and Executor Selection: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter21/Lesson4.html

Planned05

Checkpoint Lab — Executors: LocalExecutor, CeleryExecutor, KubernetesExecutor, Edge Executor Concepts, Hybrid Workload Isolation, and Executor Selection: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter21/Lesson5.html

Planned

22

Chapter 22

Celery Execution: Broker/Result Backend Concepts, Worker Queues, Routing, Autoscaling, Reliability, and Operational Failure Modes

5 lessons

01

Celery Execution: Broker/Result Backend Concepts, Worker Queues, Routing, Autoscaling, Reliability, and Operational Failure Modes: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter22/Lesson1.html

Planned02

Celery Execution: Broker/Result Backend Concepts, Worker Queues, Routing, Autoscaling, Reliability, and Operational Failure Modes: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter22/Lesson2.html

Planned03

Celery Execution: Broker/Result Backend Concepts, Worker Queues, Routing, Autoscaling, Reliability, and Operational Failure Modes: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter22/Lesson3.html

Planned04

Celery Execution: Broker/Result Backend Concepts, Worker Queues, Routing, Autoscaling, Reliability, and Operational Failure Modes: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter22/Lesson4.html

Planned05

Checkpoint Lab — Celery Execution: Broker/Result Backend Concepts, Worker Queues, Routing, Autoscaling, Reliability, and Operational Failure Modes: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter22/Lesson5.html

Planned

23

Chapter 23

Kubernetes Execution: Pods, Images, Service Accounts, Volumes, Resource Requests/Limits, Pod Overrides, Scheduling, and Cluster Security

5 lessons

01

Kubernetes Execution: Pods, Images, Service Accounts, Volumes, Resource Requests/Limits, Pod Overrides, Scheduling, and Cluster Security: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter23/Lesson1.html

Planned02

Kubernetes Execution: Pods, Images, Service Accounts, Volumes, Resource Requests/Limits, Pod Overrides, Scheduling, and Cluster Security: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter23/Lesson2.html

Planned03

Kubernetes Execution: Pods, Images, Service Accounts, Volumes, Resource Requests/Limits, Pod Overrides, Scheduling, and Cluster Security: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter23/Lesson3.html

Planned04

Kubernetes Execution: Pods, Images, Service Accounts, Volumes, Resource Requests/Limits, Pod Overrides, Scheduling, and Cluster Security: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter23/Lesson4.html

Planned05

Checkpoint Lab — Kubernetes Execution: Pods, Images, Service Accounts, Volumes, Resource Requests/Limits, Pod Overrides, Scheduling, and Cluster Security: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter23/Lesson5.html

Planned

24

Chapter 24

Edge Executor and Remote/Distributed Workloads: Edge Workers, Placement, Isolation, Connectivity, Failure Detection, and Specialized Execution Environments

5 lessons

01

Edge Executor and Remote/Distributed Workloads: Edge Workers, Placement, Isolation, Connectivity, Failure Detection, and Specialized Execution Environments: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter24/Lesson1.html

Planned02

Edge Executor and Remote/Distributed Workloads: Edge Workers, Placement, Isolation, Connectivity, Failure Detection, and Specialized Execution Environments: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter24/Lesson2.html

Planned03

Edge Executor and Remote/Distributed Workloads: Edge Workers, Placement, Isolation, Connectivity, Failure Detection, and Specialized Execution Environments: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter24/Lesson3.html

Planned04

Edge Executor and Remote/Distributed Workloads: Edge Workers, Placement, Isolation, Connectivity, Failure Detection, and Specialized Execution Environments: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter24/Lesson4.html

Planned05

Checkpoint Lab — Edge Executor and Remote/Distributed Workloads: Edge Workers, Placement, Isolation, Connectivity, Failure Detection, and Specialized Execution Environments: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter24/Lesson5.html

Planned

25

Chapter 25

Providers and Hooks: Provider Packages, Operators, Hooks, Sensors, Connection Types, Version Compatibility, and Dependency Management

5 lessons

01

Providers and Hooks: Provider Packages, Operators, Hooks, Sensors, Connection Types, Version Compatibility, and Dependency Management: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter25/Lesson1.html

Planned02

Providers and Hooks: Provider Packages, Operators, Hooks, Sensors, Connection Types, Version Compatibility, and Dependency Management: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter25/Lesson2.html

Planned03

Providers and Hooks: Provider Packages, Operators, Hooks, Sensors, Connection Types, Version Compatibility, and Dependency Management: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter25/Lesson3.html

Planned04

Providers and Hooks: Provider Packages, Operators, Hooks, Sensors, Connection Types, Version Compatibility, and Dependency Management: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter25/Lesson4.html

Planned05

Checkpoint Lab — Providers and Hooks: Provider Packages, Operators, Hooks, Sensors, Connection Types, Version Compatibility, and Dependency Management: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter25/Lesson5.html

Planned

26

Chapter 26

SQL and Data Platform Orchestration: Database Hooks, Warehouses, Spark/Flink/Kubernetes Jobs, dbt, Kafka/CDC Coordination, and External Compute Boundaries

5 lessons

01

SQL and Data Platform Orchestration: Database Hooks, Warehouses, Spark/Flink/Kubernetes Jobs, dbt, Kafka/CDC Coordination, and External Compute Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter26/Lesson1.html

Planned02

SQL and Data Platform Orchestration: Database Hooks, Warehouses, Spark/Flink/Kubernetes Jobs, dbt, Kafka/CDC Coordination, and External Compute Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter26/Lesson2.html

Planned03

SQL and Data Platform Orchestration: Database Hooks, Warehouses, Spark/Flink/Kubernetes Jobs, dbt, Kafka/CDC Coordination, and External Compute Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter26/Lesson3.html

Planned04

SQL and Data Platform Orchestration: Database Hooks, Warehouses, Spark/Flink/Kubernetes Jobs, dbt, Kafka/CDC Coordination, and External Compute Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter26/Lesson4.html

Planned05

Checkpoint Lab — SQL and Data Platform Orchestration: Database Hooks, Warehouses, Spark/Flink/Kubernetes Jobs, dbt, Kafka/CDC Coordination, and External Compute Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter26/Lesson5.html

Planned

27

Chapter 27

Files, Object Storage, and Transfer Workflows: S3/GCS/Azure Concepts, Atomicity, Temporary Paths, Checksums, Partitioned Data, and Transfer Validation

5 lessons

01

Files, Object Storage, and Transfer Workflows: S3/GCS/Azure Concepts, Atomicity, Temporary Paths, Checksums, Partitioned Data, and Transfer Validation: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter27/Lesson1.html

Planned02

Files, Object Storage, and Transfer Workflows: S3/GCS/Azure Concepts, Atomicity, Temporary Paths, Checksums, Partitioned Data, and Transfer Validation: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter27/Lesson2.html

Planned03

Files, Object Storage, and Transfer Workflows: S3/GCS/Azure Concepts, Atomicity, Temporary Paths, Checksums, Partitioned Data, and Transfer Validation: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter27/Lesson3.html

Planned04

Files, Object Storage, and Transfer Workflows: S3/GCS/Azure Concepts, Atomicity, Temporary Paths, Checksums, Partitioned Data, and Transfer Validation: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter27/Lesson4.html

Planned05

Checkpoint Lab — Files, Object Storage, and Transfer Workflows: S3/GCS/Azure Concepts, Atomicity, Temporary Paths, Checksums, Partitioned Data, and Transfer Validation: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter27/Lesson5.html

Planned

28

Chapter 28

REST API and Automation: API Server, Authentication, DAG Runs, Tasks, Assets, Backfills, CLI vs API, Idempotent Automation, and External Control Planes

5 lessons

01

REST API and Automation: API Server, Authentication, DAG Runs, Tasks, Assets, Backfills, CLI vs API, Idempotent Automation, and External Control Planes: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter28/Lesson1.html

Planned02

REST API and Automation: API Server, Authentication, DAG Runs, Tasks, Assets, Backfills, CLI vs API, Idempotent Automation, and External Control Planes: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter28/Lesson2.html

Planned03

REST API and Automation: API Server, Authentication, DAG Runs, Tasks, Assets, Backfills, CLI vs API, Idempotent Automation, and External Control Planes: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter28/Lesson3.html

Planned04

REST API and Automation: API Server, Authentication, DAG Runs, Tasks, Assets, Backfills, CLI vs API, Idempotent Automation, and External Control Planes: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter28/Lesson4.html

Planned05

Checkpoint Lab — REST API and Automation: API Server, Authentication, DAG Runs, Tasks, Assets, Backfills, CLI vs API, Idempotent Automation, and External Control Planes: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter28/Lesson5.html

Planned

29

Chapter 29

Metadata Database Internals and Maintenance: Core Tables, Connection Pooling, Cleanup, Index/DB Performance, Backups, and Why Tasks Must Not Query It Directly

5 lessons

01

Metadata Database Internals and Maintenance: Core Tables, Connection Pooling, Cleanup, Index/DB Performance, Backups, and Why Tasks Must Not Query It Directly: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter29/Lesson1.html

Planned02

Metadata Database Internals and Maintenance: Core Tables, Connection Pooling, Cleanup, Index/DB Performance, Backups, and Why Tasks Must Not Query It Directly: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter29/Lesson2.html

Planned03

Metadata Database Internals and Maintenance: Core Tables, Connection Pooling, Cleanup, Index/DB Performance, Backups, and Why Tasks Must Not Query It Directly: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter29/Lesson3.html

Planned04

Metadata Database Internals and Maintenance: Core Tables, Connection Pooling, Cleanup, Index/DB Performance, Backups, and Why Tasks Must Not Query It Directly: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter29/Lesson4.html

Planned05

Checkpoint Lab — Metadata Database Internals and Maintenance: Core Tables, Connection Pooling, Cleanup, Index/DB Performance, Backups, and Why Tasks Must Not Query It Directly: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter29/Lesson5.html

Planned

30

Chapter 30

Observability: UI, Logs, Metrics, OpenTelemetry/StatsD Concepts, Task Duration, Scheduler Health, Queue Delay, Triggerer Health, and Alerting

5 lessons

01

Observability: UI, Logs, Metrics, OpenTelemetry/StatsD Concepts, Task Duration, Scheduler Health, Queue Delay, Triggerer Health, and Alerting: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter30/Lesson1.html

Planned02

Observability: UI, Logs, Metrics, OpenTelemetry/StatsD Concepts, Task Duration, Scheduler Health, Queue Delay, Triggerer Health, and Alerting: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter30/Lesson2.html

Planned03

Observability: UI, Logs, Metrics, OpenTelemetry/StatsD Concepts, Task Duration, Scheduler Health, Queue Delay, Triggerer Health, and Alerting: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter30/Lesson3.html

Planned04

Observability: UI, Logs, Metrics, OpenTelemetry/StatsD Concepts, Task Duration, Scheduler Health, Queue Delay, Triggerer Health, and Alerting: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter30/Lesson4.html

Planned05

Checkpoint Lab — Observability: UI, Logs, Metrics, OpenTelemetry/StatsD Concepts, Task Duration, Scheduler Health, Queue Delay, Triggerer Health, and Alerting: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter30/Lesson5.html

Planned

31

Chapter 31

Testing DAGs: Import Tests, Unit Tests, Task Tests, Dag Bags, Mocking Connections, Contract Tests, Time Semantics, and Integration Environments

5 lessons

01

Testing DAGs: Import Tests, Unit Tests, Task Tests, Dag Bags, Mocking Connections, Contract Tests, Time Semantics, and Integration Environments: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter31/Lesson1.html

Planned02

Testing DAGs: Import Tests, Unit Tests, Task Tests, Dag Bags, Mocking Connections, Contract Tests, Time Semantics, and Integration Environments: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter31/Lesson2.html

Planned03

Testing DAGs: Import Tests, Unit Tests, Task Tests, Dag Bags, Mocking Connections, Contract Tests, Time Semantics, and Integration Environments: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter31/Lesson3.html

Planned04

Testing DAGs: Import Tests, Unit Tests, Task Tests, Dag Bags, Mocking Connections, Contract Tests, Time Semantics, and Integration Environments: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter31/Lesson4.html

Planned05

Checkpoint Lab — Testing DAGs: Import Tests, Unit Tests, Task Tests, Dag Bags, Mocking Connections, Contract Tests, Time Semantics, and Integration Environments: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter31/Lesson5.html

Planned

32

Chapter 32

DAG Quality and CI/CD: Linting, Static Validation, Serialization, Packaging, Image Builds, GitOps, Promotion, Canary Workflows, and Rollback

5 lessons

01

DAG Quality and CI/CD: Linting, Static Validation, Serialization, Packaging, Image Builds, GitOps, Promotion, Canary Workflows, and Rollback: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter32/Lesson1.html

Planned02

DAG Quality and CI/CD: Linting, Static Validation, Serialization, Packaging, Image Builds, GitOps, Promotion, Canary Workflows, and Rollback: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter32/Lesson2.html

Planned03

DAG Quality and CI/CD: Linting, Static Validation, Serialization, Packaging, Image Builds, GitOps, Promotion, Canary Workflows, and Rollback: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter32/Lesson3.html

Planned04

DAG Quality and CI/CD: Linting, Static Validation, Serialization, Packaging, Image Builds, GitOps, Promotion, Canary Workflows, and Rollback: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter32/Lesson4.html

Planned05

Checkpoint Lab — DAG Quality and CI/CD: Linting, Static Validation, Serialization, Packaging, Image Builds, GitOps, Promotion, Canary Workflows, and Rollback: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter32/Lesson5.html

Planned

33

Chapter 33

Security: Authentication, RBAC, API Security, TLS/Proxy Boundaries, Secrets, Impersonation, DAG Code Trust, Supply Chain, and Multi-Tenant Threat Models

5 lessons

01

Security: Authentication, RBAC, API Security, TLS/Proxy Boundaries, Secrets, Impersonation, DAG Code Trust, Supply Chain, and Multi-Tenant Threat Models: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter33/Lesson1.html

Planned02

Security: Authentication, RBAC, API Security, TLS/Proxy Boundaries, Secrets, Impersonation, DAG Code Trust, Supply Chain, and Multi-Tenant Threat Models: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter33/Lesson2.html

Planned03

Security: Authentication, RBAC, API Security, TLS/Proxy Boundaries, Secrets, Impersonation, DAG Code Trust, Supply Chain, and Multi-Tenant Threat Models: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter33/Lesson3.html

Planned04

Security: Authentication, RBAC, API Security, TLS/Proxy Boundaries, Secrets, Impersonation, DAG Code Trust, Supply Chain, and Multi-Tenant Threat Models: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter33/Lesson4.html

Planned05

Checkpoint Lab — Security: Authentication, RBAC, API Security, TLS/Proxy Boundaries, Secrets, Impersonation, DAG Code Trust, Supply Chain, and Multi-Tenant Threat Models: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter33/Lesson5.html

Planned

34

Chapter 34

Performance and Scaling: Parsing Cost, Scheduler Throughput, Pools, Concurrency, Max Active Runs, Mapping Limits, Database Pressure, and DAG Design for Scale

5 lessons

01

Performance and Scaling: Parsing Cost, Scheduler Throughput, Pools, Concurrency, Max Active Runs, Mapping Limits, Database Pressure, and DAG Design for Scale: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter34/Lesson1.html

Planned02

Performance and Scaling: Parsing Cost, Scheduler Throughput, Pools, Concurrency, Max Active Runs, Mapping Limits, Database Pressure, and DAG Design for Scale: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter34/Lesson2.html

Planned03

Performance and Scaling: Parsing Cost, Scheduler Throughput, Pools, Concurrency, Max Active Runs, Mapping Limits, Database Pressure, and DAG Design for Scale: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter34/Lesson3.html

Planned04

Performance and Scaling: Parsing Cost, Scheduler Throughput, Pools, Concurrency, Max Active Runs, Mapping Limits, Database Pressure, and DAG Design for Scale: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter34/Lesson4.html

Planned05

Checkpoint Lab — Performance and Scaling: Parsing Cost, Scheduler Throughput, Pools, Concurrency, Max Active Runs, Mapping Limits, Database Pressure, and DAG Design for Scale: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter34/Lesson5.html

Planned

35

Chapter 35

High Availability and Disaster Recovery: Multiple Schedulers, API Servers, Triggerers, Metadata DB HA, Executor/Broker Failure, Backups, and Recovery Runbooks

5 lessons

01

High Availability and Disaster Recovery: Multiple Schedulers, API Servers, Triggerers, Metadata DB HA, Executor/Broker Failure, Backups, and Recovery Runbooks: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter35/Lesson1.html

Planned02

High Availability and Disaster Recovery: Multiple Schedulers, API Servers, Triggerers, Metadata DB HA, Executor/Broker Failure, Backups, and Recovery Runbooks: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter35/Lesson2.html

Planned03

High Availability and Disaster Recovery: Multiple Schedulers, API Servers, Triggerers, Metadata DB HA, Executor/Broker Failure, Backups, and Recovery Runbooks: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter35/Lesson3.html

Planned04

High Availability and Disaster Recovery: Multiple Schedulers, API Servers, Triggerers, Metadata DB HA, Executor/Broker Failure, Backups, and Recovery Runbooks: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter35/Lesson4.html

Planned05

Checkpoint Lab — High Availability and Disaster Recovery: Multiple Schedulers, API Servers, Triggerers, Metadata DB HA, Executor/Broker Failure, Backups, and Recovery Runbooks: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter35/Lesson5.html

Planned

36

Chapter 36

Governance and Platform Engineering: DAG Ownership, Policies, Pools, Cluster Policies, Naming Standards, Asset Cataloging, Cost Attribution, and Self-Service Guardrails

5 lessons

01

Governance and Platform Engineering: DAG Ownership, Policies, Pools, Cluster Policies, Naming Standards, Asset Cataloging, Cost Attribution, and Self-Service Guardrails: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter36/Lesson1.html

Planned02

Governance and Platform Engineering: DAG Ownership, Policies, Pools, Cluster Policies, Naming Standards, Asset Cataloging, Cost Attribution, and Self-Service Guardrails: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter36/Lesson2.html

Planned03

Governance and Platform Engineering: DAG Ownership, Policies, Pools, Cluster Policies, Naming Standards, Asset Cataloging, Cost Attribution, and Self-Service Guardrails: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter36/Lesson3.html

Planned04

Governance and Platform Engineering: DAG Ownership, Policies, Pools, Cluster Policies, Naming Standards, Asset Cataloging, Cost Attribution, and Self-Service Guardrails: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter36/Lesson4.html

Planned05

Checkpoint Lab — Governance and Platform Engineering: DAG Ownership, Policies, Pools, Cluster Policies, Naming Standards, Asset Cataloging, Cost Attribution, and Self-Service Guardrails: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter36/Lesson5.html

Planned

37

Chapter 37

Upgrading Airflow 2.x to 3.x and 3.x Minors: Public API Migration, Removed Behaviors, Provider Compatibility, Database Migration, Rollback, and Regression Gates

5 lessons

01

Upgrading Airflow 2.x to 3.x and 3.x Minors: Public API Migration, Removed Behaviors, Provider Compatibility, Database Migration, Rollback, and Regression Gates: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter37/Lesson1.html

Planned02

Upgrading Airflow 2.x to 3.x and 3.x Minors: Public API Migration, Removed Behaviors, Provider Compatibility, Database Migration, Rollback, and Regression Gates: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter37/Lesson2.html

Planned03

Upgrading Airflow 2.x to 3.x and 3.x Minors: Public API Migration, Removed Behaviors, Provider Compatibility, Database Migration, Rollback, and Regression Gates: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter37/Lesson3.html

Planned04

Upgrading Airflow 2.x to 3.x and 3.x Minors: Public API Migration, Removed Behaviors, Provider Compatibility, Database Migration, Rollback, and Regression Gates: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter37/Lesson4.html

Planned05

Checkpoint Lab — Upgrading Airflow 2.x to 3.x and 3.x Minors: Public API Migration, Removed Behaviors, Provider Compatibility, Database Migration, Rollback, and Regression Gates: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter37/Lesson5.html

Planned

38

Chapter 38

Production Capstone: Author, Map, Asset-Schedule, Backfill, Secure, Deploy, Observe, Fail, Recover, Scale, and Upgrade an Airflow 3.3 Platform

5 lessons

01

Production Capstone: Author, Map, Asset-Schedule, Backfill, Secure, Deploy, Observe, Fail, Recover, Scale, and Upgrade an Airflow 3.3 Platform: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter38/Lesson1.html

Planned02

Production Capstone: Author, Map, Asset-Schedule, Backfill, Secure, Deploy, Observe, Fail, Recover, Scale, and Upgrade an Airflow 3.3 Platform: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter38/Lesson2.html

Planned03

Production Capstone: Author, Map, Asset-Schedule, Backfill, Secure, Deploy, Observe, Fail, Recover, Scale, and Upgrade an Airflow 3.3 Platform: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter38/Lesson3.html

Planned04

Production Capstone: Author, Map, Asset-Schedule, Backfill, Secure, Deploy, Observe, Fail, Recover, Scale, and Upgrade an Airflow 3.3 Platform: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter38/Lesson4.html

Planned05

Checkpoint Lab — Production Capstone: Author, Map, Asset-Schedule, Backfill, Secure, Deploy, Observe, Fail, Recover, Scale, and Upgrade an Airflow 3.3 Platform: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter38/Lesson5.html

Planned