Curriculum planned

Stage 08 · Event Streaming & Real-Time Processing

Apache Beam

A comprehensive Apache Beam course covering the unified batch/streaming model, PCollections and transforms, event time, watermarks, windows and triggers, state and timers, Splittable DoFn, schemas and Beam SQL, I/O connectors, cross-language transforms, portability, runners, testing, performance, observability, security, upgrades, and production pipeline design.

Browse planned curriculum Back to all courses

34planned chapters

170reserved lesson paths

Advancedlearning level

Plannedcourse state

Coverage baselineApache Beam 2.75.0 baseline (released July 8, 2026) with Java/Python/Go SDKs, portable runners, unified bounded/unbounded processing, modern state/timers, schemas, cross-language transforms, Splittable DoFn, Beam SQL, Iceberg/Delta integrations, and production runner portability

Course brief

Design Beam pipelines from semantics first—boundedness, event time, windowing, state, triggers, side effects, and runner guarantees—then map those semantics onto portable execution engines without assuming every runner behaves identically.

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

Build bounded and unbounded pipelines in Beam using Java, Python, or Go SDK concepts, reusable transforms, schemas, and tested I/O boundaries
Reason precisely about event time, processing time, watermarks, windows, triggers, allowed lateness, accumulation modes, state, timers, and late-data correctness
Implement scalable source/sink logic with Splittable DoFn, side inputs/outputs, batching, cross-language transforms, and schema-aware processing
Compare DirectRunner, Flink, Spark, Dataflow and other runner behaviors using the portability model, capability constraints, metrics, and failure semantics
Package, secure, benchmark, observe, upgrade, and operate production Beam pipelines with reproducibility, fault injection, and explicit correctness assertions

Complete planned syllabus

34 chapters · 170 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.

Chapter 1

Beam Foundations: Unified Batch and Streaming, Beam 2.75.0, SDKs, Runners, Portability, and Local Lab Setup

5 lessons

Beam Foundations: Unified Batch and Streaming, Beam 2.75.0, SDKs, Runners, Portability, and Local Lab Setup: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter01/Lesson1.html

Planned02

Beam Foundations: Unified Batch and Streaming, Beam 2.75.0, SDKs, Runners, Portability, and Local Lab Setup: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter01/Lesson2.html

Planned03

Beam Foundations: Unified Batch and Streaming, Beam 2.75.0, SDKs, Runners, Portability, and Local Lab Setup: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter01/Lesson3.html

Planned04

Beam Foundations: Unified Batch and Streaming, Beam 2.75.0, SDKs, Runners, Portability, and Local Lab Setup: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter01/Lesson4.html

Planned05

Checkpoint Lab — Beam Foundations: Unified Batch and Streaming, Beam 2.75.0, SDKs, Runners, Portability, and Local Lab Setup: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter01/Lesson5.html

Planned

Chapter 2

Programming Model: Pipeline, PCollection, PTransform, ParDo, DoFn, Immutability, and Deferred Execution

5 lessons

Programming Model: Pipeline, PCollection, PTransform, ParDo, DoFn, Immutability, and Deferred Execution: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter02/Lesson1.html

Planned02

Programming Model: Pipeline, PCollection, PTransform, ParDo, DoFn, Immutability, and Deferred Execution: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter02/Lesson2.html

Planned03

Programming Model: Pipeline, PCollection, PTransform, ParDo, DoFn, Immutability, and Deferred Execution: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter02/Lesson3.html

Planned04

Programming Model: Pipeline, PCollection, PTransform, ParDo, DoFn, Immutability, and Deferred Execution: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter02/Lesson4.html

Planned05

Checkpoint Lab — Programming Model: Pipeline, PCollection, PTransform, ParDo, DoFn, Immutability, and Deferred Execution: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter02/Lesson5.html

Planned

Chapter 3

SDK Workflows: Java, Python, and Go Project Structure, Dependencies, Options, Packaging, and Reproducible Environments

5 lessons

SDK Workflows: Java, Python, and Go Project Structure, Dependencies, Options, Packaging, and Reproducible Environments: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter03/Lesson1.html

Planned02

SDK Workflows: Java, Python, and Go Project Structure, Dependencies, Options, Packaging, and Reproducible Environments: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter03/Lesson2.html

Planned03

SDK Workflows: Java, Python, and Go Project Structure, Dependencies, Options, Packaging, and Reproducible Environments: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter03/Lesson3.html

Planned04

SDK Workflows: Java, Python, and Go Project Structure, Dependencies, Options, Packaging, and Reproducible Environments: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter03/Lesson4.html

Planned05

Checkpoint Lab — SDK Workflows: Java, Python, and Go Project Structure, Dependencies, Options, Packaging, and Reproducible Environments: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter03/Lesson5.html

Planned

Chapter 4

PCollection Semantics: Boundedness, Element Types, Coders, Determinism, Partitioning Expectations, and Data Contracts

5 lessons

PCollection Semantics: Boundedness, Element Types, Coders, Determinism, Partitioning Expectations, and Data Contracts: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter04/Lesson1.html

Planned02

PCollection Semantics: Boundedness, Element Types, Coders, Determinism, Partitioning Expectations, and Data Contracts: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter04/Lesson2.html

Planned03

PCollection Semantics: Boundedness, Element Types, Coders, Determinism, Partitioning Expectations, and Data Contracts: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter04/Lesson3.html

Planned04

PCollection Semantics: Boundedness, Element Types, Coders, Determinism, Partitioning Expectations, and Data Contracts: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter04/Lesson4.html

Planned05

Checkpoint Lab — PCollection Semantics: Boundedness, Element Types, Coders, Determinism, Partitioning Expectations, and Data Contracts: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter04/Lesson5.html

Planned

Chapter 5

Core Transforms: Map/FlatMap, Filter, Flatten, Partition, Distinct, Combine, GroupByKey, CoGroupByKey, and Composite Transforms

5 lessons

Core Transforms: Map/FlatMap, Filter, Flatten, Partition, Distinct, Combine, GroupByKey, CoGroupByKey, and Composite Transforms: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter05/Lesson1.html

Planned02

Core Transforms: Map/FlatMap, Filter, Flatten, Partition, Distinct, Combine, GroupByKey, CoGroupByKey, and Composite Transforms: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter05/Lesson2.html

Planned03

Core Transforms: Map/FlatMap, Filter, Flatten, Partition, Distinct, Combine, GroupByKey, CoGroupByKey, and Composite Transforms: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter05/Lesson3.html

Planned04

Core Transforms: Map/FlatMap, Filter, Flatten, Partition, Distinct, Combine, GroupByKey, CoGroupByKey, and Composite Transforms: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter05/Lesson4.html

Planned05

Checkpoint Lab — Core Transforms: Map/FlatMap, Filter, Flatten, Partition, Distinct, Combine, GroupByKey, CoGroupByKey, and Composite Transforms: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter05/Lesson5.html

Planned

Chapter 6

Keys and Aggregation: Keying Strategy, Hot Keys, Combiners, Pre-Aggregation, Fanout, Associativity, and Scaling Tradeoffs

5 lessons

Keys and Aggregation: Keying Strategy, Hot Keys, Combiners, Pre-Aggregation, Fanout, Associativity, and Scaling Tradeoffs: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter06/Lesson1.html

Planned02

Keys and Aggregation: Keying Strategy, Hot Keys, Combiners, Pre-Aggregation, Fanout, Associativity, and Scaling Tradeoffs: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter06/Lesson2.html

Planned03

Keys and Aggregation: Keying Strategy, Hot Keys, Combiners, Pre-Aggregation, Fanout, Associativity, and Scaling Tradeoffs: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter06/Lesson3.html

Planned04

Keys and Aggregation: Keying Strategy, Hot Keys, Combiners, Pre-Aggregation, Fanout, Associativity, and Scaling Tradeoffs: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter06/Lesson4.html

Planned05

Checkpoint Lab — Keys and Aggregation: Keying Strategy, Hot Keys, Combiners, Pre-Aggregation, Fanout, Associativity, and Scaling Tradeoffs: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter06/Lesson5.html

Planned

Chapter 7

Time Semantics: Event Time, Processing Time, Ingestion Time, Timestamps, Clock Skew, and Correctness Boundaries

5 lessons

Time Semantics: Event Time, Processing Time, Ingestion Time, Timestamps, Clock Skew, and Correctness Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter07/Lesson1.html

Planned02

Time Semantics: Event Time, Processing Time, Ingestion Time, Timestamps, Clock Skew, and Correctness Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter07/Lesson2.html

Planned03

Time Semantics: Event Time, Processing Time, Ingestion Time, Timestamps, Clock Skew, and Correctness Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter07/Lesson3.html

Planned04

Time Semantics: Event Time, Processing Time, Ingestion Time, Timestamps, Clock Skew, and Correctness Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter07/Lesson4.html

Planned05

Checkpoint Lab — Time Semantics: Event Time, Processing Time, Ingestion Time, Timestamps, Clock Skew, and Correctness Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter07/Lesson5.html

Planned

Chapter 8

Watermarks: Progress Estimation, Source Watermarks, Holds, Idle Inputs, Late Data, and Runner-Specific Behavior

5 lessons

Watermarks: Progress Estimation, Source Watermarks, Holds, Idle Inputs, Late Data, and Runner-Specific Behavior: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter08/Lesson1.html

Planned02

Watermarks: Progress Estimation, Source Watermarks, Holds, Idle Inputs, Late Data, and Runner-Specific Behavior: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter08/Lesson2.html

Planned03

Watermarks: Progress Estimation, Source Watermarks, Holds, Idle Inputs, Late Data, and Runner-Specific Behavior: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter08/Lesson3.html

Planned04

Watermarks: Progress Estimation, Source Watermarks, Holds, Idle Inputs, Late Data, and Runner-Specific Behavior: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter08/Lesson4.html

Planned05

Checkpoint Lab — Watermarks: Progress Estimation, Source Watermarks, Holds, Idle Inputs, Late Data, and Runner-Specific Behavior: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter08/Lesson5.html

Planned

Chapter 9

Windows: Fixed, Sliding, Sessions, Global Window, Custom WindowFns, Merging, and Window Compatibility

5 lessons

Windows: Fixed, Sliding, Sessions, Global Window, Custom WindowFns, Merging, and Window Compatibility: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter09/Lesson1.html

Planned02

Windows: Fixed, Sliding, Sessions, Global Window, Custom WindowFns, Merging, and Window Compatibility: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter09/Lesson2.html

Planned03

Windows: Fixed, Sliding, Sessions, Global Window, Custom WindowFns, Merging, and Window Compatibility: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter09/Lesson3.html

Planned04

Windows: Fixed, Sliding, Sessions, Global Window, Custom WindowFns, Merging, and Window Compatibility: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter09/Lesson4.html

Planned05

Checkpoint Lab — Windows: Fixed, Sliding, Sessions, Global Window, Custom WindowFns, Merging, and Window Compatibility: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter09/Lesson5.html

Planned

Chapter 10

Triggers: Event-Time, Processing-Time, Count, Composite Triggers, Repeatedly, OrFinally, and Operational Consequences

5 lessons

Triggers: Event-Time, Processing-Time, Count, Composite Triggers, Repeatedly, OrFinally, and Operational Consequences: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter10/Lesson1.html

Planned02

Triggers: Event-Time, Processing-Time, Count, Composite Triggers, Repeatedly, OrFinally, and Operational Consequences: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter10/Lesson2.html

Planned03

Triggers: Event-Time, Processing-Time, Count, Composite Triggers, Repeatedly, OrFinally, and Operational Consequences: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter10/Lesson3.html

Planned04

Triggers: Event-Time, Processing-Time, Count, Composite Triggers, Repeatedly, OrFinally, and Operational Consequences: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter10/Lesson4.html

Planned05

Checkpoint Lab — Triggers: Event-Time, Processing-Time, Count, Composite Triggers, Repeatedly, OrFinally, and Operational Consequences: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter10/Lesson5.html

Planned

Chapter 11

Accumulation and Lateness: Discarding vs Accumulating Panes, Allowed Lateness, Pane Info, Retractions, and Downstream Semantics

5 lessons

Accumulation and Lateness: Discarding vs Accumulating Panes, Allowed Lateness, Pane Info, Retractions, and Downstream Semantics: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter11/Lesson1.html

Planned02

Accumulation and Lateness: Discarding vs Accumulating Panes, Allowed Lateness, Pane Info, Retractions, and Downstream Semantics: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter11/Lesson2.html

Planned03

Accumulation and Lateness: Discarding vs Accumulating Panes, Allowed Lateness, Pane Info, Retractions, and Downstream Semantics: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter11/Lesson3.html

Planned04

Accumulation and Lateness: Discarding vs Accumulating Panes, Allowed Lateness, Pane Info, Retractions, and Downstream Semantics: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter11/Lesson4.html

Planned05

Checkpoint Lab — Accumulation and Lateness: Discarding vs Accumulating Panes, Allowed Lateness, Pane Info, Retractions, and Downstream Semantics: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter11/Lesson5.html

Planned

Chapter 12

Side Inputs and Side Outputs: Views, Broadcast-Like Data, Tagged Outputs, Memory Cost, Refresh Semantics, and Alternatives

5 lessons

Side Inputs and Side Outputs: Views, Broadcast-Like Data, Tagged Outputs, Memory Cost, Refresh Semantics, and Alternatives: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter12/Lesson1.html

Planned02

Side Inputs and Side Outputs: Views, Broadcast-Like Data, Tagged Outputs, Memory Cost, Refresh Semantics, and Alternatives: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter12/Lesson2.html

Planned03

Side Inputs and Side Outputs: Views, Broadcast-Like Data, Tagged Outputs, Memory Cost, Refresh Semantics, and Alternatives: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter12/Lesson3.html

Planned04

Side Inputs and Side Outputs: Views, Broadcast-Like Data, Tagged Outputs, Memory Cost, Refresh Semantics, and Alternatives: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter12/Lesson4.html

Planned05

Checkpoint Lab — Side Inputs and Side Outputs: Views, Broadcast-Like Data, Tagged Outputs, Memory Cost, Refresh Semantics, and Alternatives: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter12/Lesson5.html

Planned

Chapter 13

DoFn Lifecycle and Execution: Setup, StartBundle, ProcessElement, FinishBundle, Teardown, Serialization, Thread Safety, and Retries

5 lessons

DoFn Lifecycle and Execution: Setup, StartBundle, ProcessElement, FinishBundle, Teardown, Serialization, Thread Safety, and Retries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter13/Lesson1.html

Planned02

DoFn Lifecycle and Execution: Setup, StartBundle, ProcessElement, FinishBundle, Teardown, Serialization, Thread Safety, and Retries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter13/Lesson2.html

Planned03

DoFn Lifecycle and Execution: Setup, StartBundle, ProcessElement, FinishBundle, Teardown, Serialization, Thread Safety, and Retries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter13/Lesson3.html

Planned04

DoFn Lifecycle and Execution: Setup, StartBundle, ProcessElement, FinishBundle, Teardown, Serialization, Thread Safety, and Retries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter13/Lesson4.html

Planned05

Checkpoint Lab — DoFn Lifecycle and Execution: Setup, StartBundle, ProcessElement, FinishBundle, Teardown, Serialization, Thread Safety, and Retries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter13/Lesson5.html

Planned

Chapter 14

Stateful Processing: Keyed State, Value/Bag/Map/Set/Combining State, State Scope, Garbage Collection, and Upgrade Constraints

5 lessons

Stateful Processing: Keyed State, Value/Bag/Map/Set/Combining State, State Scope, Garbage Collection, and Upgrade Constraints: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter14/Lesson1.html

Planned02

Stateful Processing: Keyed State, Value/Bag/Map/Set/Combining State, State Scope, Garbage Collection, and Upgrade Constraints: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter14/Lesson2.html

Planned03

Stateful Processing: Keyed State, Value/Bag/Map/Set/Combining State, State Scope, Garbage Collection, and Upgrade Constraints: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter14/Lesson3.html

Planned04

Stateful Processing: Keyed State, Value/Bag/Map/Set/Combining State, State Scope, Garbage Collection, and Upgrade Constraints: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter14/Lesson4.html

Planned05

Checkpoint Lab — Stateful Processing: Keyed State, Value/Bag/Map/Set/Combining State, State Scope, Garbage Collection, and Upgrade Constraints: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter14/Lesson5.html

Planned

Chapter 15

Timers: Event-Time and Processing-Time Timers, Dynamic Timers, Timer Families, Coordination with State, and Determinism

5 lessons

Timers: Event-Time and Processing-Time Timers, Dynamic Timers, Timer Families, Coordination with State, and Determinism: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter15/Lesson1.html

Planned02

Timers: Event-Time and Processing-Time Timers, Dynamic Timers, Timer Families, Coordination with State, and Determinism: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter15/Lesson2.html

Planned03

Timers: Event-Time and Processing-Time Timers, Dynamic Timers, Timer Families, Coordination with State, and Determinism: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter15/Lesson3.html

Planned04

Timers: Event-Time and Processing-Time Timers, Dynamic Timers, Timer Families, Coordination with State, and Determinism: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter15/Lesson4.html

Planned05

Checkpoint Lab — Timers: Event-Time and Processing-Time Timers, Dynamic Timers, Timer Families, Coordination with State, and Determinism: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter15/Lesson5.html

Planned

Chapter 16

Splittable DoFn: Restrictions, Trackers, Claims, Dynamic Splitting, Progress, Watermarks, Checkpointing, and Custom Sources

5 lessons

Splittable DoFn: Restrictions, Trackers, Claims, Dynamic Splitting, Progress, Watermarks, Checkpointing, and Custom Sources: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter16/Lesson1.html

Planned02

Splittable DoFn: Restrictions, Trackers, Claims, Dynamic Splitting, Progress, Watermarks, Checkpointing, and Custom Sources: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter16/Lesson2.html

Planned03

Splittable DoFn: Restrictions, Trackers, Claims, Dynamic Splitting, Progress, Watermarks, Checkpointing, and Custom Sources: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter16/Lesson3.html

Planned04

Splittable DoFn: Restrictions, Trackers, Claims, Dynamic Splitting, Progress, Watermarks, Checkpointing, and Custom Sources: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter16/Lesson4.html

Planned05

Checkpoint Lab — Splittable DoFn: Restrictions, Trackers, Claims, Dynamic Splitting, Progress, Watermarks, Checkpointing, and Custom Sources: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter16/Lesson5.html

Planned

Chapter 17

Schemas and Row-Oriented Processing: Beam Schemas, Rows, Logical Types, Schema Inference, Field Access, and Language Interoperability

5 lessons

Schemas and Row-Oriented Processing: Beam Schemas, Rows, Logical Types, Schema Inference, Field Access, and Language Interoperability: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter17/Lesson1.html

Planned02

Schemas and Row-Oriented Processing: Beam Schemas, Rows, Logical Types, Schema Inference, Field Access, and Language Interoperability: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter17/Lesson2.html

Planned03

Schemas and Row-Oriented Processing: Beam Schemas, Rows, Logical Types, Schema Inference, Field Access, and Language Interoperability: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter17/Lesson3.html

Planned04

Schemas and Row-Oriented Processing: Beam Schemas, Rows, Logical Types, Schema Inference, Field Access, and Language Interoperability: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter17/Lesson4.html

Planned05

Checkpoint Lab — Schemas and Row-Oriented Processing: Beam Schemas, Rows, Logical Types, Schema Inference, Field Access, and Language Interoperability: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter17/Lesson5.html

Planned

Chapter 18

Beam SQL: Tables, Schemas, SQL Transforms, Windowed SQL, UDFs/UDAFs, Planner Boundaries, and SQL-vs-SDK Tradeoffs

5 lessons

Beam SQL: Tables, Schemas, SQL Transforms, Windowed SQL, UDFs/UDAFs, Planner Boundaries, and SQL-vs-SDK Tradeoffs: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter18/Lesson1.html

Planned02

Beam SQL: Tables, Schemas, SQL Transforms, Windowed SQL, UDFs/UDAFs, Planner Boundaries, and SQL-vs-SDK Tradeoffs: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter18/Lesson2.html

Planned03

Beam SQL: Tables, Schemas, SQL Transforms, Windowed SQL, UDFs/UDAFs, Planner Boundaries, and SQL-vs-SDK Tradeoffs: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter18/Lesson3.html

Planned04

Beam SQL: Tables, Schemas, SQL Transforms, Windowed SQL, UDFs/UDAFs, Planner Boundaries, and SQL-vs-SDK Tradeoffs: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter18/Lesson4.html

Planned05

Checkpoint Lab — Beam SQL: Tables, Schemas, SQL Transforms, Windowed SQL, UDFs/UDAFs, Planner Boundaries, and SQL-vs-SDK Tradeoffs: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter18/Lesson5.html

Planned

Chapter 19

Files and Object Storage I/O: Text/CSV/JSON, Avro, Parquet, FileIO, Dynamic Destinations, S3/GCS/Azure Concepts, and Small-File Control

5 lessons

Files and Object Storage I/O: Text/CSV/JSON, Avro, Parquet, FileIO, Dynamic Destinations, S3/GCS/Azure Concepts, and Small-File Control: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter19/Lesson1.html

Planned02

Files and Object Storage I/O: Text/CSV/JSON, Avro, Parquet, FileIO, Dynamic Destinations, S3/GCS/Azure Concepts, and Small-File Control: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter19/Lesson2.html

Planned03

Files and Object Storage I/O: Text/CSV/JSON, Avro, Parquet, FileIO, Dynamic Destinations, S3/GCS/Azure Concepts, and Small-File Control: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter19/Lesson3.html

Planned04

Files and Object Storage I/O: Text/CSV/JSON, Avro, Parquet, FileIO, Dynamic Destinations, S3/GCS/Azure Concepts, and Small-File Control: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter19/Lesson4.html

Planned05

Checkpoint Lab — Files and Object Storage I/O: Text/CSV/JSON, Avro, Parquet, FileIO, Dynamic Destinations, S3/GCS/Azure Concepts, and Small-File Control: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter19/Lesson5.html

Planned

Chapter 20

Lakehouse I/O: Iceberg, Delta Lake, Table Metadata, Partitioning, Schema Evolution, Sort/Distribution Controls, and Commit Semantics

5 lessons

Lakehouse I/O: Iceberg, Delta Lake, Table Metadata, Partitioning, Schema Evolution, Sort/Distribution Controls, and Commit Semantics: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter20/Lesson1.html

Planned02

Lakehouse I/O: Iceberg, Delta Lake, Table Metadata, Partitioning, Schema Evolution, Sort/Distribution Controls, and Commit Semantics: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter20/Lesson2.html

Planned03

Lakehouse I/O: Iceberg, Delta Lake, Table Metadata, Partitioning, Schema Evolution, Sort/Distribution Controls, and Commit Semantics: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter20/Lesson3.html

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Lakehouse I/O: Iceberg, Delta Lake, Table Metadata, Partitioning, Schema Evolution, Sort/Distribution Controls, and Commit Semantics: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter20/Lesson4.html

Planned05

Checkpoint Lab — Lakehouse I/O: Iceberg, Delta Lake, Table Metadata, Partitioning, Schema Evolution, Sort/Distribution Controls, and Commit Semantics: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter20/Lesson5.html

Planned

Chapter 21

Messaging and Streaming I/O: Kafka, Pub/Sub Concepts, Kinesis/Pulsar Awareness, Offset/Checkpoint Semantics, Backlog, and Delivery Guarantees

5 lessons

Messaging and Streaming I/O: Kafka, Pub/Sub Concepts, Kinesis/Pulsar Awareness, Offset/Checkpoint Semantics, Backlog, and Delivery Guarantees: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter21/Lesson1.html

Planned02

Messaging and Streaming I/O: Kafka, Pub/Sub Concepts, Kinesis/Pulsar Awareness, Offset/Checkpoint Semantics, Backlog, and Delivery Guarantees: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter21/Lesson2.html

Planned03

Messaging and Streaming I/O: Kafka, Pub/Sub Concepts, Kinesis/Pulsar Awareness, Offset/Checkpoint Semantics, Backlog, and Delivery Guarantees: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter21/Lesson3.html

Planned04

Messaging and Streaming I/O: Kafka, Pub/Sub Concepts, Kinesis/Pulsar Awareness, Offset/Checkpoint Semantics, Backlog, and Delivery Guarantees: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter21/Lesson4.html

Planned05

Checkpoint Lab — Messaging and Streaming I/O: Kafka, Pub/Sub Concepts, Kinesis/Pulsar Awareness, Offset/Checkpoint Semantics, Backlog, and Delivery Guarantees: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter21/Lesson5.html

Planned

Chapter 22

Databases and External Services: JDBC, BigQuery-Style Warehouses, Change Streams, API Enrichment, Async Patterns, Rate Limits, and Idempotency

5 lessons

Databases and External Services: JDBC, BigQuery-Style Warehouses, Change Streams, API Enrichment, Async Patterns, Rate Limits, and Idempotency: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter22/Lesson1.html

Planned02

Databases and External Services: JDBC, BigQuery-Style Warehouses, Change Streams, API Enrichment, Async Patterns, Rate Limits, and Idempotency: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter22/Lesson2.html

Planned03

Databases and External Services: JDBC, BigQuery-Style Warehouses, Change Streams, API Enrichment, Async Patterns, Rate Limits, and Idempotency: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter22/Lesson3.html

Planned04

Databases and External Services: JDBC, BigQuery-Style Warehouses, Change Streams, API Enrichment, Async Patterns, Rate Limits, and Idempotency: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter22/Lesson4.html

Planned05

Checkpoint Lab — Databases and External Services: JDBC, BigQuery-Style Warehouses, Change Streams, API Enrichment, Async Patterns, Rate Limits, and Idempotency: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter22/Lesson5.html

Planned

Chapter 23

Cross-Language Transforms: Expansion Services, Artifact Staging, Type Translation, Java/Python/Go Interop, Versioning, and Debugging

5 lessons

Cross-Language Transforms: Expansion Services, Artifact Staging, Type Translation, Java/Python/Go Interop, Versioning, and Debugging: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter23/Lesson1.html

Planned02

Cross-Language Transforms: Expansion Services, Artifact Staging, Type Translation, Java/Python/Go Interop, Versioning, and Debugging: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter23/Lesson2.html

Planned03

Cross-Language Transforms: Expansion Services, Artifact Staging, Type Translation, Java/Python/Go Interop, Versioning, and Debugging: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter23/Lesson3.html

Planned04

Cross-Language Transforms: Expansion Services, Artifact Staging, Type Translation, Java/Python/Go Interop, Versioning, and Debugging: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter23/Lesson4.html

Planned05

Checkpoint Lab — Cross-Language Transforms: Expansion Services, Artifact Staging, Type Translation, Java/Python/Go Interop, Versioning, and Debugging: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter23/Lesson5.html

Planned

Chapter 24

Portability Architecture: Runner API, Fn API, SDK Harnesses, Environments, Containers, Artifact Retrieval, and Portable Execution

5 lessons

Portability Architecture: Runner API, Fn API, SDK Harnesses, Environments, Containers, Artifact Retrieval, and Portable Execution: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter24/Lesson1.html

Planned02

Portability Architecture: Runner API, Fn API, SDK Harnesses, Environments, Containers, Artifact Retrieval, and Portable Execution: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter24/Lesson2.html

Planned03

Portability Architecture: Runner API, Fn API, SDK Harnesses, Environments, Containers, Artifact Retrieval, and Portable Execution: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter24/Lesson3.html

Planned04

Portability Architecture: Runner API, Fn API, SDK Harnesses, Environments, Containers, Artifact Retrieval, and Portable Execution: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter24/Lesson4.html

Planned05

Checkpoint Lab — Portability Architecture: Runner API, Fn API, SDK Harnesses, Environments, Containers, Artifact Retrieval, and Portable Execution: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter24/Lesson5.html

Planned

Chapter 25

Runner Comparison: DirectRunner, Flink Runner, Spark Runner, Dataflow Portable Runner, Capability Matrices, and Semantic Gaps

5 lessons

Runner Comparison: DirectRunner, Flink Runner, Spark Runner, Dataflow Portable Runner, Capability Matrices, and Semantic Gaps: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter25/Lesson1.html

Planned02

Runner Comparison: DirectRunner, Flink Runner, Spark Runner, Dataflow Portable Runner, Capability Matrices, and Semantic Gaps: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter25/Lesson2.html

Planned03

Runner Comparison: DirectRunner, Flink Runner, Spark Runner, Dataflow Portable Runner, Capability Matrices, and Semantic Gaps: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter25/Lesson3.html

Planned04

Runner Comparison: DirectRunner, Flink Runner, Spark Runner, Dataflow Portable Runner, Capability Matrices, and Semantic Gaps: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter25/Lesson4.html

Planned05

Checkpoint Lab — Runner Comparison: DirectRunner, Flink Runner, Spark Runner, Dataflow Portable Runner, Capability Matrices, and Semantic Gaps: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter25/Lesson5.html

Planned

Chapter 26

Performance Engineering: Fusion, Parallelism, Bundle Sizing, Serialization, Hot Keys, Shuffle, Memory, Autoscaling, and Throughput/Latency Tradeoffs

5 lessons

Performance Engineering: Fusion, Parallelism, Bundle Sizing, Serialization, Hot Keys, Shuffle, Memory, Autoscaling, and Throughput/Latency Tradeoffs: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter26/Lesson1.html

Planned02

Performance Engineering: Fusion, Parallelism, Bundle Sizing, Serialization, Hot Keys, Shuffle, Memory, Autoscaling, and Throughput/Latency Tradeoffs: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter26/Lesson2.html

Planned03

Performance Engineering: Fusion, Parallelism, Bundle Sizing, Serialization, Hot Keys, Shuffle, Memory, Autoscaling, and Throughput/Latency Tradeoffs: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter26/Lesson3.html

Planned04

Performance Engineering: Fusion, Parallelism, Bundle Sizing, Serialization, Hot Keys, Shuffle, Memory, Autoscaling, and Throughput/Latency Tradeoffs: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter26/Lesson4.html

Planned05

Checkpoint Lab — Performance Engineering: Fusion, Parallelism, Bundle Sizing, Serialization, Hot Keys, Shuffle, Memory, Autoscaling, and Throughput/Latency Tradeoffs: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter26/Lesson5.html

Planned

Chapter 27

Reliability and Side Effects: Retries, At-Least-Once Effects, Idempotency, Exactly-Once Claims, Deduplication, Transactions, and Sink Design

5 lessons

Reliability and Side Effects: Retries, At-Least-Once Effects, Idempotency, Exactly-Once Claims, Deduplication, Transactions, and Sink Design: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter27/Lesson1.html

Planned02

Reliability and Side Effects: Retries, At-Least-Once Effects, Idempotency, Exactly-Once Claims, Deduplication, Transactions, and Sink Design: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter27/Lesson2.html

Planned03

Reliability and Side Effects: Retries, At-Least-Once Effects, Idempotency, Exactly-Once Claims, Deduplication, Transactions, and Sink Design: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter27/Lesson3.html

Planned04

Reliability and Side Effects: Retries, At-Least-Once Effects, Idempotency, Exactly-Once Claims, Deduplication, Transactions, and Sink Design: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter27/Lesson4.html

Planned05

Checkpoint Lab — Reliability and Side Effects: Retries, At-Least-Once Effects, Idempotency, Exactly-Once Claims, Deduplication, Transactions, and Sink Design: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter27/Lesson5.html

Planned

Chapter 28

Testing Beam Pipelines: TestPipeline, PAssert, Synthetic Sources, Window/Trigger Tests, State/Timer Tests, Property Tests, and Golden Data

5 lessons

Testing Beam Pipelines: TestPipeline, PAssert, Synthetic Sources, Window/Trigger Tests, State/Timer Tests, Property Tests, and Golden Data: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter28/Lesson1.html

Planned02

Testing Beam Pipelines: TestPipeline, PAssert, Synthetic Sources, Window/Trigger Tests, State/Timer Tests, Property Tests, and Golden Data: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter28/Lesson2.html

Planned03

Testing Beam Pipelines: TestPipeline, PAssert, Synthetic Sources, Window/Trigger Tests, State/Timer Tests, Property Tests, and Golden Data: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter28/Lesson3.html

Planned04

Testing Beam Pipelines: TestPipeline, PAssert, Synthetic Sources, Window/Trigger Tests, State/Timer Tests, Property Tests, and Golden Data: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter28/Lesson4.html

Planned05

Checkpoint Lab — Testing Beam Pipelines: TestPipeline, PAssert, Synthetic Sources, Window/Trigger Tests, State/Timer Tests, Property Tests, and Golden Data: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter28/Lesson5.html

Planned

Chapter 29

Observability: Beam Metrics, Runner Metrics, Logs, Traces, Backlog, Watermarks, Bundle Timing, Memory Profiling, and Operational Dashboards

5 lessons

Observability: Beam Metrics, Runner Metrics, Logs, Traces, Backlog, Watermarks, Bundle Timing, Memory Profiling, and Operational Dashboards: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter29/Lesson1.html

Planned02

Observability: Beam Metrics, Runner Metrics, Logs, Traces, Backlog, Watermarks, Bundle Timing, Memory Profiling, and Operational Dashboards: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter29/Lesson2.html

Planned03

Observability: Beam Metrics, Runner Metrics, Logs, Traces, Backlog, Watermarks, Bundle Timing, Memory Profiling, and Operational Dashboards: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter29/Lesson3.html

Planned04

Observability: Beam Metrics, Runner Metrics, Logs, Traces, Backlog, Watermarks, Bundle Timing, Memory Profiling, and Operational Dashboards: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter29/Lesson4.html

Planned05

Checkpoint Lab — Observability: Beam Metrics, Runner Metrics, Logs, Traces, Backlog, Watermarks, Bundle Timing, Memory Profiling, and Operational Dashboards: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter29/Lesson5.html

Planned

Chapter 30

Security and Supply Chain: Credentials, Secret Injection, IAM Boundaries, TLS, Container Images, Dependency Pinning, Artifact Integrity, and Least Privilege

5 lessons

Security and Supply Chain: Credentials, Secret Injection, IAM Boundaries, TLS, Container Images, Dependency Pinning, Artifact Integrity, and Least Privilege: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter30/Lesson1.html

Planned02

Security and Supply Chain: Credentials, Secret Injection, IAM Boundaries, TLS, Container Images, Dependency Pinning, Artifact Integrity, and Least Privilege: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter30/Lesson2.html

Planned03

Security and Supply Chain: Credentials, Secret Injection, IAM Boundaries, TLS, Container Images, Dependency Pinning, Artifact Integrity, and Least Privilege: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter30/Lesson3.html

Planned04

Security and Supply Chain: Credentials, Secret Injection, IAM Boundaries, TLS, Container Images, Dependency Pinning, Artifact Integrity, and Least Privilege: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter30/Lesson4.html

Planned05

Checkpoint Lab — Security and Supply Chain: Credentials, Secret Injection, IAM Boundaries, TLS, Container Images, Dependency Pinning, Artifact Integrity, and Least Privilege: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter30/Lesson5.html

Planned

Chapter 31

Deployment and CI/CD: Parameterization, Templates, Containers, Artifact Registries, Environment Promotion, Canary Pipelines, and Rollback Patterns

5 lessons

Deployment and CI/CD: Parameterization, Templates, Containers, Artifact Registries, Environment Promotion, Canary Pipelines, and Rollback Patterns: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter31/Lesson1.html

Planned02

Deployment and CI/CD: Parameterization, Templates, Containers, Artifact Registries, Environment Promotion, Canary Pipelines, and Rollback Patterns: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter31/Lesson2.html

Planned03

Deployment and CI/CD: Parameterization, Templates, Containers, Artifact Registries, Environment Promotion, Canary Pipelines, and Rollback Patterns: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter31/Lesson3.html

Planned04

Deployment and CI/CD: Parameterization, Templates, Containers, Artifact Registries, Environment Promotion, Canary Pipelines, and Rollback Patterns: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter31/Lesson4.html

Planned05

Checkpoint Lab — Deployment and CI/CD: Parameterization, Templates, Containers, Artifact Registries, Environment Promotion, Canary Pipelines, and Rollback Patterns: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter31/Lesson5.html

Planned

Chapter 32

Upgrades and Compatibility: Beam Release Cadence, SDK/Runner Compatibility, Deprecated APIs, Connector Evolution, Savepoint/State Concerns, and Regression Gates

5 lessons

Upgrades and Compatibility: Beam Release Cadence, SDK/Runner Compatibility, Deprecated APIs, Connector Evolution, Savepoint/State Concerns, and Regression Gates: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter32/Lesson1.html

Planned02

Upgrades and Compatibility: Beam Release Cadence, SDK/Runner Compatibility, Deprecated APIs, Connector Evolution, Savepoint/State Concerns, and Regression Gates: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter32/Lesson2.html

Planned03

Upgrades and Compatibility: Beam Release Cadence, SDK/Runner Compatibility, Deprecated APIs, Connector Evolution, Savepoint/State Concerns, and Regression Gates: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter32/Lesson3.html

Planned04

Upgrades and Compatibility: Beam Release Cadence, SDK/Runner Compatibility, Deprecated APIs, Connector Evolution, Savepoint/State Concerns, and Regression Gates: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter32/Lesson4.html

Planned05

Checkpoint Lab — Upgrades and Compatibility: Beam Release Cadence, SDK/Runner Compatibility, Deprecated APIs, Connector Evolution, Savepoint/State Concerns, and Regression Gates: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter32/Lesson5.html

Planned

Chapter 33

Architecture Patterns: ETL/ELT, Streaming Enrichment, CDC, Session Analytics, Fanout, Backfills, Reprocessing, Lambda/Kappa Tradeoffs, and Multi-Runner Design

5 lessons

Architecture Patterns: ETL/ELT, Streaming Enrichment, CDC, Session Analytics, Fanout, Backfills, Reprocessing, Lambda/Kappa Tradeoffs, and Multi-Runner Design: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter33/Lesson1.html

Planned02

Architecture Patterns: ETL/ELT, Streaming Enrichment, CDC, Session Analytics, Fanout, Backfills, Reprocessing, Lambda/Kappa Tradeoffs, and Multi-Runner Design: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter33/Lesson2.html

Planned03

Architecture Patterns: ETL/ELT, Streaming Enrichment, CDC, Session Analytics, Fanout, Backfills, Reprocessing, Lambda/Kappa Tradeoffs, and Multi-Runner Design: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter33/Lesson3.html

Planned04

Architecture Patterns: ETL/ELT, Streaming Enrichment, CDC, Session Analytics, Fanout, Backfills, Reprocessing, Lambda/Kappa Tradeoffs, and Multi-Runner Design: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter33/Lesson4.html

Planned05

Checkpoint Lab — Architecture Patterns: ETL/ELT, Streaming Enrichment, CDC, Session Analytics, Fanout, Backfills, Reprocessing, Lambda/Kappa Tradeoffs, and Multi-Runner Design: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter33/Lesson5.html

Planned

Chapter 34

Production Capstone: Build, Test, Window, State, Stream, Benchmark, Port, Secure, Observe, Fail, Recover, and Upgrade a Beam 2.75 Pipeline

5 lessons

Production Capstone: Build, Test, Window, State, Stream, Benchmark, Port, Secure, Observe, Fail, Recover, and Upgrade a Beam 2.75 Pipeline: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter34/Lesson1.html

Planned02

Production Capstone: Build, Test, Window, State, Stream, Benchmark, Port, Secure, Observe, Fail, Recover, and Upgrade a Beam 2.75 Pipeline: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter34/Lesson2.html

Planned03

Production Capstone: Build, Test, Window, State, Stream, Benchmark, Port, Secure, Observe, Fail, Recover, and Upgrade a Beam 2.75 Pipeline: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter34/Lesson3.html

Planned04

Production Capstone: Build, Test, Window, State, Stream, Benchmark, Port, Secure, Observe, Fail, Recover, and Upgrade a Beam 2.75 Pipeline: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter34/Lesson4.html

Planned05

Checkpoint Lab — Production Capstone: Build, Test, Window, State, Stream, Benchmark, Port, Secure, Observe, Fail, Recover, and Upgrade a Beam 2.75 Pipeline: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter34/Lesson5.html

Planned