Curriculum planned

Stage 08 · Event Streaming & Real-Time Processing

Apache Flink

A comprehensive Apache Flink course covering stateful stream processing, event time, watermarks, windows, keyed/operator state, checkpointing, savepoints, exactly-once design, DataStream and DataStream V2, Table API and Flink SQL, changelogs, connectors, PyFlink, materialized tables, deployment, HA, security, observability, performance tuning, upgrades, and production streaming architecture.

Browse planned curriculum Back to all courses

38planned chapters

190reserved lesson paths

Advancedlearning level

Plannedcourse state

Coverage baselineApache Flink 2.3.0 baseline (released June 25, 2026) with DataStream and DataStream V2 APIs, Flink SQL/Table API, relational changelogs, materialized tables, state/checkpointing, native S3 filesystem, adaptive scheduling/partitioning, application lifecycle management, and production observability

Course brief

Build stateful streaming systems by treating time, state, checkpoints, backpressure, changelogs, and deployment lifecycle as first-class correctness concerns—then validate recovery and exactly-once behavior under real failures rather than relying on API labels.

A comprehensive Apache Flink course covering stateful stream processing, event time, watermarks, windows, keyed/operator state, checkpointing, savepoints, exactly-once design, DataStream and DataStream V2, Table API and Flink SQL, changelogs, connectors, PyFlink, materialized tables, deployment, HA, security, observability, performance tuning, upgrades, and production streaming architecture.

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

Implement event-time DataStream pipelines with watermarks, windows, state, timers, async I/O, checkpoints, savepoints, and explicit late-data behavior
Write Flink SQL/Table API applications using dynamic tables, changelog streams, temporal joins, windows, materialized tables, connectors, and schema-aware formats
Explain JobManager/TaskManager architecture, slots, chaining, network exchange, state backends, checkpoint barriers, backpressure, schedulers, and recovery behavior
Deploy highly available Flink applications on Kubernetes/standalone environments with object-storage state, security, observability, adaptive scheduling, and application lifecycle controls
Tune and upgrade production jobs using metrics, checkpoints/savepoints, compatibility planning, performance baselines, failure injection, and stateful migration 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

Flink Foundations: Stateful Stream Processing, Bounded vs Unbounded Data, Flink 2.3, Workload Fit, and Local Lab Setup

5 lessons

01

Flink Foundations: Stateful Stream Processing, Bounded vs Unbounded Data, Flink 2.3, Workload Fit, and Local Lab Setup: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter01/Lesson1.html

Planned02

Flink Foundations: Stateful Stream Processing, Bounded vs Unbounded Data, Flink 2.3, Workload Fit, and Local Lab Setup: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter01/Lesson2.html

Planned03

Flink Foundations: Stateful Stream Processing, Bounded vs Unbounded Data, Flink 2.3, Workload Fit, and Local Lab Setup: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter01/Lesson3.html

Planned04

Flink Foundations: Stateful Stream Processing, Bounded vs Unbounded Data, Flink 2.3, Workload Fit, and Local Lab Setup: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter01/Lesson4.html

Planned05

Checkpoint Lab — Flink Foundations: Stateful Stream Processing, Bounded vs Unbounded Data, Flink 2.3, Workload Fit, and Local Lab Setup: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter01/Lesson5.html

Planned

02

Chapter 2

Runtime Architecture: JobManager, TaskManagers, Dispatcher, ResourceManager, JobMaster, Slots, Operators, Subtasks, and Failure Domains

5 lessons

01

Runtime Architecture: JobManager, TaskManagers, Dispatcher, ResourceManager, JobMaster, Slots, Operators, Subtasks, and Failure Domains: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter02/Lesson1.html

Planned02

Runtime Architecture: JobManager, TaskManagers, Dispatcher, ResourceManager, JobMaster, Slots, Operators, Subtasks, and Failure Domains: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter02/Lesson2.html

Planned03

Runtime Architecture: JobManager, TaskManagers, Dispatcher, ResourceManager, JobMaster, Slots, Operators, Subtasks, and Failure Domains: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter02/Lesson3.html

Planned04

Runtime Architecture: JobManager, TaskManagers, Dispatcher, ResourceManager, JobMaster, Slots, Operators, Subtasks, and Failure Domains: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter02/Lesson4.html

Planned05

Checkpoint Lab — Runtime Architecture: JobManager, TaskManagers, Dispatcher, ResourceManager, JobMaster, Slots, Operators, Subtasks, and Failure Domains: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter02/Lesson5.html

Planned

03

Chapter 3

Dataflow Execution: Job Graphs, Execution Graphs, Parallelism, Max Parallelism, Operator Chaining, Key Groups, Network Exchanges, and Serialization

5 lessons

01

Dataflow Execution: Job Graphs, Execution Graphs, Parallelism, Max Parallelism, Operator Chaining, Key Groups, Network Exchanges, and Serialization: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter03/Lesson1.html

Planned02

Dataflow Execution: Job Graphs, Execution Graphs, Parallelism, Max Parallelism, Operator Chaining, Key Groups, Network Exchanges, and Serialization: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter03/Lesson2.html

Planned03

Dataflow Execution: Job Graphs, Execution Graphs, Parallelism, Max Parallelism, Operator Chaining, Key Groups, Network Exchanges, and Serialization: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter03/Lesson3.html

Planned04

Dataflow Execution: Job Graphs, Execution Graphs, Parallelism, Max Parallelism, Operator Chaining, Key Groups, Network Exchanges, and Serialization: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter03/Lesson4.html

Planned05

Checkpoint Lab — Dataflow Execution: Job Graphs, Execution Graphs, Parallelism, Max Parallelism, Operator Chaining, Key Groups, Network Exchanges, and Serialization: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter03/Lesson5.html

Planned

04

Chapter 4

Event Time and Watermarks: Processing/Ingestion/Event Time, Watermark Strategies, Idleness, Alignment, Timestamp Assignment, and Out-of-Order Data

5 lessons

01

Event Time and Watermarks: Processing/Ingestion/Event Time, Watermark Strategies, Idleness, Alignment, Timestamp Assignment, and Out-of-Order Data: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter04/Lesson1.html

Planned02

Event Time and Watermarks: Processing/Ingestion/Event Time, Watermark Strategies, Idleness, Alignment, Timestamp Assignment, and Out-of-Order Data: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter04/Lesson2.html

Planned03

Event Time and Watermarks: Processing/Ingestion/Event Time, Watermark Strategies, Idleness, Alignment, Timestamp Assignment, and Out-of-Order Data: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter04/Lesson3.html

Planned04

Event Time and Watermarks: Processing/Ingestion/Event Time, Watermark Strategies, Idleness, Alignment, Timestamp Assignment, and Out-of-Order Data: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter04/Lesson4.html

Planned05

Checkpoint Lab — Event Time and Watermarks: Processing/Ingestion/Event Time, Watermark Strategies, Idleness, Alignment, Timestamp Assignment, and Out-of-Order Data: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter04/Lesson5.html

Planned

05

Chapter 5

Windows: Tumbling, Sliding, Session, Global, Keyed/Non-Keyed Windows, Window Functions, Incremental Aggregation, and Lifecycle

5 lessons

01

Windows: Tumbling, Sliding, Session, Global, Keyed/Non-Keyed Windows, Window Functions, Incremental Aggregation, and Lifecycle: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter05/Lesson1.html

Planned02

Windows: Tumbling, Sliding, Session, Global, Keyed/Non-Keyed Windows, Window Functions, Incremental Aggregation, and Lifecycle: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter05/Lesson2.html

Planned03

Windows: Tumbling, Sliding, Session, Global, Keyed/Non-Keyed Windows, Window Functions, Incremental Aggregation, and Lifecycle: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter05/Lesson3.html

Planned04

Windows: Tumbling, Sliding, Session, Global, Keyed/Non-Keyed Windows, Window Functions, Incremental Aggregation, and Lifecycle: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter05/Lesson4.html

Planned05

Checkpoint Lab — Windows: Tumbling, Sliding, Session, Global, Keyed/Non-Keyed Windows, Window Functions, Incremental Aggregation, and Lifecycle: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter05/Lesson5.html

Planned

06

Chapter 6

Triggers, Evictors, Allowed Lateness, Side Outputs, and Late Data: Correctness, Memory, Cleanup, and Operational Tradeoffs

5 lessons

01

Triggers, Evictors, Allowed Lateness, Side Outputs, and Late Data: Correctness, Memory, Cleanup, and Operational Tradeoffs: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter06/Lesson1.html

Planned02

Triggers, Evictors, Allowed Lateness, Side Outputs, and Late Data: Correctness, Memory, Cleanup, and Operational Tradeoffs: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter06/Lesson2.html

Planned03

Triggers, Evictors, Allowed Lateness, Side Outputs, and Late Data: Correctness, Memory, Cleanup, and Operational Tradeoffs: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter06/Lesson3.html

Planned04

Triggers, Evictors, Allowed Lateness, Side Outputs, and Late Data: Correctness, Memory, Cleanup, and Operational Tradeoffs: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter06/Lesson4.html

Planned05

Checkpoint Lab — Triggers, Evictors, Allowed Lateness, Side Outputs, and Late Data: Correctness, Memory, Cleanup, and Operational Tradeoffs: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter06/Lesson5.html

Planned

07

Chapter 7

State Fundamentals: Keyed State, Operator State, Broadcast State, Managed vs Raw State, TTL, Serialization, and State Scope

5 lessons

01

State Fundamentals: Keyed State, Operator State, Broadcast State, Managed vs Raw State, TTL, Serialization, and State Scope: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter07/Lesson1.html

Planned02

State Fundamentals: Keyed State, Operator State, Broadcast State, Managed vs Raw State, TTL, Serialization, and State Scope: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter07/Lesson2.html

Planned03

State Fundamentals: Keyed State, Operator State, Broadcast State, Managed vs Raw State, TTL, Serialization, and State Scope: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter07/Lesson3.html

Planned04

State Fundamentals: Keyed State, Operator State, Broadcast State, Managed vs Raw State, TTL, Serialization, and State Scope: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter07/Lesson4.html

Planned05

Checkpoint Lab — State Fundamentals: Keyed State, Operator State, Broadcast State, Managed vs Raw State, TTL, Serialization, and State Scope: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter07/Lesson5.html

Planned

08

Chapter 8

State Backends and Storage: Heap, RocksDB/EmbeddedRocksDB, ForSt-Style Disaggregated State Concepts, Checkpoint Storage, Object Storage, and Tradeoffs

5 lessons

01

State Backends and Storage: Heap, RocksDB/EmbeddedRocksDB, ForSt-Style Disaggregated State Concepts, Checkpoint Storage, Object Storage, and Tradeoffs: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter08/Lesson1.html

Planned02

State Backends and Storage: Heap, RocksDB/EmbeddedRocksDB, ForSt-Style Disaggregated State Concepts, Checkpoint Storage, Object Storage, and Tradeoffs: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter08/Lesson2.html

Planned03

State Backends and Storage: Heap, RocksDB/EmbeddedRocksDB, ForSt-Style Disaggregated State Concepts, Checkpoint Storage, Object Storage, and Tradeoffs: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter08/Lesson3.html

Planned04

State Backends and Storage: Heap, RocksDB/EmbeddedRocksDB, ForSt-Style Disaggregated State Concepts, Checkpoint Storage, Object Storage, and Tradeoffs: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter08/Lesson4.html

Planned05

Checkpoint Lab — State Backends and Storage: Heap, RocksDB/EmbeddedRocksDB, ForSt-Style Disaggregated State Concepts, Checkpoint Storage, Object Storage, and Tradeoffs: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter08/Lesson5.html

Planned

09

Chapter 9

Checkpointing Internals: Barriers, Alignment, Unaligned Checkpoints, Incremental State, Checkpoint Coordination, Timeouts, and Failure Diagnosis

5 lessons

01

Checkpointing Internals: Barriers, Alignment, Unaligned Checkpoints, Incremental State, Checkpoint Coordination, Timeouts, and Failure Diagnosis: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter09/Lesson1.html

Planned02

Checkpointing Internals: Barriers, Alignment, Unaligned Checkpoints, Incremental State, Checkpoint Coordination, Timeouts, and Failure Diagnosis: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter09/Lesson2.html

Planned03

Checkpointing Internals: Barriers, Alignment, Unaligned Checkpoints, Incremental State, Checkpoint Coordination, Timeouts, and Failure Diagnosis: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter09/Lesson3.html

Planned04

Checkpointing Internals: Barriers, Alignment, Unaligned Checkpoints, Incremental State, Checkpoint Coordination, Timeouts, and Failure Diagnosis: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter09/Lesson4.html

Planned05

Checkpoint Lab — Checkpointing Internals: Barriers, Alignment, Unaligned Checkpoints, Incremental State, Checkpoint Coordination, Timeouts, and Failure Diagnosis: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter09/Lesson5.html

Planned

10

Chapter 10

Savepoints and Stateful Upgrades: Operator UIDs, State Mapping, Rescaling, Schema Evolution, Compatibility, Restore Modes, and Migration Discipline

5 lessons

01

Savepoints and Stateful Upgrades: Operator UIDs, State Mapping, Rescaling, Schema Evolution, Compatibility, Restore Modes, and Migration Discipline: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter10/Lesson1.html

Planned02

Savepoints and Stateful Upgrades: Operator UIDs, State Mapping, Rescaling, Schema Evolution, Compatibility, Restore Modes, and Migration Discipline: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter10/Lesson2.html

Planned03

Savepoints and Stateful Upgrades: Operator UIDs, State Mapping, Rescaling, Schema Evolution, Compatibility, Restore Modes, and Migration Discipline: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter10/Lesson3.html

Planned04

Savepoints and Stateful Upgrades: Operator UIDs, State Mapping, Rescaling, Schema Evolution, Compatibility, Restore Modes, and Migration Discipline: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter10/Lesson4.html

Planned05

Checkpoint Lab — Savepoints and Stateful Upgrades: Operator UIDs, State Mapping, Rescaling, Schema Evolution, Compatibility, Restore Modes, and Migration Discipline: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter10/Lesson5.html

Planned

11

Chapter 11

Exactly-Once Processing: Source Positions, Checkpoints, Two-Phase/Transactional Sinks, Idempotent Sinks, External Side Effects, and Semantic Boundaries

5 lessons

01

Exactly-Once Processing: Source Positions, Checkpoints, Two-Phase/Transactional Sinks, Idempotent Sinks, External Side Effects, and Semantic Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter11/Lesson1.html

Planned02

Exactly-Once Processing: Source Positions, Checkpoints, Two-Phase/Transactional Sinks, Idempotent Sinks, External Side Effects, and Semantic Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter11/Lesson2.html

Planned03

Exactly-Once Processing: Source Positions, Checkpoints, Two-Phase/Transactional Sinks, Idempotent Sinks, External Side Effects, and Semantic Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter11/Lesson3.html

Planned04

Exactly-Once Processing: Source Positions, Checkpoints, Two-Phase/Transactional Sinks, Idempotent Sinks, External Side Effects, and Semantic Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter11/Lesson4.html

Planned05

Checkpoint Lab — Exactly-Once Processing: Source Positions, Checkpoints, Two-Phase/Transactional Sinks, Idempotent Sinks, External Side Effects, and Semantic Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter11/Lesson5.html

Planned

12

Chapter 12

Failure Recovery: Restart Strategies, Failover Regions, Checkpoint Recovery, Local Recovery, Partial Failures, and Recovery-Time Engineering

5 lessons

01

Failure Recovery: Restart Strategies, Failover Regions, Checkpoint Recovery, Local Recovery, Partial Failures, and Recovery-Time Engineering: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter12/Lesson1.html

Planned02

Failure Recovery: Restart Strategies, Failover Regions, Checkpoint Recovery, Local Recovery, Partial Failures, and Recovery-Time Engineering: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter12/Lesson2.html

Planned03

Failure Recovery: Restart Strategies, Failover Regions, Checkpoint Recovery, Local Recovery, Partial Failures, and Recovery-Time Engineering: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter12/Lesson3.html

Planned04

Failure Recovery: Restart Strategies, Failover Regions, Checkpoint Recovery, Local Recovery, Partial Failures, and Recovery-Time Engineering: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter12/Lesson4.html

Planned05

Checkpoint Lab — Failure Recovery: Restart Strategies, Failover Regions, Checkpoint Recovery, Local Recovery, Partial Failures, and Recovery-Time Engineering: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter12/Lesson5.html

Planned

13

Chapter 13

Backpressure and Network Flow: Buffers, Credit-Based Flow Control, Busy/Idle/Backpressured Time, Skew, Throughput Collapse, and Diagnosis

5 lessons

01

Backpressure and Network Flow: Buffers, Credit-Based Flow Control, Busy/Idle/Backpressured Time, Skew, Throughput Collapse, and Diagnosis: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter13/Lesson1.html

Planned02

Backpressure and Network Flow: Buffers, Credit-Based Flow Control, Busy/Idle/Backpressured Time, Skew, Throughput Collapse, and Diagnosis: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter13/Lesson2.html

Planned03

Backpressure and Network Flow: Buffers, Credit-Based Flow Control, Busy/Idle/Backpressured Time, Skew, Throughput Collapse, and Diagnosis: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter13/Lesson3.html

Planned04

Backpressure and Network Flow: Buffers, Credit-Based Flow Control, Busy/Idle/Backpressured Time, Skew, Throughput Collapse, and Diagnosis: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter13/Lesson4.html

Planned05

Checkpoint Lab — Backpressure and Network Flow: Buffers, Credit-Based Flow Control, Busy/Idle/Backpressured Time, Skew, Throughput Collapse, and Diagnosis: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter13/Lesson5.html

Planned

14

Chapter 14

DataStream API Foundations: Sources, Transformations, Keys, Sinks, Rich Functions, Side Outputs, Union/Connect, Partitioning, and Type Information

5 lessons

01

DataStream API Foundations: Sources, Transformations, Keys, Sinks, Rich Functions, Side Outputs, Union/Connect, Partitioning, and Type Information: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter14/Lesson1.html

Planned02

DataStream API Foundations: Sources, Transformations, Keys, Sinks, Rich Functions, Side Outputs, Union/Connect, Partitioning, and Type Information: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter14/Lesson2.html

Planned03

DataStream API Foundations: Sources, Transformations, Keys, Sinks, Rich Functions, Side Outputs, Union/Connect, Partitioning, and Type Information: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter14/Lesson3.html

Planned04

DataStream API Foundations: Sources, Transformations, Keys, Sinks, Rich Functions, Side Outputs, Union/Connect, Partitioning, and Type Information: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter14/Lesson4.html

Planned05

Checkpoint Lab — DataStream API Foundations: Sources, Transformations, Keys, Sinks, Rich Functions, Side Outputs, Union/Connect, Partitioning, and Type Information: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter14/Lesson5.html

Planned

15

Chapter 15

DataStream API V2: Modern API Concepts, Process Functions, State/Timers Boundaries, Migration Considerations, and When to Adopt It

5 lessons

01

DataStream API V2: Modern API Concepts, Process Functions, State/Timers Boundaries, Migration Considerations, and When to Adopt It: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter15/Lesson1.html

Planned02

DataStream API V2: Modern API Concepts, Process Functions, State/Timers Boundaries, Migration Considerations, and When to Adopt It: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter15/Lesson2.html

Planned03

DataStream API V2: Modern API Concepts, Process Functions, State/Timers Boundaries, Migration Considerations, and When to Adopt It: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter15/Lesson3.html

Planned04

DataStream API V2: Modern API Concepts, Process Functions, State/Timers Boundaries, Migration Considerations, and When to Adopt It: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter15/Lesson4.html

Planned05

Checkpoint Lab — DataStream API V2: Modern API Concepts, Process Functions, State/Timers Boundaries, Migration Considerations, and When to Adopt It: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter15/Lesson5.html

Planned

16

Chapter 16

Process Functions, Timers, and Async I/O: KeyedProcessFunction, Event/Processing-Time Timers, Asynchronous Enrichment, Ordering, and Timeout Handling

5 lessons

01

Process Functions, Timers, and Async I/O: KeyedProcessFunction, Event/Processing-Time Timers, Asynchronous Enrichment, Ordering, and Timeout Handling: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter16/Lesson1.html

Planned02

Process Functions, Timers, and Async I/O: KeyedProcessFunction, Event/Processing-Time Timers, Asynchronous Enrichment, Ordering, and Timeout Handling: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter16/Lesson2.html

Planned03

Process Functions, Timers, and Async I/O: KeyedProcessFunction, Event/Processing-Time Timers, Asynchronous Enrichment, Ordering, and Timeout Handling: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter16/Lesson3.html

Planned04

Process Functions, Timers, and Async I/O: KeyedProcessFunction, Event/Processing-Time Timers, Asynchronous Enrichment, Ordering, and Timeout Handling: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter16/Lesson4.html

Planned05

Checkpoint Lab — Process Functions, Timers, and Async I/O: KeyedProcessFunction, Event/Processing-Time Timers, Asynchronous Enrichment, Ordering, and Timeout Handling: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter16/Lesson5.html

Planned

17

Chapter 17

Complex Event Processing: CEP Patterns, Contiguity, Quantifiers, Time Constraints, Pattern State, After-Match Skip Strategies, and Use Cases

5 lessons

01

Complex Event Processing: CEP Patterns, Contiguity, Quantifiers, Time Constraints, Pattern State, After-Match Skip Strategies, and Use Cases: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter17/Lesson1.html

Planned02

Complex Event Processing: CEP Patterns, Contiguity, Quantifiers, Time Constraints, Pattern State, After-Match Skip Strategies, and Use Cases: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter17/Lesson2.html

Planned03

Complex Event Processing: CEP Patterns, Contiguity, Quantifiers, Time Constraints, Pattern State, After-Match Skip Strategies, and Use Cases: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter17/Lesson3.html

Planned04

Complex Event Processing: CEP Patterns, Contiguity, Quantifiers, Time Constraints, Pattern State, After-Match Skip Strategies, and Use Cases: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter17/Lesson4.html

Planned05

Checkpoint Lab — Complex Event Processing: CEP Patterns, Contiguity, Quantifiers, Time Constraints, Pattern State, After-Match Skip Strategies, and Use Cases: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter17/Lesson5.html

Planned

18

Chapter 18

Table API Foundations: TableEnvironment, Schemas, Expressions, Catalogs, Temporary/Permanent Objects, DDL/DML, and API/SQL Interoperability

5 lessons

01

Table API Foundations: TableEnvironment, Schemas, Expressions, Catalogs, Temporary/Permanent Objects, DDL/DML, and API/SQL Interoperability: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter18/Lesson1.html

Planned02

Table API Foundations: TableEnvironment, Schemas, Expressions, Catalogs, Temporary/Permanent Objects, DDL/DML, and API/SQL Interoperability: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter18/Lesson2.html

Planned03

Table API Foundations: TableEnvironment, Schemas, Expressions, Catalogs, Temporary/Permanent Objects, DDL/DML, and API/SQL Interoperability: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter18/Lesson3.html

Planned04

Table API Foundations: TableEnvironment, Schemas, Expressions, Catalogs, Temporary/Permanent Objects, DDL/DML, and API/SQL Interoperability: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter18/Lesson4.html

Planned05

Checkpoint Lab — Table API Foundations: TableEnvironment, Schemas, Expressions, Catalogs, Temporary/Permanent Objects, DDL/DML, and API/SQL Interoperability: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter18/Lesson5.html

Planned

19

Chapter 19

Flink SQL and Dynamic Tables: Changelog Semantics, Append/Update/Retract/Upsert Streams, Primary Keys, Planner Mental Model, and Relational Streaming

5 lessons

01

Flink SQL and Dynamic Tables: Changelog Semantics, Append/Update/Retract/Upsert Streams, Primary Keys, Planner Mental Model, and Relational Streaming: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter19/Lesson1.html

Planned02

Flink SQL and Dynamic Tables: Changelog Semantics, Append/Update/Retract/Upsert Streams, Primary Keys, Planner Mental Model, and Relational Streaming: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter19/Lesson2.html

Planned03

Flink SQL and Dynamic Tables: Changelog Semantics, Append/Update/Retract/Upsert Streams, Primary Keys, Planner Mental Model, and Relational Streaming: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter19/Lesson3.html

Planned04

Flink SQL and Dynamic Tables: Changelog Semantics, Append/Update/Retract/Upsert Streams, Primary Keys, Planner Mental Model, and Relational Streaming: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter19/Lesson4.html

Planned05

Checkpoint Lab — Flink SQL and Dynamic Tables: Changelog Semantics, Append/Update/Retract/Upsert Streams, Primary Keys, Planner Mental Model, and Relational Streaming: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter19/Lesson5.html

Planned

20

Chapter 20

Streaming SQL Windows and Joins: Window TVFs, Interval Joins, Regular Joins, Temporal Joins, Lookup Joins, Over Windows, and State Cost

5 lessons

01

Streaming SQL Windows and Joins: Window TVFs, Interval Joins, Regular Joins, Temporal Joins, Lookup Joins, Over Windows, and State Cost: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter20/Lesson1.html

Planned02

Streaming SQL Windows and Joins: Window TVFs, Interval Joins, Regular Joins, Temporal Joins, Lookup Joins, Over Windows, and State Cost: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter20/Lesson2.html

Planned03

Streaming SQL Windows and Joins: Window TVFs, Interval Joins, Regular Joins, Temporal Joins, Lookup Joins, Over Windows, and State Cost: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter20/Lesson3.html

Planned04

Streaming SQL Windows and Joins: Window TVFs, Interval Joins, Regular Joins, Temporal Joins, Lookup Joins, Over Windows, and State Cost: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter20/Lesson4.html

Planned05

Checkpoint Lab — Streaming SQL Windows and Joins: Window TVFs, Interval Joins, Regular Joins, Temporal Joins, Lookup Joins, Over Windows, and State Cost: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter20/Lesson5.html

Planned

21

Chapter 21

Process Table Functions and Advanced SQL: PTFs, MATCH_RECOGNIZE, Table Functions, UDFs/UDAFs, Changelog Conversion, and Custom Logic Boundaries

5 lessons

01

Process Table Functions and Advanced SQL: PTFs, MATCH_RECOGNIZE, Table Functions, UDFs/UDAFs, Changelog Conversion, and Custom Logic Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter21/Lesson1.html

Planned02

Process Table Functions and Advanced SQL: PTFs, MATCH_RECOGNIZE, Table Functions, UDFs/UDAFs, Changelog Conversion, and Custom Logic Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter21/Lesson2.html

Planned03

Process Table Functions and Advanced SQL: PTFs, MATCH_RECOGNIZE, Table Functions, UDFs/UDAFs, Changelog Conversion, and Custom Logic Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter21/Lesson3.html

Planned04

Process Table Functions and Advanced SQL: PTFs, MATCH_RECOGNIZE, Table Functions, UDFs/UDAFs, Changelog Conversion, and Custom Logic Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter21/Lesson4.html

Planned05

Checkpoint Lab — Process Table Functions and Advanced SQL: PTFs, MATCH_RECOGNIZE, Table Functions, UDFs/UDAFs, Changelog Conversion, and Custom Logic Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter21/Lesson5.html

Planned

22

Chapter 22

FROM_CHANGELOG and TO_CHANGELOG: CDC-Style Operation Columns, Append/Upsert Conversion, Conflict Handling Concepts, and Audit/Archive Pipelines

5 lessons

01

FROM_CHANGELOG and TO_CHANGELOG: CDC-Style Operation Columns, Append/Upsert Conversion, Conflict Handling Concepts, and Audit/Archive Pipelines: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter22/Lesson1.html

Planned02

FROM_CHANGELOG and TO_CHANGELOG: CDC-Style Operation Columns, Append/Upsert Conversion, Conflict Handling Concepts, and Audit/Archive Pipelines: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter22/Lesson2.html

Planned03

FROM_CHANGELOG and TO_CHANGELOG: CDC-Style Operation Columns, Append/Upsert Conversion, Conflict Handling Concepts, and Audit/Archive Pipelines: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter22/Lesson3.html

Planned04

FROM_CHANGELOG and TO_CHANGELOG: CDC-Style Operation Columns, Append/Upsert Conversion, Conflict Handling Concepts, and Audit/Archive Pipelines: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter22/Lesson4.html

Planned05

Checkpoint Lab — FROM_CHANGELOG and TO_CHANGELOG: CDC-Style Operation Columns, Append/Upsert Conversion, Conflict Handling Concepts, and Audit/Archive Pipelines: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter22/Lesson5.html

Planned

23

Chapter 23

Connectors: Kafka, Files, JDBC, Data Lakes, Search Systems, Sources/Sinks, Delivery Guarantees, Discovery, and Connector Version Compatibility

5 lessons

01

Connectors: Kafka, Files, JDBC, Data Lakes, Search Systems, Sources/Sinks, Delivery Guarantees, Discovery, and Connector Version Compatibility: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter23/Lesson1.html

Planned02

Connectors: Kafka, Files, JDBC, Data Lakes, Search Systems, Sources/Sinks, Delivery Guarantees, Discovery, and Connector Version Compatibility: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter23/Lesson2.html

Planned03

Connectors: Kafka, Files, JDBC, Data Lakes, Search Systems, Sources/Sinks, Delivery Guarantees, Discovery, and Connector Version Compatibility: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter23/Lesson3.html

Planned04

Connectors: Kafka, Files, JDBC, Data Lakes, Search Systems, Sources/Sinks, Delivery Guarantees, Discovery, and Connector Version Compatibility: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter23/Lesson4.html

Planned05

Checkpoint Lab — Connectors: Kafka, Files, JDBC, Data Lakes, Search Systems, Sources/Sinks, Delivery Guarantees, Discovery, and Connector Version Compatibility: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter23/Lesson5.html

Planned

24

Chapter 24

Formats and Schema Integration: JSON, CSV, Avro, Protobuf, Parquet, Debezium/Canal Changelogs, Metadata Columns, and Schema Evolution

5 lessons

01

Formats and Schema Integration: JSON, CSV, Avro, Protobuf, Parquet, Debezium/Canal Changelogs, Metadata Columns, and Schema Evolution: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter24/Lesson1.html

Planned02

Formats and Schema Integration: JSON, CSV, Avro, Protobuf, Parquet, Debezium/Canal Changelogs, Metadata Columns, and Schema Evolution: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter24/Lesson2.html

Planned03

Formats and Schema Integration: JSON, CSV, Avro, Protobuf, Parquet, Debezium/Canal Changelogs, Metadata Columns, and Schema Evolution: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter24/Lesson3.html

Planned04

Formats and Schema Integration: JSON, CSV, Avro, Protobuf, Parquet, Debezium/Canal Changelogs, Metadata Columns, and Schema Evolution: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter24/Lesson4.html

Planned05

Checkpoint Lab — Formats and Schema Integration: JSON, CSV, Avro, Protobuf, Parquet, Debezium/Canal Changelogs, Metadata Columns, and Schema Evolution: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter24/Lesson5.html

Planned

25

Chapter 25

Materialized Tables: Declarative Continuous Refresh, Freshness, Evolution, Start Modes, Refresh Strategy, and Operational Lifecycle

5 lessons

01

Materialized Tables: Declarative Continuous Refresh, Freshness, Evolution, Start Modes, Refresh Strategy, and Operational Lifecycle: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter25/Lesson1.html

Planned02

Materialized Tables: Declarative Continuous Refresh, Freshness, Evolution, Start Modes, Refresh Strategy, and Operational Lifecycle: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter25/Lesson2.html

Planned03

Materialized Tables: Declarative Continuous Refresh, Freshness, Evolution, Start Modes, Refresh Strategy, and Operational Lifecycle: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter25/Lesson3.html

Planned04

Materialized Tables: Declarative Continuous Refresh, Freshness, Evolution, Start Modes, Refresh Strategy, and Operational Lifecycle: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter25/Lesson4.html

Planned05

Checkpoint Lab — Materialized Tables: Declarative Continuous Refresh, Freshness, Evolution, Start Modes, Refresh Strategy, and Operational Lifecycle: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter25/Lesson5.html

Planned

26

Chapter 26

PyFlink: Python DataStream/Table APIs, Environment Setup, Dependencies, UDF Execution, Cross-Language Boundaries, Packaging, and Performance

5 lessons

01

PyFlink: Python DataStream/Table APIs, Environment Setup, Dependencies, UDF Execution, Cross-Language Boundaries, Packaging, and Performance: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter26/Lesson1.html

Planned02

PyFlink: Python DataStream/Table APIs, Environment Setup, Dependencies, UDF Execution, Cross-Language Boundaries, Packaging, and Performance: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter26/Lesson2.html

Planned03

PyFlink: Python DataStream/Table APIs, Environment Setup, Dependencies, UDF Execution, Cross-Language Boundaries, Packaging, and Performance: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter26/Lesson3.html

Planned04

PyFlink: Python DataStream/Table APIs, Environment Setup, Dependencies, UDF Execution, Cross-Language Boundaries, Packaging, and Performance: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter26/Lesson4.html

Planned05

Checkpoint Lab — PyFlink: Python DataStream/Table APIs, Environment Setup, Dependencies, UDF Execution, Cross-Language Boundaries, Packaging, and Performance: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter26/Lesson5.html

Planned

27

Chapter 27

AI/ML and Vector-Aware SQL Concepts: Model DDLs, ML_PREDICT, Embeddings, VECTOR_SEARCH Evolution, External Model Services, and Streaming AI Boundaries

5 lessons

01

AI/ML and Vector-Aware SQL Concepts: Model DDLs, ML_PREDICT, Embeddings, VECTOR_SEARCH Evolution, External Model Services, and Streaming AI Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter27/Lesson1.html

Planned02

AI/ML and Vector-Aware SQL Concepts: Model DDLs, ML_PREDICT, Embeddings, VECTOR_SEARCH Evolution, External Model Services, and Streaming AI Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter27/Lesson2.html

Planned03

AI/ML and Vector-Aware SQL Concepts: Model DDLs, ML_PREDICT, Embeddings, VECTOR_SEARCH Evolution, External Model Services, and Streaming AI Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter27/Lesson3.html

Planned04

AI/ML and Vector-Aware SQL Concepts: Model DDLs, ML_PREDICT, Embeddings, VECTOR_SEARCH Evolution, External Model Services, and Streaming AI Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter27/Lesson4.html

Planned05

Checkpoint Lab — AI/ML and Vector-Aware SQL Concepts: Model DDLs, ML_PREDICT, Embeddings, VECTOR_SEARCH Evolution, External Model Services, and Streaming AI Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter27/Lesson5.html

Planned

28

Chapter 28

Batch Processing in Flink: Bounded Execution, Batch Runtime Optimizations, Sort/Hash Operators, Shuffle, Adaptive Batch Scheduling, and Resource Use

5 lessons

01

Batch Processing in Flink: Bounded Execution, Batch Runtime Optimizations, Sort/Hash Operators, Shuffle, Adaptive Batch Scheduling, and Resource Use: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter28/Lesson1.html

Planned02

Batch Processing in Flink: Bounded Execution, Batch Runtime Optimizations, Sort/Hash Operators, Shuffle, Adaptive Batch Scheduling, and Resource Use: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter28/Lesson2.html

Planned03

Batch Processing in Flink: Bounded Execution, Batch Runtime Optimizations, Sort/Hash Operators, Shuffle, Adaptive Batch Scheduling, and Resource Use: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter28/Lesson3.html

Planned04

Batch Processing in Flink: Bounded Execution, Batch Runtime Optimizations, Sort/Hash Operators, Shuffle, Adaptive Batch Scheduling, and Resource Use: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter28/Lesson4.html

Planned05

Checkpoint Lab — Batch Processing in Flink: Bounded Execution, Batch Runtime Optimizations, Sort/Hash Operators, Shuffle, Adaptive Batch Scheduling, and Resource Use: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter28/Lesson5.html

Planned

29

Chapter 29

Planner and SQL Performance: Statistics, Join Strategy, Mini-Batch Aggregation, State TTL, Two-Phase Aggregation, Operator Fusion, and Plan Inspection

5 lessons

01

Planner and SQL Performance: Statistics, Join Strategy, Mini-Batch Aggregation, State TTL, Two-Phase Aggregation, Operator Fusion, and Plan Inspection: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter29/Lesson1.html

Planned02

Planner and SQL Performance: Statistics, Join Strategy, Mini-Batch Aggregation, State TTL, Two-Phase Aggregation, Operator Fusion, and Plan Inspection: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter29/Lesson2.html

Planned03

Planner and SQL Performance: Statistics, Join Strategy, Mini-Batch Aggregation, State TTL, Two-Phase Aggregation, Operator Fusion, and Plan Inspection: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter29/Lesson3.html

Planned04

Planner and SQL Performance: Statistics, Join Strategy, Mini-Batch Aggregation, State TTL, Two-Phase Aggregation, Operator Fusion, and Plan Inspection: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter29/Lesson4.html

Planned05

Checkpoint Lab — Planner and SQL Performance: Statistics, Join Strategy, Mini-Batch Aggregation, State TTL, Two-Phase Aggregation, Operator Fusion, and Plan Inspection: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter29/Lesson5.html

Planned

30

Chapter 30

Resource Management and Scheduling: Slots, Slot Sharing, Reactive/Adaptive Scheduling, Adaptive Partition Selection, Rescaling, and Resource Profiles

5 lessons

01

Resource Management and Scheduling: Slots, Slot Sharing, Reactive/Adaptive Scheduling, Adaptive Partition Selection, Rescaling, and Resource Profiles: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter30/Lesson1.html

Planned02

Resource Management and Scheduling: Slots, Slot Sharing, Reactive/Adaptive Scheduling, Adaptive Partition Selection, Rescaling, and Resource Profiles: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter30/Lesson2.html

Planned03

Resource Management and Scheduling: Slots, Slot Sharing, Reactive/Adaptive Scheduling, Adaptive Partition Selection, Rescaling, and Resource Profiles: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter30/Lesson3.html

Planned04

Resource Management and Scheduling: Slots, Slot Sharing, Reactive/Adaptive Scheduling, Adaptive Partition Selection, Rescaling, and Resource Profiles: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter30/Lesson4.html

Planned05

Checkpoint Lab — Resource Management and Scheduling: Slots, Slot Sharing, Reactive/Adaptive Scheduling, Adaptive Partition Selection, Rescaling, and Resource Profiles: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter30/Lesson5.html

Planned

31

Chapter 31

Deployment Modes: Application vs Session, Standalone, Kubernetes, Native K8s, Packaging, Artifacts, Dependencies, Classloading, and Job Submission

5 lessons

01

Deployment Modes: Application vs Session, Standalone, Kubernetes, Native K8s, Packaging, Artifacts, Dependencies, Classloading, and Job Submission: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter31/Lesson1.html

Planned02

Deployment Modes: Application vs Session, Standalone, Kubernetes, Native K8s, Packaging, Artifacts, Dependencies, Classloading, and Job Submission: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter31/Lesson2.html

Planned03

Deployment Modes: Application vs Session, Standalone, Kubernetes, Native K8s, Packaging, Artifacts, Dependencies, Classloading, and Job Submission: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter31/Lesson3.html

Planned04

Deployment Modes: Application vs Session, Standalone, Kubernetes, Native K8s, Packaging, Artifacts, Dependencies, Classloading, and Job Submission: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter31/Lesson4.html

Planned05

Checkpoint Lab — Deployment Modes: Application vs Session, Standalone, Kubernetes, Native K8s, Packaging, Artifacts, Dependencies, Classloading, and Job Submission: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter31/Lesson5.html

Planned

32

Chapter 32

High Availability and Durable State: HA Metadata, Kubernetes/ZooKeeper Concepts, Checkpoint/Savepoint Storage, Native S3 Filesystem, and Disaster-Recovery Boundaries

5 lessons

01

High Availability and Durable State: HA Metadata, Kubernetes/ZooKeeper Concepts, Checkpoint/Savepoint Storage, Native S3 Filesystem, and Disaster-Recovery Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter32/Lesson1.html

Planned02

High Availability and Durable State: HA Metadata, Kubernetes/ZooKeeper Concepts, Checkpoint/Savepoint Storage, Native S3 Filesystem, and Disaster-Recovery Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter32/Lesson2.html

Planned03

High Availability and Durable State: HA Metadata, Kubernetes/ZooKeeper Concepts, Checkpoint/Savepoint Storage, Native S3 Filesystem, and Disaster-Recovery Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter32/Lesson3.html

Planned04

High Availability and Durable State: HA Metadata, Kubernetes/ZooKeeper Concepts, Checkpoint/Savepoint Storage, Native S3 Filesystem, and Disaster-Recovery Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter32/Lesson4.html

Planned05

Checkpoint Lab — High Availability and Durable State: HA Metadata, Kubernetes/ZooKeeper Concepts, Checkpoint/Savepoint Storage, Native S3 Filesystem, and Disaster-Recovery Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter32/Lesson5.html

Planned

33

Chapter 33

Security: TLS, Authentication/Authorization Boundaries, Secrets, Hadoop/Kerberos Context, Kubernetes Service Accounts, REST/UI Exposure, and Least Privilege

5 lessons

01

Security: TLS, Authentication/Authorization Boundaries, Secrets, Hadoop/Kerberos Context, Kubernetes Service Accounts, REST/UI Exposure, and Least Privilege: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter33/Lesson1.html

Planned02

Security: TLS, Authentication/Authorization Boundaries, Secrets, Hadoop/Kerberos Context, Kubernetes Service Accounts, REST/UI Exposure, and Least Privilege: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter33/Lesson2.html

Planned03

Security: TLS, Authentication/Authorization Boundaries, Secrets, Hadoop/Kerberos Context, Kubernetes Service Accounts, REST/UI Exposure, and Least Privilege: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter33/Lesson3.html

Planned04

Security: TLS, Authentication/Authorization Boundaries, Secrets, Hadoop/Kerberos Context, Kubernetes Service Accounts, REST/UI Exposure, and Least Privilege: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter33/Lesson4.html

Planned05

Checkpoint Lab — Security: TLS, Authentication/Authorization Boundaries, Secrets, Hadoop/Kerberos Context, Kubernetes Service Accounts, REST/UI Exposure, and Least Privilege: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter33/Lesson5.html

Planned

34

Chapter 34

Observability: Web UI, REST API, Metrics, OpenTelemetry, Logs, Backpressure Views, Checkpoint Stats, Rescale History, Flame Graphs, and Alerting

5 lessons

01

Observability: Web UI, REST API, Metrics, OpenTelemetry, Logs, Backpressure Views, Checkpoint Stats, Rescale History, Flame Graphs, and Alerting: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter34/Lesson1.html

Planned02

Observability: Web UI, REST API, Metrics, OpenTelemetry, Logs, Backpressure Views, Checkpoint Stats, Rescale History, Flame Graphs, and Alerting: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter34/Lesson2.html

Planned03

Observability: Web UI, REST API, Metrics, OpenTelemetry, Logs, Backpressure Views, Checkpoint Stats, Rescale History, Flame Graphs, and Alerting: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter34/Lesson3.html

Planned04

Observability: Web UI, REST API, Metrics, OpenTelemetry, Logs, Backpressure Views, Checkpoint Stats, Rescale History, Flame Graphs, and Alerting: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter34/Lesson4.html

Planned05

Checkpoint Lab — Observability: Web UI, REST API, Metrics, OpenTelemetry, Logs, Backpressure Views, Checkpoint Stats, Rescale History, Flame Graphs, and Alerting: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter34/Lesson5.html

Planned

35

Chapter 35

Performance Engineering: Parallelism, Key Distribution, Serialization, Network Buffers, RocksDB/ForSt Tuning, Checkpoint Cost, GC, State Size, and Benchmarking

5 lessons

01

Performance Engineering: Parallelism, Key Distribution, Serialization, Network Buffers, RocksDB/ForSt Tuning, Checkpoint Cost, GC, State Size, and Benchmarking: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter35/Lesson1.html

Planned02

Performance Engineering: Parallelism, Key Distribution, Serialization, Network Buffers, RocksDB/ForSt Tuning, Checkpoint Cost, GC, State Size, and Benchmarking: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter35/Lesson2.html

Planned03

Performance Engineering: Parallelism, Key Distribution, Serialization, Network Buffers, RocksDB/ForSt Tuning, Checkpoint Cost, GC, State Size, and Benchmarking: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter35/Lesson3.html

Planned04

Performance Engineering: Parallelism, Key Distribution, Serialization, Network Buffers, RocksDB/ForSt Tuning, Checkpoint Cost, GC, State Size, and Benchmarking: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter35/Lesson4.html

Planned05

Checkpoint Lab — Performance Engineering: Parallelism, Key Distribution, Serialization, Network Buffers, RocksDB/ForSt Tuning, Checkpoint Cost, GC, State Size, and Benchmarking: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter35/Lesson5.html

Planned

36

Chapter 36

Testing and Validation: MiniCluster, Unit/Integration Tests, Test Harness Concepts, Deterministic Time, Savepoint Tests, Fault Injection, and End-to-End Assertions

5 lessons

01

Testing and Validation: MiniCluster, Unit/Integration Tests, Test Harness Concepts, Deterministic Time, Savepoint Tests, Fault Injection, and End-to-End Assertions: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter36/Lesson1.html

Planned02

Testing and Validation: MiniCluster, Unit/Integration Tests, Test Harness Concepts, Deterministic Time, Savepoint Tests, Fault Injection, and End-to-End Assertions: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter36/Lesson2.html

Planned03

Testing and Validation: MiniCluster, Unit/Integration Tests, Test Harness Concepts, Deterministic Time, Savepoint Tests, Fault Injection, and End-to-End Assertions: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter36/Lesson3.html

Planned04

Testing and Validation: MiniCluster, Unit/Integration Tests, Test Harness Concepts, Deterministic Time, Savepoint Tests, Fault Injection, and End-to-End Assertions: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter36/Lesson4.html

Planned05

Checkpoint Lab — Testing and Validation: MiniCluster, Unit/Integration Tests, Test Harness Concepts, Deterministic Time, Savepoint Tests, Fault Injection, and End-to-End Assertions: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter36/Lesson5.html

Planned

37

Chapter 37

Upgrades and Application Lifecycle: Flink 1.20/2.x Migration Concepts, Application Management, Stateful Compatibility, Connector Upgrades, Rollback, and Release Notes

5 lessons

01

Upgrades and Application Lifecycle: Flink 1.20/2.x Migration Concepts, Application Management, Stateful Compatibility, Connector Upgrades, Rollback, and Release Notes: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter37/Lesson1.html

Planned02

Upgrades and Application Lifecycle: Flink 1.20/2.x Migration Concepts, Application Management, Stateful Compatibility, Connector Upgrades, Rollback, and Release Notes: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter37/Lesson2.html

Planned03

Upgrades and Application Lifecycle: Flink 1.20/2.x Migration Concepts, Application Management, Stateful Compatibility, Connector Upgrades, Rollback, and Release Notes: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter37/Lesson3.html

Planned04

Upgrades and Application Lifecycle: Flink 1.20/2.x Migration Concepts, Application Management, Stateful Compatibility, Connector Upgrades, Rollback, and Release Notes: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter37/Lesson4.html

Planned05

Checkpoint Lab — Upgrades and Application Lifecycle: Flink 1.20/2.x Migration Concepts, Application Management, Stateful Compatibility, Connector Upgrades, Rollback, and Release Notes: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter37/Lesson5.html

Planned

38

Chapter 38

Production Capstone: Build, State, Stream-SQL, Secure, Observe, Backpressure, Fail, Recover, Rescale, and Upgrade a Flink 2.3 Real-Time Platform

5 lessons

01

Production Capstone: Build, State, Stream-SQL, Secure, Observe, Backpressure, Fail, Recover, Rescale, and Upgrade a Flink 2.3 Real-Time Platform: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter38/Lesson1.html

Planned02

Production Capstone: Build, State, Stream-SQL, Secure, Observe, Backpressure, Fail, Recover, Rescale, and Upgrade a Flink 2.3 Real-Time Platform: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter38/Lesson2.html

Planned03

Production Capstone: Build, State, Stream-SQL, Secure, Observe, Backpressure, Fail, Recover, Rescale, and Upgrade a Flink 2.3 Real-Time Platform: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter38/Lesson3.html

Planned04

Production Capstone: Build, State, Stream-SQL, Secure, Observe, Backpressure, Fail, Recover, Rescale, and Upgrade a Flink 2.3 Real-Time Platform: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter38/Lesson4.html

Planned05

Checkpoint Lab — Production Capstone: Build, State, Stream-SQL, Secure, Observe, Backpressure, Fail, Recover, Rescale, and Upgrade a Flink 2.3 Real-Time Platform: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter38/Lesson5.html

Planned