Curriculum planned

Stage 08 · Event Streaming & Real-Time Processing

Apache Storm

A comprehensive Apache Storm course covering topology architecture, spouts and bolts, tuples and stream groupings, parallelism, acknowledgement and reliability, backpressure, Storm 3.0 batching/network changes, stateful processing, Trident, Kafka integration, resource-aware scheduling, security, observability, performance tuning, testing, migration, and maintenance of production Storm systems.

Browse planned curriculum Back to all courses

30planned chapters

150reserved lesson paths

Specializedlearning level

Plannedcourse state

Coverage baselineApache Storm 3.0.0 baseline (released July 22, 2026) with Java 25 runtime requirements, Java API compatibility with 2.x, removal of the Clojure dependency/DSL, Zstd inter-worker and cluster-state compression, AIMD dynamic batching, jitter-aware grouping, scheduler improvements, Trident, security, and production operations

Course brief

Understand and maintain Storm by tracing every tuple through spouts, bolts, stream groupings, executors, ack trees, worker processes, schedulers, and state—then measure where latency, reliability, and resource contention actually arise in long-running topologies.

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 and deploy Storm 3.0 Java topologies using spouts, bolts, stream groupings, parallelism controls, configuration, and safe lifecycle operations
Explain acknowledgement trees, tuple timeouts, replay, at-least-once semantics, backpressure, batching, worker communication, and failure recovery
Use stateful bolts and Trident where appropriate, integrate Kafka and external systems, and design idempotent/transactional persistence boundaries
Operate shared clusters using built-in schedulers, resource-aware scheduling, security, metrics, UI/REST tooling, tuning, and daemon fault tolerance
Assess migration from Storm 2.x to 3.0, modernize or retire legacy topologies, benchmark alternatives, and execute production failure/recovery drills

Complete planned syllabus

30 chapters · 150 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

Storm Foundations: Distributed Real-Time Computation, Topology Model, Storm 3.0, Java 25, Workload Fit, and Local Lab Setup

5 lessons

Storm Foundations: Distributed Real-Time Computation, Topology Model, Storm 3.0, Java 25, Workload Fit, and Local Lab Setup: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter01/Lesson1.html

Planned02

Storm Foundations: Distributed Real-Time Computation, Topology Model, Storm 3.0, Java 25, Workload Fit, and Local Lab Setup: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter01/Lesson2.html

Planned03

Storm Foundations: Distributed Real-Time Computation, Topology Model, Storm 3.0, Java 25, Workload Fit, and Local Lab Setup: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter01/Lesson3.html

Planned04

Storm Foundations: Distributed Real-Time Computation, Topology Model, Storm 3.0, Java 25, Workload Fit, and Local Lab Setup: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter01/Lesson4.html

Planned05

Checkpoint Lab — Storm Foundations: Distributed Real-Time Computation, Topology Model, Storm 3.0, Java 25, Workload Fit, and Local Lab Setup: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter01/Lesson5.html

Planned

Chapter 2

Cluster Architecture: Nimbus, Supervisors, Workers, Executors, Tasks, ZooKeeper/Cluster State, UI, Logviewer, and Failure Boundaries

5 lessons

Cluster Architecture: Nimbus, Supervisors, Workers, Executors, Tasks, ZooKeeper/Cluster State, UI, Logviewer, and Failure Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter02/Lesson1.html

Planned02

Cluster Architecture: Nimbus, Supervisors, Workers, Executors, Tasks, ZooKeeper/Cluster State, UI, Logviewer, and Failure Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter02/Lesson2.html

Planned03

Cluster Architecture: Nimbus, Supervisors, Workers, Executors, Tasks, ZooKeeper/Cluster State, UI, Logviewer, and Failure Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter02/Lesson3.html

Planned04

Cluster Architecture: Nimbus, Supervisors, Workers, Executors, Tasks, ZooKeeper/Cluster State, UI, Logviewer, and Failure Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter02/Lesson4.html

Planned05

Checkpoint Lab — Cluster Architecture: Nimbus, Supervisors, Workers, Executors, Tasks, ZooKeeper/Cluster State, UI, Logviewer, and Failure Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter02/Lesson5.html

Planned

Chapter 3

Topology Development Workflow: Maven/Gradle Packaging, TopologyBuilder, Configuration, Local Testing, Remote Submission, and Artifact Discipline

5 lessons

Topology Development Workflow: Maven/Gradle Packaging, TopologyBuilder, Configuration, Local Testing, Remote Submission, and Artifact Discipline: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter03/Lesson1.html

Planned02

Topology Development Workflow: Maven/Gradle Packaging, TopologyBuilder, Configuration, Local Testing, Remote Submission, and Artifact Discipline: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter03/Lesson2.html

Planned03

Topology Development Workflow: Maven/Gradle Packaging, TopologyBuilder, Configuration, Local Testing, Remote Submission, and Artifact Discipline: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter03/Lesson3.html

Planned04

Topology Development Workflow: Maven/Gradle Packaging, TopologyBuilder, Configuration, Local Testing, Remote Submission, and Artifact Discipline: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter03/Lesson4.html

Planned05

Checkpoint Lab — Topology Development Workflow: Maven/Gradle Packaging, TopologyBuilder, Configuration, Local Testing, Remote Submission, and Artifact Discipline: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter03/Lesson5.html

Planned

Chapter 4

Spouts, Bolts, Tuples, Streams, Fields, Anchoring, Emitting, Declaring Output, and Data-Contract Design

5 lessons

Spouts, Bolts, Tuples, Streams, Fields, Anchoring, Emitting, Declaring Output, and Data-Contract Design: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter04/Lesson1.html

Planned02

Spouts, Bolts, Tuples, Streams, Fields, Anchoring, Emitting, Declaring Output, and Data-Contract Design: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter04/Lesson2.html

Planned03

Spouts, Bolts, Tuples, Streams, Fields, Anchoring, Emitting, Declaring Output, and Data-Contract Design: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter04/Lesson3.html

Planned04

Spouts, Bolts, Tuples, Streams, Fields, Anchoring, Emitting, Declaring Output, and Data-Contract Design: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter04/Lesson4.html

Planned05

Checkpoint Lab — Spouts, Bolts, Tuples, Streams, Fields, Anchoring, Emitting, Declaring Output, and Data-Contract Design: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter04/Lesson5.html

Planned

Chapter 5

Stream Groupings: Shuffle, Fields, Partial-Key, All, Global, None, Direct, Local-or-Shuffle, Custom, and Jitter-Aware Strategies

5 lessons

Stream Groupings: Shuffle, Fields, Partial-Key, All, Global, None, Direct, Local-or-Shuffle, Custom, and Jitter-Aware Strategies: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter05/Lesson1.html

Planned02

Stream Groupings: Shuffle, Fields, Partial-Key, All, Global, None, Direct, Local-or-Shuffle, Custom, and Jitter-Aware Strategies: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter05/Lesson2.html

Planned03

Stream Groupings: Shuffle, Fields, Partial-Key, All, Global, None, Direct, Local-or-Shuffle, Custom, and Jitter-Aware Strategies: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter05/Lesson3.html

Planned04

Stream Groupings: Shuffle, Fields, Partial-Key, All, Global, None, Direct, Local-or-Shuffle, Custom, and Jitter-Aware Strategies: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter05/Lesson4.html

Planned05

Checkpoint Lab — Stream Groupings: Shuffle, Fields, Partial-Key, All, Global, None, Direct, Local-or-Shuffle, Custom, and Jitter-Aware Strategies: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter05/Lesson5.html

Planned

Chapter 6

Parallelism and Scaling: Workers, Executors, Tasks, Component Parallelism Hints, Rebalance, Bottlenecks, and Resource Topology

5 lessons

Parallelism and Scaling: Workers, Executors, Tasks, Component Parallelism Hints, Rebalance, Bottlenecks, and Resource Topology: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter06/Lesson1.html

Planned02

Parallelism and Scaling: Workers, Executors, Tasks, Component Parallelism Hints, Rebalance, Bottlenecks, and Resource Topology: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter06/Lesson2.html

Planned03

Parallelism and Scaling: Workers, Executors, Tasks, Component Parallelism Hints, Rebalance, Bottlenecks, and Resource Topology: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter06/Lesson3.html

Planned04

Parallelism and Scaling: Workers, Executors, Tasks, Component Parallelism Hints, Rebalance, Bottlenecks, and Resource Topology: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter06/Lesson4.html

Planned05

Checkpoint Lab — Parallelism and Scaling: Workers, Executors, Tasks, Component Parallelism Hints, Rebalance, Bottlenecks, and Resource Topology: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter06/Lesson5.html

Planned

Chapter 7

Message Processing Guarantees: Anchoring, Ackers, Ack Trees, XOR Tracking, Tuple Timeouts, Fail/Replay, and At-Least-Once Semantics

5 lessons

Message Processing Guarantees: Anchoring, Ackers, Ack Trees, XOR Tracking, Tuple Timeouts, Fail/Replay, and At-Least-Once Semantics: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter07/Lesson1.html

Planned02

Message Processing Guarantees: Anchoring, Ackers, Ack Trees, XOR Tracking, Tuple Timeouts, Fail/Replay, and At-Least-Once Semantics: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter07/Lesson2.html

Planned03

Message Processing Guarantees: Anchoring, Ackers, Ack Trees, XOR Tracking, Tuple Timeouts, Fail/Replay, and At-Least-Once Semantics: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter07/Lesson3.html

Planned04

Message Processing Guarantees: Anchoring, Ackers, Ack Trees, XOR Tracking, Tuple Timeouts, Fail/Replay, and At-Least-Once Semantics: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter07/Lesson4.html

Planned05

Checkpoint Lab — Message Processing Guarantees: Anchoring, Ackers, Ack Trees, XOR Tracking, Tuple Timeouts, Fail/Replay, and At-Least-Once Semantics: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter07/Lesson5.html

Planned

Chapter 8

Idempotency and External Side Effects: Duplicate Processing, Transaction Keys, Deduplication, Database Writes, Retry Safety, and Honest Guarantees

5 lessons

Idempotency and External Side Effects: Duplicate Processing, Transaction Keys, Deduplication, Database Writes, Retry Safety, and Honest Guarantees: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter08/Lesson1.html

Planned02

Idempotency and External Side Effects: Duplicate Processing, Transaction Keys, Deduplication, Database Writes, Retry Safety, and Honest Guarantees: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter08/Lesson2.html

Planned03

Idempotency and External Side Effects: Duplicate Processing, Transaction Keys, Deduplication, Database Writes, Retry Safety, and Honest Guarantees: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter08/Lesson3.html

Planned04

Idempotency and External Side Effects: Duplicate Processing, Transaction Keys, Deduplication, Database Writes, Retry Safety, and Honest Guarantees: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter08/Lesson4.html

Planned05

Checkpoint Lab — Idempotency and External Side Effects: Duplicate Processing, Transaction Keys, Deduplication, Database Writes, Retry Safety, and Honest Guarantees: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter08/Lesson5.html

Planned

Chapter 9

Topology Lifecycle and CLI Operations: Submit, Kill, Activate, Deactivate, Rebalance, Config, Logs, Classpath, and Deployment Runbooks

5 lessons

Topology Lifecycle and CLI Operations: Submit, Kill, Activate, Deactivate, Rebalance, Config, Logs, Classpath, and Deployment Runbooks: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter09/Lesson1.html

Planned02

Topology Lifecycle and CLI Operations: Submit, Kill, Activate, Deactivate, Rebalance, Config, Logs, Classpath, and Deployment Runbooks: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter09/Lesson2.html

Planned03

Topology Lifecycle and CLI Operations: Submit, Kill, Activate, Deactivate, Rebalance, Config, Logs, Classpath, and Deployment Runbooks: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter09/Lesson3.html

Planned04

Topology Lifecycle and CLI Operations: Submit, Kill, Activate, Deactivate, Rebalance, Config, Logs, Classpath, and Deployment Runbooks: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter09/Lesson4.html

Planned05

Checkpoint Lab — Topology Lifecycle and CLI Operations: Submit, Kill, Activate, Deactivate, Rebalance, Config, Logs, Classpath, and Deployment Runbooks: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter09/Lesson5.html

Planned

Chapter 10

Backpressure and Flow Control: Queue Pressure, Executor Capacity, Producer/Consumer Imbalance, Backpressure Signals, and Throughput Collapse

5 lessons

Backpressure and Flow Control: Queue Pressure, Executor Capacity, Producer/Consumer Imbalance, Backpressure Signals, and Throughput Collapse: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter10/Lesson1.html

Planned02

Backpressure and Flow Control: Queue Pressure, Executor Capacity, Producer/Consumer Imbalance, Backpressure Signals, and Throughput Collapse: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter10/Lesson2.html

Planned03

Backpressure and Flow Control: Queue Pressure, Executor Capacity, Producer/Consumer Imbalance, Backpressure Signals, and Throughput Collapse: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter10/Lesson3.html

Planned04

Backpressure and Flow Control: Queue Pressure, Executor Capacity, Producer/Consumer Imbalance, Backpressure Signals, and Throughput Collapse: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter10/Lesson4.html

Planned05

Checkpoint Lab — Backpressure and Flow Control: Queue Pressure, Executor Capacity, Producer/Consumer Imbalance, Backpressure Signals, and Throughput Collapse: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter10/Lesson5.html

Planned

Chapter 11

Storm 3.0 Network and Batching: Zstd Compression, AIMD Dynamic Batch Sizing, Inter-Worker Transport, Cluster-State Compression, and Tuning Tradeoffs

5 lessons

Storm 3.0 Network and Batching: Zstd Compression, AIMD Dynamic Batch Sizing, Inter-Worker Transport, Cluster-State Compression, and Tuning Tradeoffs: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter11/Lesson1.html

Planned02

Storm 3.0 Network and Batching: Zstd Compression, AIMD Dynamic Batch Sizing, Inter-Worker Transport, Cluster-State Compression, and Tuning Tradeoffs: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter11/Lesson2.html

Planned03

Storm 3.0 Network and Batching: Zstd Compression, AIMD Dynamic Batch Sizing, Inter-Worker Transport, Cluster-State Compression, and Tuning Tradeoffs: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter11/Lesson3.html

Planned04

Storm 3.0 Network and Batching: Zstd Compression, AIMD Dynamic Batch Sizing, Inter-Worker Transport, Cluster-State Compression, and Tuning Tradeoffs: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter11/Lesson4.html

Planned05

Checkpoint Lab — Storm 3.0 Network and Batching: Zstd Compression, AIMD Dynamic Batch Sizing, Inter-Worker Transport, Cluster-State Compression, and Tuning Tradeoffs: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter11/Lesson5.html

Planned

Chapter 12

Stateful Processing: IStatefulBolt, KeyValueState, Checkpointing, Recovery, State Providers, Transaction Boundaries, and Rescaling Constraints

5 lessons

Stateful Processing: IStatefulBolt, KeyValueState, Checkpointing, Recovery, State Providers, Transaction Boundaries, and Rescaling Constraints: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter12/Lesson1.html

Planned02

Stateful Processing: IStatefulBolt, KeyValueState, Checkpointing, Recovery, State Providers, Transaction Boundaries, and Rescaling Constraints: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter12/Lesson2.html

Planned03

Stateful Processing: IStatefulBolt, KeyValueState, Checkpointing, Recovery, State Providers, Transaction Boundaries, and Rescaling Constraints: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter12/Lesson3.html

Planned04

Stateful Processing: IStatefulBolt, KeyValueState, Checkpointing, Recovery, State Providers, Transaction Boundaries, and Rescaling Constraints: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter12/Lesson4.html

Planned05

Checkpoint Lab — Stateful Processing: IStatefulBolt, KeyValueState, Checkpointing, Recovery, State Providers, Transaction Boundaries, and Rescaling Constraints: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter12/Lesson5.html

Planned

Chapter 13

Trident Foundations: Micro-Batch/High-Level Abstractions, Streams, Operations, Partitioning, Persistent State, and When Trident Fits

5 lessons

Trident Foundations: Micro-Batch/High-Level Abstractions, Streams, Operations, Partitioning, Persistent State, and When Trident Fits: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter13/Lesson1.html

Planned02

Trident Foundations: Micro-Batch/High-Level Abstractions, Streams, Operations, Partitioning, Persistent State, and When Trident Fits: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter13/Lesson2.html

Planned03

Trident Foundations: Micro-Batch/High-Level Abstractions, Streams, Operations, Partitioning, Persistent State, and When Trident Fits: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter13/Lesson3.html

Planned04

Trident Foundations: Micro-Batch/High-Level Abstractions, Streams, Operations, Partitioning, Persistent State, and When Trident Fits: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter13/Lesson4.html

Planned05

Checkpoint Lab — Trident Foundations: Micro-Batch/High-Level Abstractions, Streams, Operations, Partitioning, Persistent State, and When Trident Fits: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter13/Lesson5.html

Planned

Chapter 14

Trident State and Exactly-Once Patterns: Transactional/Opaque State, State Updates, Replays, Idempotency, Persistence, and Semantic Limitations

5 lessons

Trident State and Exactly-Once Patterns: Transactional/Opaque State, State Updates, Replays, Idempotency, Persistence, and Semantic Limitations: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter14/Lesson1.html

Planned02

Trident State and Exactly-Once Patterns: Transactional/Opaque State, State Updates, Replays, Idempotency, Persistence, and Semantic Limitations: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter14/Lesson2.html

Planned03

Trident State and Exactly-Once Patterns: Transactional/Opaque State, State Updates, Replays, Idempotency, Persistence, and Semantic Limitations: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter14/Lesson3.html

Planned04

Trident State and Exactly-Once Patterns: Transactional/Opaque State, State Updates, Replays, Idempotency, Persistence, and Semantic Limitations: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter14/Lesson4.html

Planned05

Checkpoint Lab — Trident State and Exactly-Once Patterns: Transactional/Opaque State, State Updates, Replays, Idempotency, Persistence, and Semantic Limitations: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter14/Lesson5.html

Planned

Chapter 15

Windowing and Aggregation: Sliding/Tumbling Windows, Count/Time Windows, Timestamp Fields, Lag, Expiration, Triggers, and Stateful Analytics

5 lessons

Windowing and Aggregation: Sliding/Tumbling Windows, Count/Time Windows, Timestamp Fields, Lag, Expiration, Triggers, and Stateful Analytics: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter15/Lesson1.html

Planned02

Windowing and Aggregation: Sliding/Tumbling Windows, Count/Time Windows, Timestamp Fields, Lag, Expiration, Triggers, and Stateful Analytics: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter15/Lesson2.html

Planned03

Windowing and Aggregation: Sliding/Tumbling Windows, Count/Time Windows, Timestamp Fields, Lag, Expiration, Triggers, and Stateful Analytics: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter15/Lesson3.html

Planned04

Windowing and Aggregation: Sliding/Tumbling Windows, Count/Time Windows, Timestamp Fields, Lag, Expiration, Triggers, and Stateful Analytics: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter15/Lesson4.html

Planned05

Checkpoint Lab — Windowing and Aggregation: Sliding/Tumbling Windows, Count/Time Windows, Timestamp Fields, Lag, Expiration, Triggers, and Stateful Analytics: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter15/Lesson5.html

Planned

Chapter 16

Time, Ordering, and Late Events: Source Timestamps, Processing Delays, Window Semantics, Partition Ordering, Replays, and Event-Time Limitations

5 lessons

Time, Ordering, and Late Events: Source Timestamps, Processing Delays, Window Semantics, Partition Ordering, Replays, and Event-Time Limitations: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter16/Lesson1.html

Planned02

Time, Ordering, and Late Events: Source Timestamps, Processing Delays, Window Semantics, Partition Ordering, Replays, and Event-Time Limitations: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter16/Lesson2.html

Planned03

Time, Ordering, and Late Events: Source Timestamps, Processing Delays, Window Semantics, Partition Ordering, Replays, and Event-Time Limitations: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter16/Lesson3.html

Planned04

Time, Ordering, and Late Events: Source Timestamps, Processing Delays, Window Semantics, Partition Ordering, Replays, and Event-Time Limitations: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter16/Lesson4.html

Planned05

Checkpoint Lab — Time, Ordering, and Late Events: Source Timestamps, Processing Delays, Window Semantics, Partition Ordering, Replays, and Event-Time Limitations: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter16/Lesson5.html

Planned

Chapter 17

Kafka Integration: KafkaSpout Concepts, Consumer Groups, Offset Commit/Replay, Partition Assignment, Delivery Semantics, and Backpressure Interactions

5 lessons

Kafka Integration: KafkaSpout Concepts, Consumer Groups, Offset Commit/Replay, Partition Assignment, Delivery Semantics, and Backpressure Interactions: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter17/Lesson1.html

Planned02

Kafka Integration: KafkaSpout Concepts, Consumer Groups, Offset Commit/Replay, Partition Assignment, Delivery Semantics, and Backpressure Interactions: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter17/Lesson2.html

Planned03

Kafka Integration: KafkaSpout Concepts, Consumer Groups, Offset Commit/Replay, Partition Assignment, Delivery Semantics, and Backpressure Interactions: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter17/Lesson3.html

Planned04

Kafka Integration: KafkaSpout Concepts, Consumer Groups, Offset Commit/Replay, Partition Assignment, Delivery Semantics, and Backpressure Interactions: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter17/Lesson4.html

Planned05

Checkpoint Lab — Kafka Integration: KafkaSpout Concepts, Consumer Groups, Offset Commit/Replay, Partition Assignment, Delivery Semantics, and Backpressure Interactions: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter17/Lesson5.html

Planned

Chapter 18

External Systems and Sinks: JDBC, HBase/Redis/Search/Object Storage Patterns, Async Calls, Batching, Timeouts, Retries, and Circuit-Breaker Design

5 lessons

External Systems and Sinks: JDBC, HBase/Redis/Search/Object Storage Patterns, Async Calls, Batching, Timeouts, Retries, and Circuit-Breaker Design: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter18/Lesson1.html

Planned02

External Systems and Sinks: JDBC, HBase/Redis/Search/Object Storage Patterns, Async Calls, Batching, Timeouts, Retries, and Circuit-Breaker Design: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter18/Lesson2.html

Planned03

External Systems and Sinks: JDBC, HBase/Redis/Search/Object Storage Patterns, Async Calls, Batching, Timeouts, Retries, and Circuit-Breaker Design: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter18/Lesson3.html

Planned04

External Systems and Sinks: JDBC, HBase/Redis/Search/Object Storage Patterns, Async Calls, Batching, Timeouts, Retries, and Circuit-Breaker Design: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter18/Lesson4.html

Planned05

Checkpoint Lab — External Systems and Sinks: JDBC, HBase/Redis/Search/Object Storage Patterns, Async Calls, Batching, Timeouts, Retries, and Circuit-Breaker Design: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter18/Lesson5.html

Planned

Chapter 19

Schedulers: DefaultScheduler, IsolationScheduler, MultitenantScheduler, ResourceAwareScheduler, Placement Goals, and Shared-Cluster Tradeoffs

5 lessons

Schedulers: DefaultScheduler, IsolationScheduler, MultitenantScheduler, ResourceAwareScheduler, Placement Goals, and Shared-Cluster Tradeoffs: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter19/Lesson1.html

Planned02

Schedulers: DefaultScheduler, IsolationScheduler, MultitenantScheduler, ResourceAwareScheduler, Placement Goals, and Shared-Cluster Tradeoffs: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter19/Lesson2.html

Planned03

Schedulers: DefaultScheduler, IsolationScheduler, MultitenantScheduler, ResourceAwareScheduler, Placement Goals, and Shared-Cluster Tradeoffs: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter19/Lesson3.html

Planned04

Schedulers: DefaultScheduler, IsolationScheduler, MultitenantScheduler, ResourceAwareScheduler, Placement Goals, and Shared-Cluster Tradeoffs: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter19/Lesson4.html

Planned05

Checkpoint Lab — Schedulers: DefaultScheduler, IsolationScheduler, MultitenantScheduler, ResourceAwareScheduler, Placement Goals, and Shared-Cluster Tradeoffs: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter19/Lesson5.html

Planned

Chapter 20

Resource-Aware Scheduling and Custom Scheduling: CPU/Memory Profiles, Worker Heaps, Node Constraints, Priority, Custom IScheduler Plugins, and Testing

5 lessons

Resource-Aware Scheduling and Custom Scheduling: CPU/Memory Profiles, Worker Heaps, Node Constraints, Priority, Custom IScheduler Plugins, and Testing: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter20/Lesson1.html

Planned02

Resource-Aware Scheduling and Custom Scheduling: CPU/Memory Profiles, Worker Heaps, Node Constraints, Priority, Custom IScheduler Plugins, and Testing: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter20/Lesson2.html

Planned03

Resource-Aware Scheduling and Custom Scheduling: CPU/Memory Profiles, Worker Heaps, Node Constraints, Priority, Custom IScheduler Plugins, and Testing: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter20/Lesson3.html

Planned04

Resource-Aware Scheduling and Custom Scheduling: CPU/Memory Profiles, Worker Heaps, Node Constraints, Priority, Custom IScheduler Plugins, and Testing: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter20/Lesson4.html

Planned05

Checkpoint Lab — Resource-Aware Scheduling and Custom Scheduling: CPU/Memory Profiles, Worker Heaps, Node Constraints, Priority, Custom IScheduler Plugins, and Testing: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter20/Lesson5.html

Planned

Chapter 21

Daemon Fault Tolerance and Cluster Availability: Nimbus HA, Supervisor Failure, Worker Restart, ZooKeeper/Cluster-State Loss, and Recovery Procedures

5 lessons

Daemon Fault Tolerance and Cluster Availability: Nimbus HA, Supervisor Failure, Worker Restart, ZooKeeper/Cluster-State Loss, and Recovery Procedures: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter21/Lesson1.html

Planned02

Daemon Fault Tolerance and Cluster Availability: Nimbus HA, Supervisor Failure, Worker Restart, ZooKeeper/Cluster-State Loss, and Recovery Procedures: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter21/Lesson2.html

Planned03

Daemon Fault Tolerance and Cluster Availability: Nimbus HA, Supervisor Failure, Worker Restart, ZooKeeper/Cluster-State Loss, and Recovery Procedures: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter21/Lesson3.html

Planned04

Daemon Fault Tolerance and Cluster Availability: Nimbus HA, Supervisor Failure, Worker Restart, ZooKeeper/Cluster-State Loss, and Recovery Procedures: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter21/Lesson4.html

Planned05

Checkpoint Lab — Daemon Fault Tolerance and Cluster Availability: Nimbus HA, Supervisor Failure, Worker Restart, ZooKeeper/Cluster-State Loss, and Recovery Procedures: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter21/Lesson5.html

Planned

Chapter 22

Security: Authentication, Authorization, Kerberos Concepts, TLS, ZooKeeper Security, UI/DRPC Controls, Impersonation, and Least Privilege

5 lessons

Security: Authentication, Authorization, Kerberos Concepts, TLS, ZooKeeper Security, UI/DRPC Controls, Impersonation, and Least Privilege: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter22/Lesson1.html

Planned02

Security: Authentication, Authorization, Kerberos Concepts, TLS, ZooKeeper Security, UI/DRPC Controls, Impersonation, and Least Privilege: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter22/Lesson2.html

Planned03

Security: Authentication, Authorization, Kerberos Concepts, TLS, ZooKeeper Security, UI/DRPC Controls, Impersonation, and Least Privilege: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter22/Lesson3.html

Planned04

Security: Authentication, Authorization, Kerberos Concepts, TLS, ZooKeeper Security, UI/DRPC Controls, Impersonation, and Least Privilege: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter22/Lesson4.html

Planned05

Checkpoint Lab — Security: Authentication, Authorization, Kerberos Concepts, TLS, ZooKeeper Security, UI/DRPC Controls, Impersonation, and Least Privilege: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter22/Lesson5.html

Planned

Chapter 23

Secrets and Credentials: Topology Credentials, Sensitive Config, Worker Environment, Rotation, Redaction, External Secret Stores, and Operational Hygiene

5 lessons

Secrets and Credentials: Topology Credentials, Sensitive Config, Worker Environment, Rotation, Redaction, External Secret Stores, and Operational Hygiene: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter23/Lesson1.html

Planned02

Secrets and Credentials: Topology Credentials, Sensitive Config, Worker Environment, Rotation, Redaction, External Secret Stores, and Operational Hygiene: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter23/Lesson2.html

Planned03

Secrets and Credentials: Topology Credentials, Sensitive Config, Worker Environment, Rotation, Redaction, External Secret Stores, and Operational Hygiene: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter23/Lesson3.html

Planned04

Secrets and Credentials: Topology Credentials, Sensitive Config, Worker Environment, Rotation, Redaction, External Secret Stores, and Operational Hygiene: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter23/Lesson4.html

Planned05

Checkpoint Lab — Secrets and Credentials: Topology Credentials, Sensitive Config, Worker Environment, Rotation, Redaction, External Secret Stores, and Operational Hygiene: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter23/Lesson5.html

Planned

Chapter 24

Observability: Storm UI, REST API, Built-In Metrics, Custom Metrics, Worker/Executor Stats, Logging, Topology Health, Dashboards, and Alerts

5 lessons

Observability: Storm UI, REST API, Built-In Metrics, Custom Metrics, Worker/Executor Stats, Logging, Topology Health, Dashboards, and Alerts: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter24/Lesson1.html

Planned02

Observability: Storm UI, REST API, Built-In Metrics, Custom Metrics, Worker/Executor Stats, Logging, Topology Health, Dashboards, and Alerts: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter24/Lesson2.html

Planned03

Observability: Storm UI, REST API, Built-In Metrics, Custom Metrics, Worker/Executor Stats, Logging, Topology Health, Dashboards, and Alerts: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter24/Lesson3.html

Planned04

Observability: Storm UI, REST API, Built-In Metrics, Custom Metrics, Worker/Executor Stats, Logging, Topology Health, Dashboards, and Alerts: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter24/Lesson4.html

Planned05

Checkpoint Lab — Observability: Storm UI, REST API, Built-In Metrics, Custom Metrics, Worker/Executor Stats, Logging, Topology Health, Dashboards, and Alerts: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter24/Lesson5.html

Planned

Chapter 25

Performance Engineering: Serialization/Kryo, Tuple Size, Parallelism, Batching, Network Buffers, Ackers, GC, Worker Heaps, and Benchmark Methodology

5 lessons

Performance Engineering: Serialization/Kryo, Tuple Size, Parallelism, Batching, Network Buffers, Ackers, GC, Worker Heaps, and Benchmark Methodology: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter25/Lesson1.html

Planned02

Performance Engineering: Serialization/Kryo, Tuple Size, Parallelism, Batching, Network Buffers, Ackers, GC, Worker Heaps, and Benchmark Methodology: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter25/Lesson2.html

Planned03

Performance Engineering: Serialization/Kryo, Tuple Size, Parallelism, Batching, Network Buffers, Ackers, GC, Worker Heaps, and Benchmark Methodology: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter25/Lesson3.html

Planned04

Performance Engineering: Serialization/Kryo, Tuple Size, Parallelism, Batching, Network Buffers, Ackers, GC, Worker Heaps, and Benchmark Methodology: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter25/Lesson4.html

Planned05

Checkpoint Lab — Performance Engineering: Serialization/Kryo, Tuple Size, Parallelism, Batching, Network Buffers, Ackers, GC, Worker Heaps, and Benchmark Methodology: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter25/Lesson5.html

Planned

Chapter 26

Testing Topologies: Unit Testing Bolts/Spouts, Local/Mini Cluster Concepts, Deterministic Inputs, Fault Injection, Replay Tests, and Integration Validation

5 lessons

Testing Topologies: Unit Testing Bolts/Spouts, Local/Mini Cluster Concepts, Deterministic Inputs, Fault Injection, Replay Tests, and Integration Validation: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter26/Lesson1.html

Planned02

Testing Topologies: Unit Testing Bolts/Spouts, Local/Mini Cluster Concepts, Deterministic Inputs, Fault Injection, Replay Tests, and Integration Validation: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter26/Lesson2.html

Planned03

Testing Topologies: Unit Testing Bolts/Spouts, Local/Mini Cluster Concepts, Deterministic Inputs, Fault Injection, Replay Tests, and Integration Validation: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter26/Lesson3.html

Planned04

Testing Topologies: Unit Testing Bolts/Spouts, Local/Mini Cluster Concepts, Deterministic Inputs, Fault Injection, Replay Tests, and Integration Validation: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter26/Lesson4.html

Planned05

Checkpoint Lab — Testing Topologies: Unit Testing Bolts/Spouts, Local/Mini Cluster Concepts, Deterministic Inputs, Fault Injection, Replay Tests, and Integration Validation: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter26/Lesson5.html

Planned

Chapter 27

Production Operations: Capacity Planning, Shared Clusters, Log Management, Rolling Maintenance, Dependency Management, Topology Versioning, and Incident Runbooks

5 lessons

Production Operations: Capacity Planning, Shared Clusters, Log Management, Rolling Maintenance, Dependency Management, Topology Versioning, and Incident Runbooks: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter27/Lesson1.html

Planned02

Production Operations: Capacity Planning, Shared Clusters, Log Management, Rolling Maintenance, Dependency Management, Topology Versioning, and Incident Runbooks: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter27/Lesson2.html

Planned03

Production Operations: Capacity Planning, Shared Clusters, Log Management, Rolling Maintenance, Dependency Management, Topology Versioning, and Incident Runbooks: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter27/Lesson3.html

Planned04

Production Operations: Capacity Planning, Shared Clusters, Log Management, Rolling Maintenance, Dependency Management, Topology Versioning, and Incident Runbooks: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter27/Lesson4.html

Planned05

Checkpoint Lab — Production Operations: Capacity Planning, Shared Clusters, Log Management, Rolling Maintenance, Dependency Management, Topology Versioning, and Incident Runbooks: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter27/Lesson5.html

Planned

Chapter 28

Migrating Storm 2.x to 3.0: Java 25, Removed Clojure Dependency/DSL, API Compatibility, Configuration Review, Performance Changes, and Rollback Planning

5 lessons

Migrating Storm 2.x to 3.0: Java 25, Removed Clojure Dependency/DSL, API Compatibility, Configuration Review, Performance Changes, and Rollback Planning: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter28/Lesson1.html

Planned02

Migrating Storm 2.x to 3.0: Java 25, Removed Clojure Dependency/DSL, API Compatibility, Configuration Review, Performance Changes, and Rollback Planning: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter28/Lesson2.html

Planned03

Migrating Storm 2.x to 3.0: Java 25, Removed Clojure Dependency/DSL, API Compatibility, Configuration Review, Performance Changes, and Rollback Planning: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter28/Lesson3.html

Planned04

Migrating Storm 2.x to 3.0: Java 25, Removed Clojure Dependency/DSL, API Compatibility, Configuration Review, Performance Changes, and Rollback Planning: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter28/Lesson4.html

Planned05

Checkpoint Lab — Migrating Storm 2.x to 3.0: Java 25, Removed Clojure Dependency/DSL, API Compatibility, Configuration Review, Performance Changes, and Rollback Planning: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter28/Lesson5.html

Planned

Chapter 29

Storm in a Modern Streaming Stack: Choosing Storm vs Flink/Kafka Streams, Maintaining Legacy Investments, Incremental Modernization, and Migration Boundaries

5 lessons

Storm in a Modern Streaming Stack: Choosing Storm vs Flink/Kafka Streams, Maintaining Legacy Investments, Incremental Modernization, and Migration Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter29/Lesson1.html

Planned02

Storm in a Modern Streaming Stack: Choosing Storm vs Flink/Kafka Streams, Maintaining Legacy Investments, Incremental Modernization, and Migration Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter29/Lesson2.html

Planned03

Storm in a Modern Streaming Stack: Choosing Storm vs Flink/Kafka Streams, Maintaining Legacy Investments, Incremental Modernization, and Migration Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter29/Lesson3.html

Planned04

Storm in a Modern Streaming Stack: Choosing Storm vs Flink/Kafka Streams, Maintaining Legacy Investments, Incremental Modernization, and Migration Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter29/Lesson4.html

Planned05

Checkpoint Lab — Storm in a Modern Streaming Stack: Choosing Storm vs Flink/Kafka Streams, Maintaining Legacy Investments, Incremental Modernization, and Migration Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter29/Lesson5.html

Planned

Chapter 30

Production Capstone: Build, Secure, Schedule, Observe, Load-Test, Fail, Recover, Upgrade, and Modernize a Storm 3.0 Streaming Topology

5 lessons

Production Capstone: Build, Secure, Schedule, Observe, Load-Test, Fail, Recover, Upgrade, and Modernize a Storm 3.0 Streaming Topology: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter30/Lesson1.html

Planned02

Production Capstone: Build, Secure, Schedule, Observe, Load-Test, Fail, Recover, Upgrade, and Modernize a Storm 3.0 Streaming Topology: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter30/Lesson2.html

Planned03

Production Capstone: Build, Secure, Schedule, Observe, Load-Test, Fail, Recover, Upgrade, and Modernize a Storm 3.0 Streaming Topology: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter30/Lesson3.html

Planned04

Production Capstone: Build, Secure, Schedule, Observe, Load-Test, Fail, Recover, Upgrade, and Modernize a Storm 3.0 Streaming Topology: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter30/Lesson4.html

Planned05

Checkpoint Lab — Production Capstone: Build, Secure, Schedule, Observe, Load-Test, Fail, Recover, Upgrade, and Modernize a Storm 3.0 Streaming Topology: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter30/Lesson5.html

Planned