Course structure available

Stage 11 · Monitoring, Logging & Observability

Elastic Stack Complete Course

Master Elasticsearch, Kibana, Logstash, Beats, Elastic Agent, Fleet, ingest pipelines, data streams, ILM, search, security, observability, APM, vector retrieval, scaling, snapshots, upgrades, and production cluster operations.

Browse curriculum View all chapters

ELK

51chapters

255lessons

Advancedstarting level

Hands-onlearning mode

Course stateCurriculum ready

Course brief

A deep Elastic Stack curriculum covering distributed search, log ingestion, observability, security, lifecycle management, scalable operations, and modern semantic/vector retrieval.

This course is organized as a progressive operational curriculum. Lesson files are reserved in the repository structure so future content can be added without changing URLs or navigation.

By the end

You will be able to

Design Elasticsearch indices, mappings, data streams, shards, replicas, and lifecycle policies
Ingest and transform data with Elastic Agent, Beats, Logstash, and ingest pipelines
Build Kibana visualizations, dashboards, alerting, observability, and search workflows
Secure and govern Elastic clusters with TLS, roles, API keys, audit, and data controls
Scale, tune, snapshot, upgrade, troubleshoot, and recover production Elastic deployments

Complete syllabus

51 chapters in prerequisite order.

The structure goes beyond a command reference and includes architecture, security, reliability, troubleshooting, automation, governance, and production operations.

Chapter 1

Elastic Stack Foundations: Elasticsearch, Kibana, Logstash, Beats, Agent, and Fleet

5 lessons

Elastic Stack Foundations: Elasticsearch, Kibana, Logstash, Beats, Agent, and Fleet: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Elastic Stack Foundations: Elasticsearch, Kibana, Logstash, Beats, Agent, and Fleet: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Elastic Stack Foundations: Elasticsearch, Kibana, Logstash, Beats, Agent, and Fleet: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Elastic Stack Foundations: Elasticsearch, Kibana, Logstash, Beats, Agent, and Fleet: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Elastic Stack Foundations: Elasticsearch, Kibana, Logstash, Beats, Agent, and FleetReserved in course structure

Planned

Chapter 2

Elastic Stack 9.4 Architecture, Editions, Deployment Models, and Release Lifecycle

5 lessons

Elastic Stack 9.4 Architecture, Editions, Deployment Models, and Release Lifecycle: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Elastic Stack 9.4 Architecture, Editions, Deployment Models, and Release Lifecycle: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Elastic Stack 9.4 Architecture, Editions, Deployment Models, and Release Lifecycle: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Elastic Stack 9.4 Architecture, Editions, Deployment Models, and Release Lifecycle: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Elastic Stack 9.4 Architecture, Editions, Deployment Models, and Release LifecycleReserved in course structure

Planned

Chapter 3

Installing Elasticsearch, Kibana, Logstash, and Local Multi-Node Labs

5 lessons

Installing Elasticsearch, Kibana, Logstash, and Local Multi-Node Labs: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Installing Elasticsearch, Kibana, Logstash, and Local Multi-Node Labs: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Installing Elasticsearch, Kibana, Logstash, and Local Multi-Node Labs: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Installing Elasticsearch, Kibana, Logstash, and Local Multi-Node Labs: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Installing Elasticsearch, Kibana, Logstash, and Local Multi-Node LabsReserved in course structure

Planned

Chapter 4

Elasticsearch Cluster Architecture, Nodes, Roles, Master Election, and Coordination

5 lessons

Elasticsearch Cluster Architecture, Nodes, Roles, Master Election, and Coordination: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Elasticsearch Cluster Architecture, Nodes, Roles, Master Election, and Coordination: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Elasticsearch Cluster Architecture, Nodes, Roles, Master Election, and Coordination: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Elasticsearch Cluster Architecture, Nodes, Roles, Master Election, and Coordination: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Elasticsearch Cluster Architecture, Nodes, Roles, Master Election, and CoordinationReserved in course structure

Planned

Chapter 5

Indices, Documents, Fields, JSON, CRUD, and REST API Fundamentals

5 lessons

Indices, Documents, Fields, JSON, CRUD, and REST API Fundamentals: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Indices, Documents, Fields, JSON, CRUD, and REST API Fundamentals: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Indices, Documents, Fields, JSON, CRUD, and REST API Fundamentals: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Indices, Documents, Fields, JSON, CRUD, and REST API Fundamentals: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Indices, Documents, Fields, JSON, CRUD, and REST API FundamentalsReserved in course structure

Planned

Chapter 6

Mappings, Field Types, Dynamic Mapping, Templates, and Mapping Explosion

5 lessons

Mappings, Field Types, Dynamic Mapping, Templates, and Mapping Explosion: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Mappings, Field Types, Dynamic Mapping, Templates, and Mapping Explosion: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Mappings, Field Types, Dynamic Mapping, Templates, and Mapping Explosion: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Mappings, Field Types, Dynamic Mapping, Templates, and Mapping Explosion: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Mappings, Field Types, Dynamic Mapping, Templates, and Mapping ExplosionReserved in course structure

Planned

Chapter 7

Text Analysis, Analyzers, Tokenizers, Token Filters, Normalizers, and Languages

5 lessons

Text Analysis, Analyzers, Tokenizers, Token Filters, Normalizers, and Languages: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Text Analysis, Analyzers, Tokenizers, Token Filters, Normalizers, and Languages: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Text Analysis, Analyzers, Tokenizers, Token Filters, Normalizers, and Languages: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Text Analysis, Analyzers, Tokenizers, Token Filters, Normalizers, and Languages: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Text Analysis, Analyzers, Tokenizers, Token Filters, Normalizers, and LanguagesReserved in course structure

Planned

Chapter 8

Inverted Indexes, BKD Trees, Doc Values, Stored Fields, and Search Internals

5 lessons

Inverted Indexes, BKD Trees, Doc Values, Stored Fields, and Search Internals: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Inverted Indexes, BKD Trees, Doc Values, Stored Fields, and Search Internals: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Inverted Indexes, BKD Trees, Doc Values, Stored Fields, and Search Internals: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Inverted Indexes, BKD Trees, Doc Values, Stored Fields, and Search Internals: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Inverted Indexes, BKD Trees, Doc Values, Stored Fields, and Search InternalsReserved in course structure

Planned

Chapter 9

Query DSL Fundamentals: term, match, bool, range, exists, and Filters

5 lessons

Query DSL Fundamentals: term, match, bool, range, exists, and Filters: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Query DSL Fundamentals: term, match, bool, range, exists, and Filters: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Query DSL Fundamentals: term, match, bool, range, exists, and Filters: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Query DSL Fundamentals: term, match, bool, range, exists, and Filters: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Query DSL Fundamentals: term, match, bool, range, exists, and FiltersReserved in course structure

Planned

Chapter 10

Full-Text Search, Relevance, BM25, Multi-Match, Phrase, and Query Design

5 lessons

Full-Text Search, Relevance, BM25, Multi-Match, Phrase, and Query Design: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Full-Text Search, Relevance, BM25, Multi-Match, Phrase, and Query Design: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Full-Text Search, Relevance, BM25, Multi-Match, Phrase, and Query Design: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Full-Text Search, Relevance, BM25, Multi-Match, Phrase, and Query Design: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Full-Text Search, Relevance, BM25, Multi-Match, Phrase, and Query DesignReserved in course structure

Planned

Chapter 11

Aggregations: Metrics, Buckets, Pipeline Aggregations, and Analytics

5 lessons

Aggregations: Metrics, Buckets, Pipeline Aggregations, and Analytics: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Aggregations: Metrics, Buckets, Pipeline Aggregations, and Analytics: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Aggregations: Metrics, Buckets, Pipeline Aggregations, and Analytics: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Aggregations: Metrics, Buckets, Pipeline Aggregations, and Analytics: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Aggregations: Metrics, Buckets, Pipeline Aggregations, and AnalyticsReserved in course structure

Planned

Chapter 12

Runtime Fields, Scripts, Painless, Scripted Fields, and Performance Trade-Offs

5 lessons

Runtime Fields, Scripts, Painless, Scripted Fields, and Performance Trade-Offs: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Runtime Fields, Scripts, Painless, Scripted Fields, and Performance Trade-Offs: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Runtime Fields, Scripts, Painless, Scripted Fields, and Performance Trade-Offs: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Runtime Fields, Scripts, Painless, Scripted Fields, and Performance Trade-Offs: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Runtime Fields, Scripts, Painless, Scripted Fields, and Performance Trade-OffsReserved in course structure

Planned

Chapter 13

Aliases, Index Templates, Component Templates, and Reusable Index Configuration

5 lessons

Aliases, Index Templates, Component Templates, and Reusable Index Configuration: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Aliases, Index Templates, Component Templates, and Reusable Index Configuration: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Aliases, Index Templates, Component Templates, and Reusable Index Configuration: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Aliases, Index Templates, Component Templates, and Reusable Index Configuration: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Aliases, Index Templates, Component Templates, and Reusable Index ConfigurationReserved in course structure

Planned

Chapter 14

Data Streams, Backing Indices, Rollover, and Time-Series Data Architecture

5 lessons

Data Streams, Backing Indices, Rollover, and Time-Series Data Architecture: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Data Streams, Backing Indices, Rollover, and Time-Series Data Architecture: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Data Streams, Backing Indices, Rollover, and Time-Series Data Architecture: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Data Streams, Backing Indices, Rollover, and Time-Series Data Architecture: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Data Streams, Backing Indices, Rollover, and Time-Series Data ArchitectureReserved in course structure

Planned

Chapter 15

Time Series Data Streams, Downsampling Concepts, Dimensions, and Metrics

5 lessons

Time Series Data Streams, Downsampling Concepts, Dimensions, and Metrics: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Time Series Data Streams, Downsampling Concepts, Dimensions, and Metrics: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Time Series Data Streams, Downsampling Concepts, Dimensions, and Metrics: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Time Series Data Streams, Downsampling Concepts, Dimensions, and Metrics: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Time Series Data Streams, Downsampling Concepts, Dimensions, and MetricsReserved in course structure

Planned

Chapter 16

Shards, Replicas, Routing, Allocation, Awareness, and Failure Domains

5 lessons

Shards, Replicas, Routing, Allocation, Awareness, and Failure Domains: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Shards, Replicas, Routing, Allocation, Awareness, and Failure Domains: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Shards, Replicas, Routing, Allocation, Awareness, and Failure Domains: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Shards, Replicas, Routing, Allocation, Awareness, and Failure Domains: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Shards, Replicas, Routing, Allocation, Awareness, and Failure DomainsReserved in course structure

Planned

Chapter 17

Shard Sizing, Oversharding, Cluster State, Heap, and Capacity Planning

5 lessons

Shard Sizing, Oversharding, Cluster State, Heap, and Capacity Planning: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Shard Sizing, Oversharding, Cluster State, Heap, and Capacity Planning: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Shard Sizing, Oversharding, Cluster State, Heap, and Capacity Planning: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Shard Sizing, Oversharding, Cluster State, Heap, and Capacity Planning: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Shard Sizing, Oversharding, Cluster State, Heap, and Capacity PlanningReserved in course structure

Planned

Chapter 18

Index Lifecycle Management, Hot-Warm-Cold-Frozen, Rollover, and Delete

5 lessons

Index Lifecycle Management, Hot-Warm-Cold-Frozen, Rollover, and Delete: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Index Lifecycle Management, Hot-Warm-Cold-Frozen, Rollover, and Delete: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Index Lifecycle Management, Hot-Warm-Cold-Frozen, Rollover, and Delete: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Index Lifecycle Management, Hot-Warm-Cold-Frozen, Rollover, and Delete: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Index Lifecycle Management, Hot-Warm-Cold-Frozen, Rollover, and DeleteReserved in course structure

Planned

Chapter 19

Data Lifecycle Management Concepts and Serverless-Oriented Retention

5 lessons

Data Lifecycle Management Concepts and Serverless-Oriented Retention: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Data Lifecycle Management Concepts and Serverless-Oriented Retention: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Data Lifecycle Management Concepts and Serverless-Oriented Retention: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Data Lifecycle Management Concepts and Serverless-Oriented Retention: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Data Lifecycle Management Concepts and Serverless-Oriented RetentionReserved in course structure

Planned

Chapter 20

Searchable Snapshots, Frozen Tier, Object Storage, and Cost Optimization

5 lessons

Searchable Snapshots, Frozen Tier, Object Storage, and Cost Optimization: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Searchable Snapshots, Frozen Tier, Object Storage, and Cost Optimization: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Searchable Snapshots, Frozen Tier, Object Storage, and Cost Optimization: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Searchable Snapshots, Frozen Tier, Object Storage, and Cost Optimization: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Searchable Snapshots, Frozen Tier, Object Storage, and Cost OptimizationReserved in course structure

Planned

Chapter 21

Ingest Pipelines, Processors, Grok, Dissect, Enrich, Script, and Failure Handling

5 lessons

Ingest Pipelines, Processors, Grok, Dissect, Enrich, Script, and Failure Handling: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Ingest Pipelines, Processors, Grok, Dissect, Enrich, Script, and Failure Handling: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Ingest Pipelines, Processors, Grok, Dissect, Enrich, Script, and Failure Handling: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Ingest Pipelines, Processors, Grok, Dissect, Enrich, Script, and Failure Handling: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Ingest Pipelines, Processors, Grok, Dissect, Enrich, Script, and Failure HandlingReserved in course structure

Planned

Chapter 22

Elastic Agent, Integrations, Fleet Server, Policies, Enrollment, and Upgrades

5 lessons

Elastic Agent, Integrations, Fleet Server, Policies, Enrollment, and Upgrades: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Elastic Agent, Integrations, Fleet Server, Policies, Enrollment, and Upgrades: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Elastic Agent, Integrations, Fleet Server, Policies, Enrollment, and Upgrades: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Elastic Agent, Integrations, Fleet Server, Policies, Enrollment, and Upgrades: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Elastic Agent, Integrations, Fleet Server, Policies, Enrollment, and UpgradesReserved in course structure

Planned

Chapter 23

Beats Architecture, Filebeat, Metricbeat, Heartbeat Concepts, and Migration to Agent

5 lessons

Beats Architecture, Filebeat, Metricbeat, Heartbeat Concepts, and Migration to Agent: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Beats Architecture, Filebeat, Metricbeat, Heartbeat Concepts, and Migration to Agent: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Beats Architecture, Filebeat, Metricbeat, Heartbeat Concepts, and Migration to Agent: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Beats Architecture, Filebeat, Metricbeat, Heartbeat Concepts, and Migration to Agent: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Beats Architecture, Filebeat, Metricbeat, Heartbeat Concepts, and Migration to AgentReserved in course structure

Planned

Chapter 24

Logstash Architecture, Inputs, Filters, Outputs, Codecs, and Events

5 lessons

Logstash Architecture, Inputs, Filters, Outputs, Codecs, and Events: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Logstash Architecture, Inputs, Filters, Outputs, Codecs, and Events: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Logstash Architecture, Inputs, Filters, Outputs, Codecs, and Events: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Logstash Architecture, Inputs, Filters, Outputs, Codecs, and Events: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Logstash Architecture, Inputs, Filters, Outputs, Codecs, and EventsReserved in course structure

Planned

Chapter 25

Logstash Pipelines, Grok, Dissect, Mutate, Date, Aggregate, and Conditional Logic

5 lessons

Logstash Pipelines, Grok, Dissect, Mutate, Date, Aggregate, and Conditional Logic: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Logstash Pipelines, Grok, Dissect, Mutate, Date, Aggregate, and Conditional Logic: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Logstash Pipelines, Grok, Dissect, Mutate, Date, Aggregate, and Conditional Logic: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Logstash Pipelines, Grok, Dissect, Mutate, Date, Aggregate, and Conditional Logic: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Logstash Pipelines, Grok, Dissect, Mutate, Date, Aggregate, and Conditional LogicReserved in course structure

Planned

Chapter 26

Logstash Persistent Queues, Dead Letter Queues, Backpressure, and Reliability

5 lessons

Logstash Persistent Queues, Dead Letter Queues, Backpressure, and Reliability: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Logstash Persistent Queues, Dead Letter Queues, Backpressure, and Reliability: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Logstash Persistent Queues, Dead Letter Queues, Backpressure, and Reliability: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Logstash Persistent Queues, Dead Letter Queues, Backpressure, and Reliability: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Logstash Persistent Queues, Dead Letter Queues, Backpressure, and ReliabilityReserved in course structure

Planned

Chapter 27

Logstash Multiple Pipelines, Pipeline-to-Pipeline, Monitoring, and Performance

5 lessons

Logstash Multiple Pipelines, Pipeline-to-Pipeline, Monitoring, and Performance: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Logstash Multiple Pipelines, Pipeline-to-Pipeline, Monitoring, and Performance: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Logstash Multiple Pipelines, Pipeline-to-Pipeline, Monitoring, and Performance: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Logstash Multiple Pipelines, Pipeline-to-Pipeline, Monitoring, and Performance: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Logstash Multiple Pipelines, Pipeline-to-Pipeline, Monitoring, and PerformanceReserved in course structure

Planned

Chapter 28

Kibana Foundations, Spaces, Data Views, Discover, Saved Objects, and Navigation

5 lessons

Kibana Foundations, Spaces, Data Views, Discover, Saved Objects, and Navigation: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Kibana Foundations, Spaces, Data Views, Discover, Saved Objects, and Navigation: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Kibana Foundations, Spaces, Data Views, Discover, Saved Objects, and Navigation: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Kibana Foundations, Spaces, Data Views, Discover, Saved Objects, and Navigation: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Kibana Foundations, Spaces, Data Views, Discover, Saved Objects, and NavigationReserved in course structure

Planned

Chapter 29

Lens, Dashboards, Visualizations, Controls, Maps, and Operational Exploration

5 lessons

Lens, Dashboards, Visualizations, Controls, Maps, and Operational Exploration: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Lens, Dashboards, Visualizations, Controls, Maps, and Operational Exploration: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Lens, Dashboards, Visualizations, Controls, Maps, and Operational Exploration: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Lens, Dashboards, Visualizations, Controls, Maps, and Operational Exploration: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Lens, Dashboards, Visualizations, Controls, Maps, and Operational ExplorationReserved in course structure

Planned

Chapter 30

Kibana Query Language, Lucene Syntax, ES|QL, and Analytical Workflows

5 lessons

Kibana Query Language, Lucene Syntax, ES|QL, and Analytical Workflows: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Kibana Query Language, Lucene Syntax, ES|QL, and Analytical Workflows: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Kibana Query Language, Lucene Syntax, ES|QL, and Analytical Workflows: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Kibana Query Language, Lucene Syntax, ES|QL, and Analytical Workflows: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Kibana Query Language, Lucene Syntax, ES|QL, and Analytical WorkflowsReserved in course structure

Planned

Chapter 31

Kibana Alerting, Rules, Connectors, Cases, and Incident Workflows

5 lessons

Kibana Alerting, Rules, Connectors, Cases, and Incident Workflows: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Kibana Alerting, Rules, Connectors, Cases, and Incident Workflows: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Kibana Alerting, Rules, Connectors, Cases, and Incident Workflows: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Kibana Alerting, Rules, Connectors, Cases, and Incident Workflows: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Kibana Alerting, Rules, Connectors, Cases, and Incident WorkflowsReserved in course structure

Planned

Chapter 32

Elastic Observability: Logs, Metrics, Uptime/Synthetics, and Infrastructure Views

5 lessons

Elastic Observability: Logs, Metrics, Uptime/Synthetics, and Infrastructure Views: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Elastic Observability: Logs, Metrics, Uptime/Synthetics, and Infrastructure Views: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Elastic Observability: Logs, Metrics, Uptime/Synthetics, and Infrastructure Views: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Elastic Observability: Logs, Metrics, Uptime/Synthetics, and Infrastructure Views: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Elastic Observability: Logs, Metrics, Uptime/Synthetics, and Infrastructure ViewsReserved in course structure

Planned

Chapter 33

Elastic APM, Agents, Transactions, Spans, Services, and Distributed Tracing

5 lessons

Elastic APM, Agents, Transactions, Spans, Services, and Distributed Tracing: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Elastic APM, Agents, Transactions, Spans, Services, and Distributed Tracing: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Elastic APM, Agents, Transactions, Spans, Services, and Distributed Tracing: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Elastic APM, Agents, Transactions, Spans, Services, and Distributed Tracing: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Elastic APM, Agents, Transactions, Spans, Services, and Distributed TracingReserved in course structure

Planned

Chapter 34

OpenTelemetry Integration, OTLP, Elastic APM Server, and Signal Correlation

5 lessons

OpenTelemetry Integration, OTLP, Elastic APM Server, and Signal Correlation: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

OpenTelemetry Integration, OTLP, Elastic APM Server, and Signal Correlation: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

OpenTelemetry Integration, OTLP, Elastic APM Server, and Signal Correlation: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

OpenTelemetry Integration, OTLP, Elastic APM Server, and Signal Correlation: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — OpenTelemetry Integration, OTLP, Elastic APM Server, and Signal CorrelationReserved in course structure

Planned

Chapter 35

Elasticsearch Security, TLS, Users, Roles, Privileges, and Native Realm

5 lessons

Elasticsearch Security, TLS, Users, Roles, Privileges, and Native Realm: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Elasticsearch Security, TLS, Users, Roles, Privileges, and Native Realm: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Elasticsearch Security, TLS, Users, Roles, Privileges, and Native Realm: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Elasticsearch Security, TLS, Users, Roles, Privileges, and Native Realm: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Elasticsearch Security, TLS, Users, Roles, Privileges, and Native RealmReserved in course structure

Planned

Chapter 36

API Keys, Service Accounts, Tokens, SSO/OIDC/SAML/LDAP Concepts, and Authentication

5 lessons

API Keys, Service Accounts, Tokens, SSO/OIDC/SAML/LDAP Concepts, and Authentication: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

API Keys, Service Accounts, Tokens, SSO/OIDC/SAML/LDAP Concepts, and Authentication: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

API Keys, Service Accounts, Tokens, SSO/OIDC/SAML/LDAP Concepts, and Authentication: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

API Keys, Service Accounts, Tokens, SSO/OIDC/SAML/LDAP Concepts, and Authentication: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — API Keys, Service Accounts, Tokens, SSO/OIDC/SAML/LDAP Concepts, and AuthenticationReserved in course structure

Planned

Chapter 37

Document-Level Security, Field-Level Security, Spaces, and Multi-Tenancy

5 lessons

Document-Level Security, Field-Level Security, Spaces, and Multi-Tenancy: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Document-Level Security, Field-Level Security, Spaces, and Multi-Tenancy: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Document-Level Security, Field-Level Security, Spaces, and Multi-Tenancy: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Document-Level Security, Field-Level Security, Spaces, and Multi-Tenancy: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Document-Level Security, Field-Level Security, Spaces, and Multi-TenancyReserved in course structure

Planned

Chapter 38

Audit Logging, Encryption, Compliance, Sensitive Data, and Security Hardening

5 lessons

Audit Logging, Encryption, Compliance, Sensitive Data, and Security Hardening: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Audit Logging, Encryption, Compliance, Sensitive Data, and Security Hardening: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Audit Logging, Encryption, Compliance, Sensitive Data, and Security Hardening: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Audit Logging, Encryption, Compliance, Sensitive Data, and Security Hardening: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Audit Logging, Encryption, Compliance, Sensitive Data, and Security HardeningReserved in course structure

Planned

Chapter 39

Cross-Cluster Search, Remote Clusters, Cross-Cluster Replication, and Multi-Region Design

5 lessons

Cross-Cluster Search, Remote Clusters, Cross-Cluster Replication, and Multi-Region Design: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Cross-Cluster Search, Remote Clusters, Cross-Cluster Replication, and Multi-Region Design: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Cross-Cluster Search, Remote Clusters, Cross-Cluster Replication, and Multi-Region Design: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Cross-Cluster Search, Remote Clusters, Cross-Cluster Replication, and Multi-Region Design: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Cross-Cluster Search, Remote Clusters, Cross-Cluster Replication, and Multi-Region DesignReserved in course structure

Planned

Chapter 40

Snapshot Lifecycle Management, Repositories, Snapshots, Restore, and DR

5 lessons

Snapshot Lifecycle Management, Repositories, Snapshots, Restore, and DR: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Snapshot Lifecycle Management, Repositories, Snapshots, Restore, and DR: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Snapshot Lifecycle Management, Repositories, Snapshots, Restore, and DR: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Snapshot Lifecycle Management, Repositories, Snapshots, Restore, and DR: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Snapshot Lifecycle Management, Repositories, Snapshots, Restore, and DRReserved in course structure

Planned

Chapter 41

Transforms, Entity-Centric Indices, Continuous Transforms, and Analytics

5 lessons

Transforms, Entity-Centric Indices, Continuous Transforms, and Analytics: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Transforms, Entity-Centric Indices, Continuous Transforms, and Analytics: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Transforms, Entity-Centric Indices, Continuous Transforms, and Analytics: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Transforms, Entity-Centric Indices, Continuous Transforms, and Analytics: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Transforms, Entity-Centric Indices, Continuous Transforms, and AnalyticsReserved in course structure

Planned

Chapter 42

Machine Learning Jobs, Anomaly Detection, Data Frame Analytics Concepts, and Alerts

5 lessons

Machine Learning Jobs, Anomaly Detection, Data Frame Analytics Concepts, and Alerts: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Machine Learning Jobs, Anomaly Detection, Data Frame Analytics Concepts, and Alerts: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Machine Learning Jobs, Anomaly Detection, Data Frame Analytics Concepts, and Alerts: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Machine Learning Jobs, Anomaly Detection, Data Frame Analytics Concepts, and Alerts: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Machine Learning Jobs, Anomaly Detection, Data Frame Analytics Concepts, and AlertsReserved in course structure

Planned

Chapter 43

Vector Search, dense_vector, kNN, HNSW, Quantization, and ANN Fundamentals

5 lessons

Vector Search, dense_vector, kNN, HNSW, Quantization, and ANN Fundamentals: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Vector Search, dense_vector, kNN, HNSW, Quantization, and ANN Fundamentals: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Vector Search, dense_vector, kNN, HNSW, Quantization, and ANN Fundamentals: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Vector Search, dense_vector, kNN, HNSW, Quantization, and ANN Fundamentals: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Vector Search, dense_vector, kNN, HNSW, Quantization, and ANN FundamentalsReserved in course structure

Planned

Chapter 44

Semantic Search, Inference Endpoints, Hybrid Retrieval, Reranking, and RAG Patterns

5 lessons

Semantic Search, Inference Endpoints, Hybrid Retrieval, Reranking, and RAG Patterns: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Semantic Search, Inference Endpoints, Hybrid Retrieval, Reranking, and RAG Patterns: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Semantic Search, Inference Endpoints, Hybrid Retrieval, Reranking, and RAG Patterns: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Semantic Search, Inference Endpoints, Hybrid Retrieval, Reranking, and RAG Patterns: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Semantic Search, Inference Endpoints, Hybrid Retrieval, Reranking, and RAG PatternsReserved in course structure

Planned

Chapter 45

Search Applications, Relevance Evaluation, Synonyms, Query Rules, and Tuning

5 lessons

Search Applications, Relevance Evaluation, Synonyms, Query Rules, and Tuning: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Search Applications, Relevance Evaluation, Synonyms, Query Rules, and Tuning: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Search Applications, Relevance Evaluation, Synonyms, Query Rules, and Tuning: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Search Applications, Relevance Evaluation, Synonyms, Query Rules, and Tuning: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Search Applications, Relevance Evaluation, Synonyms, Query Rules, and TuningReserved in course structure

Planned

Chapter 46

Profiling Search, Slow Logs, Hot Threads, Tasks, Node Stats, and Diagnostics

5 lessons

Profiling Search, Slow Logs, Hot Threads, Tasks, Node Stats, and Diagnostics: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Profiling Search, Slow Logs, Hot Threads, Tasks, Node Stats, and Diagnostics: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Profiling Search, Slow Logs, Hot Threads, Tasks, Node Stats, and Diagnostics: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Profiling Search, Slow Logs, Hot Threads, Tasks, Node Stats, and Diagnostics: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Profiling Search, Slow Logs, Hot Threads, Tasks, Node Stats, and DiagnosticsReserved in course structure

Planned

Chapter 47

Indexing Performance, Bulk API, Refresh, Merges, Translog, and Throughput Tuning

5 lessons

Indexing Performance, Bulk API, Refresh, Merges, Translog, and Throughput Tuning: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Indexing Performance, Bulk API, Refresh, Merges, Translog, and Throughput Tuning: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Indexing Performance, Bulk API, Refresh, Merges, Translog, and Throughput Tuning: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Indexing Performance, Bulk API, Refresh, Merges, Translog, and Throughput Tuning: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Indexing Performance, Bulk API, Refresh, Merges, Translog, and Throughput TuningReserved in course structure

Planned

Chapter 48

Search Performance, Caches, Memory, Query Design, Aggregation Cost, and Latency

5 lessons

Search Performance, Caches, Memory, Query Design, Aggregation Cost, and Latency: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Search Performance, Caches, Memory, Query Design, Aggregation Cost, and Latency: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Search Performance, Caches, Memory, Query Design, Aggregation Cost, and Latency: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Search Performance, Caches, Memory, Query Design, Aggregation Cost, and Latency: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Search Performance, Caches, Memory, Query Design, Aggregation Cost, and LatencyReserved in course structure

Planned

Chapter 49

Cluster Monitoring, Stack Monitoring, Prometheus Concepts, Logging, and Alerting

5 lessons

Cluster Monitoring, Stack Monitoring, Prometheus Concepts, Logging, and Alerting: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Cluster Monitoring, Stack Monitoring, Prometheus Concepts, Logging, and Alerting: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Cluster Monitoring, Stack Monitoring, Prometheus Concepts, Logging, and Alerting: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Cluster Monitoring, Stack Monitoring, Prometheus Concepts, Logging, and Alerting: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Cluster Monitoring, Stack Monitoring, Prometheus Concepts, Logging, and AlertingReserved in course structure

Planned

Chapter 50

Rolling Upgrades, Breaking Changes, 8.x-to-9.x Migration, and Compatibility

5 lessons

Rolling Upgrades, Breaking Changes, 8.x-to-9.x Migration, and Compatibility: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Rolling Upgrades, Breaking Changes, 8.x-to-9.x Migration, and Compatibility: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Rolling Upgrades, Breaking Changes, 8.x-to-9.x Migration, and Compatibility: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Rolling Upgrades, Breaking Changes, 8.x-to-9.x Migration, and Compatibility: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Rolling Upgrades, Breaking Changes, 8.x-to-9.x Migration, and CompatibilityReserved in course structure

Planned

Chapter 51

Production Capstone: Design, Secure, Scale, Observe, Search, Upgrade, and Recover an Elastic Platform

5 lessons

Capstone Requirements, Architecture, SLOs, and Success CriteriaReserved in course structure

Planned

Build the End-to-End Monitoring or Delivery EnvironmentReserved in course structure

Planned

Integrate Security, Automation, Governance, and ObservabilityReserved in course structure

Planned

Inject Failures, Diagnose Behavior, Recover Safely, and Verify StateReserved in course structure

Planned

Final Validation, Runbook, Operational Handoff, and Improvement BacklogReserved in course structure

Planned

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Elastic Stack Complete Course

A deep Elastic Stack curriculum covering distributed search, log ingestion, observability, security, lifecycle management, scalable operations, and modern semantic/vector retrieval.

You will be able to

51 chapters in prerequisite order.

Elastic Stack Foundations: Elasticsearch, Kibana, Logstash, Beats, Agent, and Fleet

Elastic Stack 9.4 Architecture, Editions, Deployment Models, and Release Lifecycle

Installing Elasticsearch, Kibana, Logstash, and Local Multi-Node Labs

Elasticsearch Cluster Architecture, Nodes, Roles, Master Election, and Coordination

Indices, Documents, Fields, JSON, CRUD, and REST API Fundamentals

Mappings, Field Types, Dynamic Mapping, Templates, and Mapping Explosion

Text Analysis, Analyzers, Tokenizers, Token Filters, Normalizers, and Languages

Inverted Indexes, BKD Trees, Doc Values, Stored Fields, and Search Internals

Query DSL Fundamentals: term, match, bool, range, exists, and Filters

Full-Text Search, Relevance, BM25, Multi-Match, Phrase, and Query Design

Aggregations: Metrics, Buckets, Pipeline Aggregations, and Analytics

Runtime Fields, Scripts, Painless, Scripted Fields, and Performance Trade-Offs

Aliases, Index Templates, Component Templates, and Reusable Index Configuration

Data Streams, Backing Indices, Rollover, and Time-Series Data Architecture

Time Series Data Streams, Downsampling Concepts, Dimensions, and Metrics

Shards, Replicas, Routing, Allocation, Awareness, and Failure Domains

Shard Sizing, Oversharding, Cluster State, Heap, and Capacity Planning

Index Lifecycle Management, Hot-Warm-Cold-Frozen, Rollover, and Delete

Data Lifecycle Management Concepts and Serverless-Oriented Retention

Searchable Snapshots, Frozen Tier, Object Storage, and Cost Optimization

Ingest Pipelines, Processors, Grok, Dissect, Enrich, Script, and Failure Handling

Elastic Agent, Integrations, Fleet Server, Policies, Enrollment, and Upgrades

Beats Architecture, Filebeat, Metricbeat, Heartbeat Concepts, and Migration to Agent

Logstash Architecture, Inputs, Filters, Outputs, Codecs, and Events

Logstash Pipelines, Grok, Dissect, Mutate, Date, Aggregate, and Conditional Logic

Logstash Persistent Queues, Dead Letter Queues, Backpressure, and Reliability

Logstash Multiple Pipelines, Pipeline-to-Pipeline, Monitoring, and Performance

Kibana Foundations, Spaces, Data Views, Discover, Saved Objects, and Navigation

Lens, Dashboards, Visualizations, Controls, Maps, and Operational Exploration

Kibana Query Language, Lucene Syntax, ES|QL, and Analytical Workflows

Kibana Alerting, Rules, Connectors, Cases, and Incident Workflows

Elastic Observability: Logs, Metrics, Uptime/Synthetics, and Infrastructure Views

Elastic APM, Agents, Transactions, Spans, Services, and Distributed Tracing

OpenTelemetry Integration, OTLP, Elastic APM Server, and Signal Correlation

Elasticsearch Security, TLS, Users, Roles, Privileges, and Native Realm

API Keys, Service Accounts, Tokens, SSO/OIDC/SAML/LDAP Concepts, and Authentication

Document-Level Security, Field-Level Security, Spaces, and Multi-Tenancy

Audit Logging, Encryption, Compliance, Sensitive Data, and Security Hardening

Cross-Cluster Search, Remote Clusters, Cross-Cluster Replication, and Multi-Region Design

Snapshot Lifecycle Management, Repositories, Snapshots, Restore, and DR

Transforms, Entity-Centric Indices, Continuous Transforms, and Analytics

Machine Learning Jobs, Anomaly Detection, Data Frame Analytics Concepts, and Alerts

Vector Search, dense_vector, kNN, HNSW, Quantization, and ANN Fundamentals

Semantic Search, Inference Endpoints, Hybrid Retrieval, Reranking, and RAG Patterns

Search Applications, Relevance Evaluation, Synonyms, Query Rules, and Tuning

Profiling Search, Slow Logs, Hot Threads, Tasks, Node Stats, and Diagnostics

Indexing Performance, Bulk API, Refresh, Merges, Translog, and Throughput Tuning

Search Performance, Caches, Memory, Query Design, Aggregation Cost, and Latency

Cluster Monitoring, Stack Monitoring, Prometheus Concepts, Logging, and Alerting

Rolling Upgrades, Breaking Changes, 8.x-to-9.x Migration, and Compatibility

Production Capstone: Design, Secure, Scale, Observe, Search, Upgrade, and Recover an Elastic Platform

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