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Stage 11 · Monitoring, Logging & Observability

Prometheus Complete Course

Master Prometheus from metrics, scraping, labels, PromQL, TSDB internals, exporters, rules, and Alertmanager through service discovery, remote write, federation, Kubernetes, cardinality control, security, HA, and production-scale monitoring.

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PROM
42chapters
210lessons
Intermediatestarting level
Hands-onlearning mode
Course stateCurriculum ready

Course brief

A comprehensive Prometheus curriculum for metric collection, time-series analysis, alerting, scalable storage integration, and production observability.

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 and scrape high-quality metric endpoints
  • Write PromQL for troubleshooting, dashboards, SLOs, and alerting
  • Understand TSDB storage, labels, cardinality, recording rules, and retention
  • Integrate Alertmanager, service discovery, exporters, Kubernetes, and remote storage
  • Operate Prometheus securely with HA, capacity planning, upgrades, and recovery

Complete syllabus

42 chapters in prerequisite order.

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

01

Chapter 1

Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations

5 lessons
01
Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Metrics, Time-Series Monitoring, Observability, and Prometheus FoundationsReserved in course structure
Planned
02

Chapter 2

Prometheus 3.x Architecture, Components, Data Model, and Release Strategy

5 lessons
01
Prometheus 3.x Architecture, Components, Data Model, and Release Strategy: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Prometheus 3.x Architecture, Components, Data Model, and Release Strategy: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Prometheus 3.x Architecture, Components, Data Model, and Release Strategy: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Prometheus 3.x Architecture, Components, Data Model, and Release Strategy: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Prometheus 3.x Architecture, Components, Data Model, and Release StrategyReserved in course structure
Planned
03

Chapter 3

Installing Prometheus, Docker Images, Distroless Options, and Lab Setup

5 lessons
01
Installing Prometheus, Docker Images, Distroless Options, and Lab Setup: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Installing Prometheus, Docker Images, Distroless Options, and Lab Setup: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Installing Prometheus, Docker Images, Distroless Options, and Lab Setup: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Installing Prometheus, Docker Images, Distroless Options, and Lab Setup: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Installing Prometheus, Docker Images, Distroless Options, and Lab SetupReserved in course structure
Planned
04

Chapter 4

Configuration Files, Global Settings, Scrape Configs, and Reloading

5 lessons
01
Configuration Files, Global Settings, Scrape Configs, and Reloading: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Configuration Files, Global Settings, Scrape Configs, and Reloading: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Configuration Files, Global Settings, Scrape Configs, and Reloading: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Configuration Files, Global Settings, Scrape Configs, and Reloading: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Configuration Files, Global Settings, Scrape Configs, and ReloadingReserved in course structure
Planned
05

Chapter 5

Targets, Scraping, Pull Model, HTTP Exposition, and Target Health

5 lessons
01
Targets, Scraping, Pull Model, HTTP Exposition, and Target Health: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Targets, Scraping, Pull Model, HTTP Exposition, and Target Health: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Targets, Scraping, Pull Model, HTTP Exposition, and Target Health: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Targets, Scraping, Pull Model, HTTP Exposition, and Target Health: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Targets, Scraping, Pull Model, HTTP Exposition, and Target HealthReserved in course structure
Planned
06

Chapter 6

Metric Names, Labels, Samples, Timestamps, and Time-Series Identity

5 lessons
01
Metric Names, Labels, Samples, Timestamps, and Time-Series Identity: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Metric Names, Labels, Samples, Timestamps, and Time-Series Identity: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Metric Names, Labels, Samples, Timestamps, and Time-Series Identity: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Metric Names, Labels, Samples, Timestamps, and Time-Series Identity: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Metric Names, Labels, Samples, Timestamps, and Time-Series IdentityReserved in course structure
Planned
07

Chapter 7

Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics

5 lessons
01
Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Counter, Gauge, Histogram, Summary, Info, and StateSet Metric SemanticsReserved in course structure
Planned
08

Chapter 8

Instrumentation Design, RED, USE, Golden Signals, and Metric Naming

5 lessons
01
Instrumentation Design, RED, USE, Golden Signals, and Metric Naming: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Instrumentation Design, RED, USE, Golden Signals, and Metric Naming: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Instrumentation Design, RED, USE, Golden Signals, and Metric Naming: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Instrumentation Design, RED, USE, Golden Signals, and Metric Naming: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Instrumentation Design, RED, USE, Golden Signals, and Metric NamingReserved in course structure
Planned
09

Chapter 9

Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET

5 lessons
01
Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Prometheus Client Libraries for Go, Python, Java, Node.js, and .NETReserved in course structure
Planned
10

Chapter 10

Exporters, node_exporter, blackbox_exporter, and Integration Patterns

5 lessons
01
Exporters, node_exporter, blackbox_exporter, and Integration Patterns: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Exporters, node_exporter, blackbox_exporter, and Integration Patterns: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Exporters, node_exporter, blackbox_exporter, and Integration Patterns: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Exporters, node_exporter, blackbox_exporter, and Integration Patterns: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Exporters, node_exporter, blackbox_exporter, and Integration PatternsReserved in course structure
Planned
11

Chapter 11

Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata

5 lessons
01
Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Relabeling Fundamentals, Target Relabeling, Labels, and Discovery MetadataReserved in course structure
Planned
12

Chapter 12

Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control

5 lessons
01
Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion ControlReserved in course structure
Planned
13

Chapter 13

PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries

5 lessons
01
PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range QueriesReserved in course structure
Planned
14

Chapter 14

PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins

5 lessons
01
PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — PromQL Operators, Vector Matching, one-to-one, many-to-one, and JoinsReserved in course structure
Planned
15

Chapter 15

PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives

5 lessons
01
PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — PromQL Functions, Rates, Increases, Deltas, Resets, and DerivativesReserved in course structure
Planned
16

Chapter 16

Aggregation, topk, quantile, count_values, and Dimensional Analysis

5 lessons
01
Aggregation, topk, quantile, count_values, and Dimensional Analysis: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Aggregation, topk, quantile, count_values, and Dimensional Analysis: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Aggregation, topk, quantile, count_values, and Dimensional Analysis: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Aggregation, topk, quantile, count_values, and Dimensional Analysis: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Aggregation, topk, quantile, count_values, and Dimensional AnalysisReserved in course structure
Planned
17

Chapter 17

Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles

5 lessons
01
Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Histograms, Buckets, histogram_quantile, Native Histograms, and PercentilesReserved in course structure
Planned
18

Chapter 18

Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison

5 lessons
01
Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Subqueries, offset, @ Modifier, Time Functions, and Historical ComparisonReserved in course structure
Planned
19

Chapter 19

Absent Data, Staleness, Missing Series, and Defensive PromQL

5 lessons
01
Absent Data, Staleness, Missing Series, and Defensive PromQL: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Absent Data, Staleness, Missing Series, and Defensive PromQL: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Absent Data, Staleness, Missing Series, and Defensive PromQL: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Absent Data, Staleness, Missing Series, and Defensive PromQL: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Absent Data, Staleness, Missing Series, and Defensive PromQLReserved in course structure
Planned
20

Chapter 20

Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration

5 lessons
01
Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Recording Rules, Rule Groups, Evaluation Intervals, and Query AccelerationReserved in course structure
Planned
21

Chapter 21

Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design

5 lessons
01
Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert DesignReserved in course structure
Planned
22

Chapter 22

Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences

5 lessons
01
Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and SilencesReserved in course structure
Planned
23

Chapter 23

Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates

5 lessons
01
Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and TemplatesReserved in course structure
Planned
24

Chapter 24

Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets

5 lessons
01
Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic TargetsReserved in course structure
Planned
25

Chapter 25

Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling

5 lessons
01
Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and RelabelingReserved in course structure
Planned
26

Chapter 26

Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs

5 lessons
01
Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDsReserved in course structure
Planned
27

Chapter 27

kube-prometheus-stack Architecture, Components, and Production Deployment

5 lessons
01
kube-prometheus-stack Architecture, Components, and Production Deployment: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
kube-prometheus-stack Architecture, Components, and Production Deployment: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
kube-prometheus-stack Architecture, Components, and Production Deployment: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
kube-prometheus-stack Architecture, Components, and Production Deployment: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — kube-prometheus-stack Architecture, Components, and Production DeploymentReserved in course structure
Planned
28

Chapter 28

TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index

5 lessons
01
TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and IndexReserved in course structure
Planned
29

Chapter 29

Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning

5 lessons
01
Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity PlanningReserved in course structure
Planned
30

Chapter 30

Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control

5 lessons
01
Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Cardinality, Churn, High-Cardinality Labels, and Metric Cost ControlReserved in course structure
Planned
31

Chapter 31

Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning

5 lessons
01
Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Remote Write Architecture, Queues, WAL Shipping, Backpressure, and TuningReserved in course structure
Planned
32

Chapter 32

Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs

5 lessons
01
Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-OffsReserved in course structure
Planned
33

Chapter 33

Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits

5 lessons
01
Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and LimitsReserved in course structure
Planned
34

Chapter 34

HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts

5 lessons
01
HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication ConceptsReserved in course structure
Planned
35

Chapter 35

Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns

5 lessons
01
Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Pushgateway, Batch Jobs, Correct Use Cases, and Anti-PatternsReserved in course structure
Planned
36

Chapter 36

OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability

5 lessons
01
OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — OpenMetrics, Exemplars, Trace Correlation, and Standards InteroperabilityReserved in course structure
Planned
37

Chapter 37

SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules

5 lessons
01
SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording RulesReserved in course structure
Planned
38

Chapter 38

Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling

5 lessons
01
Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential HandlingReserved in course structure
Planned
39

Chapter 39

Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation

5 lessons
01
Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Prometheus HTTP API, Metadata API, Query API, Targets API, and AutomationReserved in course structure
Planned
40

Chapter 40

Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality

5 lessons
01
Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Performance Tuning, Query Analysis, Concurrency, Memory, and Large CardinalityReserved in course structure
Planned
41

Chapter 41

Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades

5 lessons
01
Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades: Concepts, Vocabulary, and Mental ModelReserved in course structure
Planned
02
Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades: Guided Configuration and Hands-On WorkflowReserved in course structure
Planned
03
Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure
Planned
04
Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure
Planned
05
Checkpoint Lab — Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and UpgradesReserved in course structure
Planned
42

Chapter 42

Production Capstone: Build, Secure, Scale, Alert, and Recover a Multi-Cluster Prometheus Platform

5 lessons
01
Capstone Requirements, Architecture, SLOs, and Success CriteriaReserved in course structure
Planned
02
Build the End-to-End Monitoring or Delivery EnvironmentReserved in course structure
Planned
03
Integrate Security, Automation, Governance, and ObservabilityReserved in course structure
Planned
04
Inject Failures, Diagnose Behavior, Recover Safely, and Verify StateReserved in course structure
Planned
05
Final Validation, Runbook, Operational Handoff, and Improvement BacklogReserved in course structure
Planned

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