Course structure available

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.

Browse curriculum View all chapters

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.

Chapter 1

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

5 lessons

Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Metrics, Time-Series Monitoring, Observability, and Prometheus Foundations: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Metrics, Time-Series Monitoring, Observability, and Prometheus FoundationsReserved in course structure

Planned

Chapter 2

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

5 lessons

Prometheus 3.x Architecture, Components, Data Model, and Release Strategy: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Prometheus 3.x Architecture, Components, Data Model, and Release Strategy: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Prometheus 3.x Architecture, Components, Data Model, and Release Strategy: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Prometheus 3.x Architecture, Components, Data Model, and Release Strategy: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Prometheus 3.x Architecture, Components, Data Model, and Release StrategyReserved in course structure

Planned

Chapter 3

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

5 lessons

Installing Prometheus, Docker Images, Distroless Options, and Lab Setup: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Installing Prometheus, Docker Images, Distroless Options, and Lab Setup: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Installing Prometheus, Docker Images, Distroless Options, and Lab Setup: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Installing Prometheus, Docker Images, Distroless Options, and Lab Setup: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Installing Prometheus, Docker Images, Distroless Options, and Lab SetupReserved in course structure

Planned

Chapter 4

Configuration Files, Global Settings, Scrape Configs, and Reloading

5 lessons

Configuration Files, Global Settings, Scrape Configs, and Reloading: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Configuration Files, Global Settings, Scrape Configs, and Reloading: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Configuration Files, Global Settings, Scrape Configs, and Reloading: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Configuration Files, Global Settings, Scrape Configs, and Reloading: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Configuration Files, Global Settings, Scrape Configs, and ReloadingReserved in course structure

Planned

Chapter 5

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

5 lessons

Targets, Scraping, Pull Model, HTTP Exposition, and Target Health: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Targets, Scraping, Pull Model, HTTP Exposition, and Target Health: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Targets, Scraping, Pull Model, HTTP Exposition, and Target Health: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Targets, Scraping, Pull Model, HTTP Exposition, and Target Health: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Targets, Scraping, Pull Model, HTTP Exposition, and Target HealthReserved in course structure

Planned

Chapter 6

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

5 lessons

Metric Names, Labels, Samples, Timestamps, and Time-Series Identity: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Metric Names, Labels, Samples, Timestamps, and Time-Series Identity: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Metric Names, Labels, Samples, Timestamps, and Time-Series Identity: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Metric Names, Labels, Samples, Timestamps, and Time-Series Identity: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Metric Names, Labels, Samples, Timestamps, and Time-Series IdentityReserved in course structure

Planned

Chapter 7

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

5 lessons

Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Counter, Gauge, Histogram, Summary, Info, and StateSet Metric Semantics: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Counter, Gauge, Histogram, Summary, Info, and StateSet Metric SemanticsReserved in course structure

Planned

Chapter 8

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

5 lessons

Instrumentation Design, RED, USE, Golden Signals, and Metric Naming: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Instrumentation Design, RED, USE, Golden Signals, and Metric Naming: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Instrumentation Design, RED, USE, Golden Signals, and Metric Naming: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Instrumentation Design, RED, USE, Golden Signals, and Metric Naming: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Instrumentation Design, RED, USE, Golden Signals, and Metric NamingReserved in course structure

Planned

Chapter 9

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

5 lessons

Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Prometheus Client Libraries for Go, Python, Java, Node.js, and .NET: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Prometheus Client Libraries for Go, Python, Java, Node.js, and .NETReserved in course structure

Planned

Chapter 10

Exporters, node_exporter, blackbox_exporter, and Integration Patterns

5 lessons

Exporters, node_exporter, blackbox_exporter, and Integration Patterns: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Exporters, node_exporter, blackbox_exporter, and Integration Patterns: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Exporters, node_exporter, blackbox_exporter, and Integration Patterns: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Exporters, node_exporter, blackbox_exporter, and Integration Patterns: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Exporters, node_exporter, blackbox_exporter, and Integration PatternsReserved in course structure

Planned

Chapter 11

Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata

5 lessons

Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Relabeling Fundamentals, Target Relabeling, Labels, and Discovery MetadataReserved in course structure

Planned

Chapter 12

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

5 lessons

Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion Control: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Metric Relabeling, Sample Filtering, Label Cleanup, and Ingestion ControlReserved in course structure

Planned

Chapter 13

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

5 lessons

PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range Queries: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — PromQL Foundations, Selectors, Matchers, Ranges, and Instant/Range QueriesReserved in course structure

Planned

Chapter 14

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

5 lessons

PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

PromQL Operators, Vector Matching, one-to-one, many-to-one, and Joins: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — PromQL Operators, Vector Matching, one-to-one, many-to-one, and JoinsReserved in course structure

Planned

Chapter 15

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

5 lessons

PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

PromQL Functions, Rates, Increases, Deltas, Resets, and Derivatives: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — PromQL Functions, Rates, Increases, Deltas, Resets, and DerivativesReserved in course structure

Planned

Chapter 16

Aggregation, topk, quantile, count_values, and Dimensional Analysis

5 lessons

Aggregation, topk, quantile, count_values, and Dimensional Analysis: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Aggregation, topk, quantile, count_values, and Dimensional Analysis: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Aggregation, topk, quantile, count_values, and Dimensional Analysis: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Aggregation, topk, quantile, count_values, and Dimensional Analysis: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Aggregation, topk, quantile, count_values, and Dimensional AnalysisReserved in course structure

Planned

Chapter 17

Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles

5 lessons

Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Histograms, Buckets, histogram_quantile, Native Histograms, and PercentilesReserved in course structure

Planned

Chapter 18

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

5 lessons

Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Subqueries, offset, @ Modifier, Time Functions, and Historical Comparison: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Subqueries, offset, @ Modifier, Time Functions, and Historical ComparisonReserved in course structure

Planned

Chapter 19

Absent Data, Staleness, Missing Series, and Defensive PromQL

5 lessons

Absent Data, Staleness, Missing Series, and Defensive PromQL: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Absent Data, Staleness, Missing Series, and Defensive PromQL: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Absent Data, Staleness, Missing Series, and Defensive PromQL: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Absent Data, Staleness, Missing Series, and Defensive PromQL: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Absent Data, Staleness, Missing Series, and Defensive PromQLReserved in course structure

Planned

Chapter 20

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

5 lessons

Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Recording Rules, Rule Groups, Evaluation Intervals, and Query Acceleration: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Recording Rules, Rule Groups, Evaluation Intervals, and Query AccelerationReserved in course structure

Planned

Chapter 21

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

5 lessons

Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert Design: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Alerting Rules, for, keep_firing_for, Labels, Annotations, and Alert DesignReserved in course structure

Planned

Chapter 22

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

5 lessons

Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and Silences: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Alertmanager Architecture, Routing Tree, Grouping, Inhibition, and SilencesReserved in course structure

Planned

Chapter 23

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

5 lessons

Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and Templates: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Alertmanager Receivers, Webhooks, Email, Slack, PagerDuty Concepts, and TemplatesReserved in course structure

Planned

Chapter 24

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

5 lessons

Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic Targets: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Service Discovery: Static, File, DNS, Consul, Cloud, and Dynamic TargetsReserved in course structure

Planned

Chapter 25

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

5 lessons

Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and Relabeling: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Kubernetes Service Discovery, Pods, Services, Endpoints, Nodes, and RelabelingReserved in course structure

Planned

Chapter 26

Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs

5 lessons

Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDsReserved in course structure

Planned

Chapter 27

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

5 lessons

kube-prometheus-stack Architecture, Components, and Production Deployment: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

kube-prometheus-stack Architecture, Components, and Production Deployment: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

kube-prometheus-stack Architecture, Components, and Production Deployment: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

kube-prometheus-stack Architecture, Components, and Production Deployment: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — kube-prometheus-stack Architecture, Components, and Production DeploymentReserved in course structure

Planned

Chapter 28

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

5 lessons

TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and Index: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — TSDB Internals, WAL, Head Block, Chunks, Blocks, Compaction, and IndexReserved in course structure

Planned

Chapter 29

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

5 lessons

Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity Planning: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Retention by Time/Size, Storage Sizing, Disk I/O, and Capacity PlanningReserved in course structure

Planned

Chapter 30

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

5 lessons

Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Cardinality, Churn, High-Cardinality Labels, and Metric Cost Control: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Cardinality, Churn, High-Cardinality Labels, and Metric Cost ControlReserved in course structure

Planned

Chapter 31

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

5 lessons

Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Remote Write Architecture, Queues, WAL Shipping, Backpressure, and Tuning: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Remote Write Architecture, Queues, WAL Shipping, Backpressure, and TuningReserved in course structure

Planned

Chapter 32

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

5 lessons

Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-Offs: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Remote Read, Long-Term Storage, Thanos/Mimir/Cortex Concepts, and Trade-OffsReserved in course structure

Planned

Chapter 33

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

5 lessons

Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and Limits: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Federation, Hierarchical Prometheus, Cross-Cluster Aggregation, and LimitsReserved in course structure

Planned

Chapter 34

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

5 lessons

HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication Concepts: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — HA Prometheus Pairs, Duplicate Samples, External Labels, and Deduplication ConceptsReserved in course structure

Planned

Chapter 35

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

5 lessons

Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Pushgateway, Batch Jobs, Correct Use Cases, and Anti-Patterns: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Pushgateway, Batch Jobs, Correct Use Cases, and Anti-PatternsReserved in course structure

Planned

Chapter 36

OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability

5 lessons

OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — OpenMetrics, Exemplars, Trace Correlation, and Standards InteroperabilityReserved in course structure

Planned

Chapter 37

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

5 lessons

SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording Rules: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — SLOs, SLIs, Error Budgets, Burn Rates, Multi-Window Alerting, and Recording RulesReserved in course structure

Planned

Chapter 38

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

5 lessons

Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential Handling: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Security, TLS, Basic Auth, OAuth2, Bearer Tokens, and Credential HandlingReserved in course structure

Planned

Chapter 39

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

5 lessons

Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Prometheus HTTP API, Metadata API, Query API, Targets API, and Automation: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Prometheus HTTP API, Metadata API, Query API, Targets API, and AutomationReserved in course structure

Planned

Chapter 40

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

5 lessons

Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Performance Tuning, Query Analysis, Concurrency, Memory, and Large Cardinality: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Performance Tuning, Query Analysis, Concurrency, Memory, and Large CardinalityReserved in course structure

Planned

Chapter 41

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

5 lessons

Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades: Concepts, Vocabulary, and Mental ModelReserved in course structure

Planned

Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades: Guided Configuration and Hands-On WorkflowReserved in course structure

Planned

Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades: Design Patterns, Trade-Offs, and Production DecisionsReserved in course structure

Planned

Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and Upgrades: Security, Diagnostics, Failure Modes, and TroubleshootingReserved in course structure

Planned

Checkpoint Lab — Backup, Snapshots, WAL Recovery, Corruption, Disaster Recovery, and UpgradesReserved in course structure

Planned

Chapter 42

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

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

You will be able to

42 chapters in prerequisite order.

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

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

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

Configuration Files, Global Settings, Scrape Configs, and Reloading

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

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

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

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

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

Exporters, node_exporter, blackbox_exporter, and Integration Patterns

Relabeling Fundamentals, Target Relabeling, Labels, and Discovery Metadata

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

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

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

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

Aggregation, topk, quantile, count_values, and Dimensional Analysis

Histograms, Buckets, histogram_quantile, Native Histograms, and Percentiles

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

Absent Data, Staleness, Missing Series, and Defensive PromQL

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

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

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

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

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

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

Prometheus Operator, ServiceMonitor, PodMonitor, PrometheusRule, and CRDs

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

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

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

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

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

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

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

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

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

OpenMetrics, Exemplars, Trace Correlation, and Standards Interoperability

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

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

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

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

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

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

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