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“Master Grafana for Observability: Build Dashboards, Monitor Systems, and Automate Alerts Like a Pro. ”

Grafana is the go-to open-source platform for visualizing, monitoring, and analyzing metrics across diverse data sources. Whether you're an SRE, DevOps engineer, system administrator, or cloud architect, mastering Grafana can significantly boost your observability skills and streamline incident management.

Why Take This Course?

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“Master Grafana for Observability: Build Dashboards, Monitor Systems, and Automate Alerts Like a Pro. ”

Grafana is the go-to open-source platform for visualizing, monitoring, and analyzing metrics across diverse data sources. Whether you're an SRE, DevOps engineer, system administrator, or cloud architect, mastering Grafana can significantly boost your observability skills and streamline incident management.

Why Take This Course?

This is a “Learn by Example” course where I not only explain concepts but also demonstrate them with real-world scenarios. You’ll see each concept in action and follow along by copying and pasting commands directly from my accompanying documentation to replicate the same results.

By the end of this course, you’ll not only understand the fundamentals of Grafana but also have a fully functional Grafana server in the cloud, equipped with SSL, a domain name, and multiple data sources configured—ready for advanced observability tasks.What You’ll Learn:

Installing Grafana using packages and setting up a secure server.Setting Up a Domain Name & SSL Certificate to secure your Grafana instance.Exploring Panel Types – Graphs, Stats, Gauges, Tables, Heatmaps, and Logs.Configuring Multiple Data Sources – MySQL, Zabbix, InfluxDB, Prometheus, and Loki.Setting Up Collection Agents – Telegraf, Promtail, Node Exporters, SNMP Agents, and more.Time Series vs. Non-Time Series Data – Learn key differences and best practices.Experimenting with Dashboards – Use community dashboards and create your own.Monitoring SNMP Devices – Using Telegraf Agents and InfluxDB Data Sources.Integrating Elasticsearch with Filebeat and Metricbeat Services for log management.Annotation Queries and Panel Linking – Link logs and graphs for correlated insights.Dynamic Dashboard Variables & Graphs – Create interactive, responsive dashboards.Using Value Groups/Tags to manage different data sources efficiently.Setting Up Alerts & Notifications – Configure contact points and detect offline devices.Receiving Email Alerts using a local SMTP server for real-time notifications.

Real-World Use Cases Covered:

  • Monitoring Kubernetes Clusters with Prometheus and Grafana.

  • Tracking System Performance with Node Exporters and Telegraf.

  • Configuring SNMP Device Monitoring with InfluxDB.

  • Analyzing Logs and Events from Elasticsearch and Loki.

  • Setting Up Alerting Systems with Email, Slack, and Webhooks.

What You’ll Achieve:

By the end of this course, you will:

  1. Have a dedicated Grafana server hosted in the cloud with SSL and a custom domain.

  2. Configure and manage various data sources and collectors with ease.

  3. Create dynamic dashboards and alerts for a complete observability solution.

  4. Be fully equipped to take your Grafana skills to the next level.

Join me in this hands-on journey where you’ll gain practical experience, sharpen your monitoring and alerting skills, and become a Grafana pro.

Enroll now and start mastering Grafana today.

Enroll now

What's inside

Learning objectives

  • Grafana basics & ui navigation
  • Connecting & managing data sources
  • Building stunning grafana dashboards
  • Query building & data transformation
  • Securing & scaling grafana
  • Real-world use cases & projects

Syllabus

Introduction to Grafana
Introduction - What you will Learn
Meet Grafana: The Artist of Metrics & Logs
Why Use Grafana? Key Features, Benefits, and Comparisons
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Career center

Learners who complete Grafana Masterclass: Observability, Monitoring, Alerts will develop knowledge and skills that may be useful to these careers:
Monitoring Engineer
A Monitoring Engineer specializes in designing, implementing, and maintaining systems that track the performance, availability, and health of IT infrastructure and applications. This role is a direct fit for the Grafana Masterclass. The course provides comprehensive training in leveraging Grafana for visualizing metrics, logs, and traces from diverse sources, including Prometheus, Loki, InfluxDB, and Elasticsearch. Learners gain expertise in creating custom dashboards, configuring collection agents such as Telegraf and Promtail, and setting up advanced alerting and notification systems. This hands-on experience is fundamental for anyone aspiring to build, manage, and optimize sophisticated observability platforms.
Observability Engineer
An Observability Engineer focuses on creating comprehensive insights into the internal states of systems by collecting and analyzing metrics, logs, and traces. This role is a perfect match for the Grafana Masterclass, which emphasizes building a complete observability solution. The course covers integrating various data sources, including time-series data from InfluxDB and logs from Loki and Elasticsearch, and linking them for correlated insights using annotation queries. By mastering dynamic dashboard creation, query building, and advanced alerting, learners are excellently prepared to design and implement robust observability frameworks essential for understanding complex distributed systems.
Site Reliability Engineer
A Site Reliability Engineer ensures that software systems are reliable, available, and performant. This role deeply involves proactively identifying and resolving operational issues, often by leveraging comprehensive monitoring and alerting systems. This Grafana Masterclass is highly relevant, as it provides practical skills in building dynamic dashboards, configuring diverse data sources like Prometheus and Loki, and setting up real-time alerts. Mastering Grafana, as taught in this course, helps one excel in analyzing system metrics, logs, and traces to prevent incidents and respond effectively when they occur, directly contributing to maintaining critical service uptime and optimizing system health.
Application Performance Management Specialist
An Application Performance Management Specialist focuses on monitoring and managing the performance and availability of software applications. This involves tracking key metrics, identifying bottlenecks, and ensuring a seamless user experience. The Grafana Masterclass provides excellent preparation for this role, teaching how to configure Grafana with various data sources relevant to application components, such as databases and servers. Expertise in building real-time dashboards to visualize application health, analyzing logs, and setting up alerts for performance degradation or errors, as thoroughly covered in this course, is fundamental for proactive application management and rapid incident resolution.
DevOps Engineer
A DevOps Engineer streamlines the software development lifecycle, focusing on automation, infrastructure as code, and continuous integration and deployment. A core aspect of this role is ensuring the operational health and performance of deployed applications and infrastructure. This course equips future DevOps Engineers with hands-on experience in using Grafana for observability, monitoring Kubernetes clusters and system performance with agents like Telegraf and Node Exporters, and configuring robust alerting systems. These skills are essential for proactive incident management, performance optimization, and integrating monitoring into the CI/CD pipeline, making the course a foundational step for those aiming to excel in this dynamic field.
Infrastructure Engineer
An Infrastructure Engineer designs, builds, and maintains the fundamental technology components that support an organization's applications and services. A critical part of this responsibility involves ensuring the health and performance of the underlying infrastructure. The Grafana Masterclass offers practical skills in monitoring key infrastructure components, from servers to databases like MySQL and SNMP devices, using various collection agents. Learning to configure a secure Grafana instance, integrate multiple data sources, and create real-time dashboards and alerts is invaluable for proactively managing infrastructure health, optimizing resource utilization, and responding swiftly to operational issues.
Platform Engineer
A Platform Engineer builds and maintains the tooling, infrastructure, and services that enable development teams to build and deploy applications efficiently. Central to this role is ensuring the reliability and performance of the underlying platform components. The Grafana Masterclass provides crucial skills in establishing comprehensive observability for platform services, including Kubernetes clusters with Prometheus, and monitoring system performance with Node Exporters and Telegraf. Mastering dynamic dashboard creation, query building, and advanced alerting, as taught in this course, is vital for Platform Engineers to provide robust, self-service monitoring capabilities and maintain high operational standards.
System Administrator
A System Administrator is responsible for the upkeep, configuration, and reliable operation of computer systems, especially multi-user computers such as servers. Ensuring system stability, performance, and security heavily relies on robust monitoring capabilities. The Grafana Masterclass directly addresses these needs by teaching how to install and secure Grafana servers, configure data sources for various systems like MySQL and SNMP devices, and create insightful dashboards to visualize real-time server states. Developing expertise in setting up alerts for offline devices and performance anomalies, as covered in this course, is invaluable for maintaining efficient and resilient IT infrastructure.
Cloud Architect
A Cloud Architect designs and oversees the cloud computing strategy of an organization, including infrastructure, platforms, and software. In a distributed cloud environment, comprehensive observability is crucial for performance, cost optimization, and reliability. This course, by teaching how to host a Grafana server in the cloud with SSL and custom domains, and integrate with various data sources relevant to cloud services like Prometheus for Kubernetes monitoring, provides practical experience. Understanding how to build dynamic dashboards and configure alerts for complex cloud environments, as detailed in the Grafana Masterclass, is vital for designing resilient, scalable, and highly observable cloud solutions.
Data Visualization Specialist
A Data Visualization Specialist focuses on transforming complex data into clear, insightful visual representations that aid decision-making. Grafana is a powerful tool for this purpose, specifically for operational and time-series data. This Grafana Masterclass is highly relevant by teaching how to build stunning Grafana dashboards, explore various panel types like graphs, stats, gauges, tables, and heatmaps, and integrate multiple data sources. The course's emphasis on creating dynamic dashboards with variables and leveraging advanced querying for data transformation provides essential skills for anyone aiming to craft compelling and interactive data visualizations for monitoring or analytical purposes.
Network Operations Center Analyst
A Network Operations Center Analyst monitors network and system health around the clock, identifying and addressing issues to ensure continuous service availability. This role heavily relies on dashboarding and alerting tools to gain real-time insights into infrastructure performance. The Grafana Masterclass may be useful by teaching how to configure data sources for system performance, visualize time-series data, and set up alerts for critical events, including detecting offline devices. These skills help build a foundational understanding of how to interpret complex operational data and respond to automated notifications, which is essential for ensuring network and system uptime.
Operations Analyst
An Operations Analyst examines an organization's operational data to identify trends, inefficiencies, and areas for improvement. In technology-driven operations, this often involves interpreting system health and performance metrics. The Grafana Masterclass may be useful by providing practical skills in using Grafana to create dashboards for visualizing operational data, monitoring real-time system states, and configuring alerts for anomalies. This course can help build a foundation in data interpretation and visualization for operational contexts, enabling an Operations Analyst to better assess system performance, understand underlying issues, and contribute to data-driven operational decision-making.
Technical Support Engineer Level Three
A Technical Support Engineer Level Three handles complex technical issues, requiring deep diagnostic skills and the ability to interpret system behaviors. Analyzing logs, metrics, and performance dashboards is often key to resolving high-level problems. This Grafana Masterclass may be useful by teaching how to configure and interpret Grafana dashboards for monitoring system performance and analyzing logs from sources like Elasticsearch and Loki. Gaining proficiency in annotation queries and panel linking for correlated insights can significantly enhance a Technical Support Engineer Level Three's ability to quickly identify root causes and provide effective solutions for critical incidents.
Database Administrator
A Database Administrator is responsible for the performance, integrity, and security of databases. Proactive monitoring of database health and query performance is essential for maintaining efficient data operations. This Grafana Masterclass may be useful by providing hands-on experience in setting up Grafana for MySQL database monitoring, including preparing dashboards to visualize database load and performance metrics. Learning to integrate various data sources and configure real-time alerts can significantly enhance a Database Administrator's ability to identify bottlenecks, troubleshoot issues, and ensure the continuous availability and optimal performance of critical database systems.
Software Engineer - Backend
A Software Engineer Backend designs, builds, and maintains the server-side logic and databases that power applications. While primarily focused on code, understanding how to monitor the performance and reliability of these systems in production is increasingly important. This Grafana Masterclass may be useful by providing insights into visualizing application metrics, analyzing logs through Loki and Elasticsearch, and understanding how alerting systems function. These skills can help a Software Engineer Backend design more observable applications and collaborate effectively with operations teams, ensuring their backend services are robust, performant, and easily diagnosable in production environments.

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Grafana Masterclass: Observability, Monitoring, Alerts.
Seminal work on the grammar of graphics, a formal language for describing data visualizations. It covers a wide range of topics, from the basics of the grammar of graphics to the use of the grammar of graphics to create a variety of charts and graphs.
This classic book by Edward Tufte must-read for anyone interested in data visualization. It covers a wide range of topics, from the principles of visual perception to the design of effective charts and graphs.
Authoritative instruction from core maintainers Julien Pivotto and Brian Brazil covers client instrumentation, counters, gauges, native histograms, PromQL vector matching, relabeling, and Alertmanager routing. Updated second-edition chapters detail TLS security, remote write, and OpenMetrics.
Covering the modern LGTM observability stack—Loki for logs, Grafana for visualization, Tempo for distributed traces, and Mimir for long-term Prometheus metrics—Rob Chapman guides engineers through end-to-end telemetry correlation. Practical labs demonstrate unified alerting, service graphs, and continuous profiling with Pyroscope.
Borgmon time-series rules, the Four Golden Signals of latency, traffic, errors, and saturation, and symptom-based alerting laid the direct architectural foundation for Prometheus. Google's SRE authors explain why whitebox metrics and error budgets outperform cause-based paging.
Updated for Grafana 10's redesigned panel transformations, dynamic dashboard variables, and unified alerting engine, Eric Salituro walks readers from initial installation to enterprise multi-tenant governance. Step-by-step tutorials connect time-series databases, relational stores, and cloud monitoring APIs.
Is specifically dedicated to the topic of logging and log management, offering a comprehensive overview of the field, including its business aspects, technical challenges, and best practices. It is an authoritative guide for anyone looking to gain a deep and broad understanding of log management as a discipline. It must-read for professionals and students focusing on this area.
Is considered a foundational text in the field of observability. It provides a comprehensive overview of what observability is, how it differs from traditional monitoring, and its importance in modern software systems. It's highly valuable for gaining a broad understanding and must-read for anyone serious about the topic. The book also discusses the cultural shifts required for adopting observability practices within an organization.
Presents the results of a four-year study of high-performing technology organizations. It identifies the key factors that drive success, and it provides a roadmap for organizations that want to improve their performance.
Recording rules, Prometheus Operator deployments on Kubernetes, Grafana dashboard provisioning, and long-term remote storage with Thanos and Cortex receive lab-driven walkthroughs. Bastos and Araujo show how to test alerting expressions and scale federation.
Designed for DevOps engineers and system administrators building their first real-time operational dashboards, Ronald McCollam explains data source provisioning, panel selection, template variables, and annotation overlays. Readers learn how to avoid dashboard clutter while surfacing actionable Golden Signals.
Direct fit for understanding the application of log management in network security. It covers the principles and practices of network security monitoring, where logs are a critical data source for detecting and responding to threats. It's a highly practical guide for implementing a network security monitoring strategy that relies heavily on log analysis.
As OpenTelemetry is the emerging standard for cloud-native observability, this book is highly relevant for contemporary practices. It offers a practical guide to setting up and operating OpenTelemetry, covering tracing, metrics, and logging. It's a must-read for those implementing observability with open standards.
Step-by-step configuration of node exporter, blackbox exporter, pushgateway, and service discovery helps systems engineers stand up their first production Prometheus server. James Turnbull walks through writing PromQL queries and routing notifications to Slack and PagerDuty.
Distinguishing static threshold dashboards from exploratory high-cardinality debugging, Charity Majors, Liz Fong-Jones, and George Miranda establish the modern theory of cloud-native observability. Grafana practitioners apply these concepts when linking exemplar metrics directly to Tempo traces and Loki logs.
This comprehensive textbook provides a solid foundation in cloud computing concepts, architectures, and technologies. It covers a wide range of topics, including cloud infrastructure, resource management, security, and applications.
Focuses on applying observability specifically in cloud-native environments, which contemporary and highly relevant topic. It covers using open-source tools like OpenTelemetry, Prometheus, and Grafana. It's a practical guide for those working with cloud-native applications.
Error-budget burn rates and latency quantile histograms turn raw Prometheus time series into user-centric reliability targets. Alex Hidalgo explains how to design meaningful SLIs, avoid misleading averages, and configure multi-window Alertmanager rules.
Provides a comprehensive overview of data visualization, covering the basics of visual perception, data types, and chart types. It great resource for beginners who want to learn the fundamentals of data visualization.
This handbook provides a step-by-step guide to implementing DevOps in your organization. It covers all aspects of DevOps, from planning to implementation to measurement, and it valuable resource for anyone looking to get started with DevOps.
Complementing other OpenTelemetry books, this resource specifically targets cloud-native environments and emphasizes the combination of tracing, metrics, and logging. It is highly relevant for contemporary cloud deployments and provides practical guidance on using OpenTelemetry effectively.
Addressing modern container orchestration at scale, Vikram Venkataraman demonstrates how OpenTelemetry standardization, Prometheus metric collection, eBPF profiling, and Grafana dashboards unify cluster visibility. Chapters also examine multi-cloud telemetry pipelines and automated AIOps troubleshooting across microservices.
This handbook concise reference for cybersecurity incident responders and heavily relies on the analysis of logs and other security data. It provides practical guidance on using logs during incident investigation and response, making it directly relevant to the application of log management in a security context. It's a useful reference tool for those focused on the defensive side of cybersecurity.
Offers insights into how Google manages large-scale systems, with a strong emphasis on monitoring and automation, both highly relevant to advanced log management strategies. It delves into the principles and practices of SRE, providing a framework for building reliable systems where logging plays a vital role in observability and incident response. It's a key text for understanding modern IT operations and the context of log management within it.
Incident response critical process that heavily utilizes log data to understand the scope and nature of a security incident. provides a practical approach to incident response, detailing how to use various data sources, including logs, to investigate and remediate security breaches. It's an important book for understanding the role of log analysis in the incident response lifecycle.
Another book dedicated to distributed tracing, this offers a comprehensive guide from a key figure in the OpenTracing and Jaeger projects. It delves into the theoretical foundations and practical implementation of tracing at scale. It's excellent for deepening understanding and strong reference.
Provides a practical guide to adopting OpenTelemetry across an organization, focusing on the value and implementation challenges. It's a good resource for understanding how to integrate OpenTelemetry into existing systems and workflows.
Concrete alerting formulas—including multi-window, multi-burn-rate PromQL expressions—translate theoretical SRE principles into daily monitoring configurations. Worked examples demonstrate how to eliminate low-value pages and measure monitoring precision and recall.
While not exclusively focused on log management, this book provides a fundamental understanding of system and network administration, which is crucial prerequisite knowledge for effective log management. It covers best practices in IT operations, including monitoring and management, laying a solid foundation. valuable reference for anyone involved in system administration, offering broad coverage of essential topics.
Provides a collection of case studies from organizations that have successfully implemented DevOps. It covers a wide range of industries and organizational sizes, and it provides valuable insights into the challenges and rewards of DevOps.
Offers a strategic approach to implementing observability within an enterprise setting, addressing planning and execution. It's useful for understanding the organizational aspects and challenges of adopting observability at scale.
Provides a comprehensive overview of cloud infrastructure security. It covers topics such as access control, data protection, and incident response.
This practical guide offers a comprehensive overview of cloud computing, covering both technical and business aspects. It includes real-world examples and case studies to illustrate how cloud computing can be used to solve business problems.
Provides a comprehensive guide to deployment automation, a key part of the DevOps process. It covers the tools, techniques, and best practices for automating deployments, and it valuable resource for anyone looking to improve their deployment process.
Dynamic pod scheduling in Kubernetes made static IP monitoring obsolete and drove the widespread adoption of Prometheus label-based service discovery. Burns, Beda, Hightower, and Evenson explain container health probes, kube-state-metrics, and cluster autoscaling signals.
Vendor-neutral and battle-tested, Mike Julian's guide teaches anti-patterns in alert fatigue, dashboard hierarchy design for executives versus on-call engineers, and metric retention strategies. Teams adopting Grafana gain a clear blueprint for what to measure and why.
For those working with Kubernetes, this book connects observability with security, highlighting their combined importance in cloud-native applications. It offers a holistic view and is valuable for understanding the role of observability in a secure Kubernetes environment.
Misused radial gauges, garish color palettes, and pie charts obscure critical anomalies during high-pressure production incidents. Stephen Few grounds dashboard layout in human visual perception so engineers can spot spikes and correlations at a single glance.
Introduces various tools and techniques used by cybersecurity blue teams, many of which involve the collection, analysis, and utilization of logs for security monitoring and defense. It provides an overview of different security tools and their relationship to log data, making it a valuable resource for understanding the practical application of log management in a defensive security posture.
Scaling Prometheus across multi-cluster enterprise Kubernetes environments requires careful tuning of ServiceMonitors, Thanos sidecars, and TSDB memory footprints. Rosso and colleagues detail production observability topologies for high-churn container platforms.
Beyond basic scraping, large deployments demand sharding, federation, Thanos global querying, and remote write tuning. William Hegedus guides operators through TSDB debugging, Jsonnet monitoring mixins, CI pipeline validation, SLO alerting, and OpenTelemetry ingestion.
Before metrics or structured logs reach a Grafana panel, teams must build resilient pipelines for emitting, shipping, and sanitizing high-volume operational signals. Jamie Riedesel addresses centralized logging architecture, cardinality explosions, PII compliance, and multi-tenant telemetry budgeting at scale.
Provides a guide to continuous delivery on AWS. It covers the tools, techniques, and best practices for deploying and scaling AWS applications.
Splunk widely used SIEM and log management platform. provides practical guidance on using Splunk for collecting, searching, analyzing, and visualizing log data. While specific to Splunk, it offers valuable hands-on experience with a leading log management tool and demonstrates key concepts in practice. It's particularly useful for those focusing on tool-specific log management skills.
Focuses on the security challenges faced by cloud computing environments. It covers topics such as cloud security architecture, threat modeling, and incident response.
Provides a comprehensive overview of serverless architectures, a new cloud computing paradigm that allows developers to build and deploy applications without managing servers. It covers topics such as serverless functions, event-driven programming, and microservices.
Focuses on the use of cloud computing for big data applications. It covers topics such as data storage, processing, and analytics.

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