Confident Grafana navigation - You will learn how to move confidently through Grafana, set up the environment, and choose between OSS, Enterprise, and Cloud based on your team's actual needs.
Connecting multiple data sources - You will learn how to connect and use PostgreSQL, Prometheus, Elasticsearch, Zabbix, and TestData to build dashboards that combine data from different systems.
Preparing data for visualization - You will practice queries, expressions, transformations, panel options, and overrides, so you can shape raw data into views that are clear and useful in daily work.
Choosing the right visualizations - You will learn when to use Time series, Table, Stat, Gauge, GeoMap, and other panel types, so your dashboards present data clearly and support faster decisions.
Dynamic dashboards with variables - You will master variables, use them in queries and panels, and apply repeat panels, so you can build flexible dashboards that adapt to the data scope you select.
Effective alerts and notifications - You will create your own alerts, configure Contact Points, Notification Policies, and Silence and Mute settings, so you can detect issues faster and control escalation better.
Stronger Prometheus skills - You will grasp Prometheus architecture, its data model, PromQL, and recording rules, so you can prepare efficient metrics for Grafana dashboards and alerting.
More reliable administration - You will learn how to work with plugins, organizations, users, teams, and authentication methods, helping you manage Grafana more securely and troubleshoot with confidence.
Grafana itself is introduced through the interface, initial configuration steps, and the process of starting the platform in a working environment. The section also compares OSS, Enterprise, and Cloud editions so participants can relate features and deployment models to usage needs.
Grafana connects to multiple back ends, and each source brings its own query style and data structure. This section positions TestData, PostgreSQL, Prometheus, Elasticsearch, and Zabbix in practical terms, showing what role they play when building dashboards and examples.
Before data becomes readable on a dashboard, it must be shaped correctly inside the panel workflow. The section covers queries, expressions, and transforms, then moves to panel options and overrides that control how the same dataset is finally rendered and differentiated.
Choosing the right panel type has a direct impact on how quickly users interpret data. This module works through Time series, Bar chart, Gauge, Pie chart, Bar gauge, Table, Stat, State timeline, and GeoMap, matching each visualization to suitable analytical scenarios.
Plugins extend Grafana beyond the default feature set by adding new data sources, panels, and application components. Participants learn the main plugin categories, go through installation and configuration steps, and apply selected extensions while building dashboards.
From a user reporting perspective, dashboards must be easy to organize, reuse, and navigate. The section addresses folders, playlists, tags and links, along with dashboard import and export, and shows how annotations add operational context directly to presented data.
Dynamic dashboards depend on variables that adapt queries and panel content to current context. This section covers major variable types, their use in expressions and visual components, and repeat-based layouts that generate a changing number of panels from selected values.
Building a usable alerting flow requires more than defining a threshold. Here the focus is on creating alert rules, assigning recipients through Contact Points, shaping escalation with Notification Policies, and controlling noise through Silence and Mute mechanisms.
Prometheus provides Grafana with a metric-oriented data model built around time series and labels. The training explains its architecture, introduces core metric concepts and PromQL syntax, and shows how query results are translated into readable visualizations for monitoring use cases.
Recording rules help move repeated calculations out of dashboard queries and into precomputed metrics. Participants examine the Grafana operating model for these rules, then use the resulting series in panels and alerts to improve consistency, reuse, and execution efficiency.
Using Elasticsearch as a Grafana source requires a different approach than classic metric systems. The section covers retrieving data from documents, deriving metrics from indexed content, and presenting both raw documents and aggregated values in panels suited to operational analysis.
Zabbix integration in Grafana relies on understanding how items, hosts, and host groups map to queries and panel content. Participants work with the plugin model and learn how to present monitoring metrics in dashboards that reflect the underlying Zabbix structure.
Administrative work in Grafana links access control with the platform’s organizational structure. This part explains how organizations, users, and teams are managed, and how authentication methods affect account provisioning, permissions, and day-to-day operation of shared environments.
When dashboards or alerts do not behave as expected, effective diagnosis depends on checking the full path from data source to panel logic. The section focuses on identifying common Grafana issues, isolating configuration errors, and verifying queries, permissions, integrations, and runtime behavior.
Basic data literacy - You should understand what metrics, records, tables, and fields are, so you can work efficiently with data coming from databases, monitoring tools, and logs.
Query basics - You should have basic experience reading or writing simple queries, such as SQL or filtering expressions, because the course includes hands-on work with source data.
IT monitoring fundamentals - You should be familiar with the basics of monitoring systems and services, so it is easier for you to understand metrics, alerts, data sources, and practical examples.
Comfortable computer use - You should be comfortable using a web browser, an operating system, and basic application settings, because the training is practical and requires independent work.
