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dt-app-dashboards

Create, modify, query, and analyze Dynatrace dashboard JSON with tiles, layouts, DQL queries, and variables.

Updated Dec 12, 2025
Search Tags:#monitoring#dashboard#observability#visualization#dql#dtctl#dynatrace
One-click install
npx skills add https://github.com/ricardojjulia/ESACompanion --skill dt-app-dashboards-ricardojjulia
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dt-app-dashboards
Source: https://github.com/ricardojjulia/ESACompanion/tree/main/.github/skills/dt-app-dashboards
Command: npx skills add https://github.com/ricardojjulia/ESACompanion --skill dt-app-dashboards-ricardojjulia

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve? Building and maintaining Dynatrace dashboards requires precise JSON structure, valid DQL queries, correct visualization field types, and careful update workflows that preserve user edits. This Skill provides the operational knowledge to create, modify, query, and analyze dashboards without inventing invalid queries or overwriting server state. ## Core Features & Use Cases - Dashboard Creation & Updates: Follows a mandatory 7-step workflow including DQL validation with dtctl, downloading existing dashboards before updates, and deploying with dtctl apply. - Visualization Guidance: Maps visualization types (lineChart, donutChart, singleValue, heatmap, maps, and more) to required DQL output field types so tiles render correctly. - Variable Configuration: Defines query, text, and CSV variables with correct reference syntax, modifiers, and default values for dynamic dashboard filtering. - Dashboard Analysis: Extracts queries, resolves variables, and assesses dashboard purpose and health from fetched JSON. - Use Case: A user asks to build a service health dashboard showing response time, error counts, and event categories. The Skill loads domain knowledge, validates each DQL query, constructs the JSON with matching tiles and layouts, and deploys it with dtctl apply. ## Quick Start Ask the assistant to create a Dynatrace dashboard showing service response times and error counts using validated DQL queries.

Frequently Asked Questions about dt-app-dashboards

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create a Dynatrace dashboard with DQL queries?▼

Define the dashboard purpose, explore available data fields, plan tiles and layouts, then validate every DQL query with dtctl query before constructing the JSON. Deploy the finished dashboard with dtctl apply, which runs validation automatically.

How do I update an existing Dynatrace dashboard without losing changes?▼

Always download the current dashboard first with dtctl get dashboard <id> -o json --plain, modify that downloaded file, and redeploy it. Building fresh JSON or injecting an id manually overwrites any UI edits made since the last deployment.

Which visualization type should I use for categorical data in Dynatrace dashboards?▼

Use categoricalBarChart, pieChart, or donutChart for values grouped by categories from summarize queries. Note that barChart is a time-series chart requiring a timestamp axis, so it fails validation when used with category-only data.

How do dashboard variables work in Dynatrace DQL queries?▼

Variables are defined in content.variables and referenced as $key in tile queries. Single-select uses field == $Var, multi-select uses in(field, array($Var)), and modifiers like :noquote or :backtick handle numeric parameters and field names.

Why does my Dynatrace dashboard tile render blank or fail validation?▼

Tiles fail when the query output field types do not match the visualization requirements, such as missing interval fields for timeseries charts or timestamp axes in heatmaps. Validate queries with dtctl query and check the field type requirements for your chosen visualization.

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