Dt App Notebooks

Dynatrace Notebook Skill

Overview

Dynatrace notebooks are JSON documents stored in the Document Store containing an ordered array of sections — markdown blocks for narrative and dql blocks for DQL queries with visualizations. Sections render top-to-bottom in array order.

When to use: Creating, modifying, querying, or analyzing notebooks.

Notebook JSON Structure

{
  "name": "My Notebook",
  "type": "notebook",
  "content": {
    "version": "7",
    "defaultTimeframe": { "from": "now()-2h", "to": "now()" },
    "sections": [
      { "id": "1", "type": "markdown", "markdown": "# Title" },
      {
        "id": "2", "type": "dql", "title": "Query Section", "showInput": true,
        "state": {
          "input": { "value": "fetch logs | summarize count()" },
          "visualization": "table",
          "visualizationSettings": { "autoSelectVisualization": true, "chartSettings": {} },
          "querySettings": {
            "maxResultRecords": 1000, "defaultScanLimitGbytes": 500,
            "maxResultMegaBytes": 1, "defaultSamplingRatio": 10, "enableSampling": false
          }
        }
      }
    ]
  }
}

• Sections render in array order.
• Section types: markdown, dql. (function exists but is rare.)
• Use string-int IDs ("1", "2", …); UUIDs are also accepted.
• content.defaultTimeframe sets the default timeframe; each section can override via section.state.input.timeframe. Hardcoded time filters in DQL are allowed.

Optional content properties: defaultSegments.

Create/Update Workflow (Mandatory Order)

Carefully follow the workflow described in [references/create-update.md](references/create-update.md).

Key rules:

• Load domain skills BEFORE generating queries — do not invent DQL.
• Validate ALL section queries before adding to the notebook.
• Set name before deploying.
• Prefer autoSelectVisualization: true in visualizationSettings unless the user requested a specific visualization type — when false, state.visualization must be set explicitly.
• Updating — ALWAYS download first: dtctl get notebook -o json --plain > notebook.json, modify, then deploy the downloaded file. Never reconstruct JSON from scratch or inject an id manually — both silently overwrite UI edits the user made since last deployment.
• Deploy with dtctl apply — validation runs automatically, and the local file is deleted on success.

Visualization Types

Notebooks support a subset of Dynatrace visualizations:

• Time-series (require timeseries/makeTimeseries): lineChart, areaChart, barChart, bandChart
• Categorical (summarize ... by:{field}): categoricalBarChart, pieChart, donutChart
• Single value / gauge / meter: singleValue, meterBar, gauge
• Tabular (any data shape): table, raw, recordView
• Distribution/status: histogram, honeycomb
• Geographic maps: choropleth, dotMap, connectionMap, bubbleMap
• Matrix/correlation: heatmap, scatterplot

Required field types per visualization: [references/sections.md](references/sections.md).

References

| File | When to Load | |------|-------------| | [create-update.md](references/create-update.md) | Creating/updating notebooks | | [sections.md](references/sections.md) | Section types, visualization field requirements, settings | | [analyzing.md](references/analyzing.md) | Reading notebooks, extracting queries, purpose identification |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Dynatrace
• Source: Dynatrace/dynatrace-for-ai
• License: Apache-2.0
• Homepage: https://www.dynatrace.com

Install and usage instructions live in the source repository linked above.