// Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations.
| name | dt-app-dashboards |
| description | Work with Dynatrace dashboards - create, modify, query, and analyze dashboard JSON including tiles, layouts, DQL queries, variables, and visualizations. |
| license | Apache-2.0 |
Dynatrace dashboards are JSON documents stored in the Document Store containing tiles (content/visualizations), layouts (grid positioning), and variables (dynamic query parameters).
When to use: Creating, modifying, querying, or analyzing dashboards.
{
"name": "My Dashboard",
"type": "dashboard",
"content": {
"version": 21,
"variables": [],
"tiles": { "<id>": { "type": "data|markdown", ... } },
"layouts": { "<id>": { "x": 0, "y": 0, "w": 24, "h": 8 } }
}
}
tiles must match IDs in layoutsmarkdown (text content) and data (DQL query + visualization)Optional content properties: settings, refreshRate, annotations
Carefully follow the workflow described in references/create-update.md.
Key rules:
name before deployingdtctl get dashboard <id> -o json --plain > dashboard.json, modify, then deploy the downloaded file. Never reconstruct JSON from scratch or inject an id manually — both silently overwrite any UI edits the user made since last deployment.timeseries/makeTimeseries): lineChart, areaChart, barChart, bandChartsummarize ... by:{field}): categoricalBarChart, pieChart, donutChartsingleValue, meterBar, gaugetable, raw, recordListhistogram, honeycombchoroplethMap, dotMap, connectionMap, bubbleMapheatmap, scatterplotRequired field types per visualization: references/tiles.md
{ "version": 2, "key": "Service", "type": "query", "visible": true,
"editable": true, "input": "smartscapeNodes SERVICE | fields name",
"multiple": false }
filter service.name == $Servicefilter in(service.name, array($Service))query (DQL-populated), csv (static list), text (free-form)Full variable reference: references/variables.md
| File | When to Load |
|---|---|
| create-update.md | Creating/updating dashboards |
| tiles.md | Tile types, visualization field requirements, settings |
| variables.md | Variable types, replacement strategies, patterns |
| analyzing.md | Reading dashboards, extracting queries, health assessment |
Work with Dynatrace notebooks - create, modify, query, and analyze notebook JSON. Derives from the dt-app-dashboards skill with notebook-specific differences documented here.
Core DQL syntax rules, common pitfalls, and query patterns. Load this skill when you need to write, build, or fix a DQL query — it prevents syntax errors and guides correct usage. Covers fetch commands, data models, field namespaces, time alignment, entity patterns, metric discovery, and smartscape topology navigation. Trigger: "write a DQL query", "build me a query", "DQL syntax", "how do I query logs/spans/metrics in Dynatrace", "create a timeseries", "fix my DQL", "fetch logs", "smartscapeNodes", "query optimization". Do NOT use for explaining an existing query or answering Dynatrace product questions — those do not require query-construction guidance.
Migrate Dynatrace classic and Gen2 entity-based DQL to Smartscape equivalents. Covers three scenarios. (1) mass data queries filtered by classic entity conditions — migrate to direct dimension filters first, Smartscape only as fallback; (2) mass data queries using entity subqueries for filtering — same dimension-first strategy; (3) pure entity list queries — migrate fetch dt.entity.* to smartscapeNodes. Also handles entityName, entityAttr, classicEntitySelector, and classic relationship patterns.
AWS cloud resource monitoring including EC2, RDS, Lambda, ECS/EKS, VPC networking, load balancers, S3, DynamoDB, SQS/SNS, and cost optimization. Use when analyzing AWS infrastructure, resource inventory, security compliance, capacity planning, or cost savings. Trigger: "show EC2 instances", "find RDS databases", "VPC resources", "AWS cost optimization", "Lambda functions", "ECS services", "security groups", "unattached EBS volumes", "AWS load balancer topology", "publicly accessible databases", "AWS dashboards". Do NOT use for explaining existing queries, product documentation questions, generic host CPU/memory metrics (use dt-obs-hosts), application-level tracing (use dt-obs-tracing), or log analysis (use dt-obs-logs).
Azure cloud resources including VMs, VMSS, SQL Database, Storage, AKS, App Service, Functions, VNet networking, load balancers, Event Hubs, Container Apps, and Key Vault. Monitor Azure infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across subscriptions and resource groups.
GCP cloud resources including Compute Engine, GKE, Cloud Run, Pub/Sub, VPC networking, DNS, IAM, Secret Manager, and monitoring. Monitor GCP infrastructure, analyze resource usage, audit security posture, and manage organizational hierarchy across projects and folders.