dt-obs-gcp — Claude Code skill for GCP resources in Dynatrace
A skill that writes DQL queries against GCP resources in Dynatrace Smartscape: inventory, topology, access audits. Useful when you need to see what actually runs in GCP.
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-gcp -a claude-codeWhat dt-obs-gcp does
The skill teaches the agent to query GCP entities in Dynatrace. Every resource carries a GCP_* prefix and lives in Smartscape, so queries are built on the smartscapeNodes function. Four core patterns cover most cases: listing resources by type with a project or region filter, parsing the JSON config out of the gcp.object field, traversing relationships between entities, and grouping by tags:gcp_labels.
For specific services the skill loads a reference file from references/: Compute Engine, GKE, Cloud Run, VPC and DNS, Pub/Sub, IAM and Secret Manager, monitoring, plus project and ownership management. GKE clusters pull in references/kubernetes-gke.md, networking pulls in references/networking-dns.md. That keeps the context small — the agent reads one section instead of everything.
The skill works on data Dynatrace has already collected from your GCP project. If resources are not modeled in Smartscape, queries come back empty, and that is a reason to check your GCP monitoring setup rather than the skill. Relationship traversals use "*" as the relationship name because GCP entities have no named relationship types.
What it helps with
- list Compute Engine VMs by project and zone
- pull machine type and status out of the
gcp.objectJSON - traverse from a VM to its subnetwork
- group resources by label to find an owner
- check role bindings and service accounts
Example prompts for the agent
- List every Compute Engine instance in project
<PROJECT_ID>with zones and statuses - Load
references/kubernetes-gke.mdand map the GKE cluster topology - Group GCP resources by
tags:gcp_labelsand show which ones have no labels
How to install dt-obs-gcp
1Skills CLI (Vercel)
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-gcp -a claude-code2Manually: put the files in place
~/.claude/skills/dt-obs-gcp/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/dt-obs-gcp/
1Skills CLI (Vercel)
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-gcp -a codex2Manually: put the files in place
.agents/skills/dt-obs-gcp/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-gcp -a cursor2Manually: put the files in place
.cursor/skills/dt-obs-gcp/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install Dynatrace/dynatrace-for-ai dt-obs-gcp2Manually: put the files in place
.github/skills/dt-obs-gcp/SKILL.md1Skills CLI (Vercel)
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-gcp -a gemini-cli2Platform CLI
gemini skills install https://github.com/Dynatrace/dynatrace-for-ai --path skills/dt-obs-gcpManually: put the files in place
.devin/skills/dt-obs-gcp/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-gcp -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about dt-obs-gcp
How do I install dt-obs-gcp in Claude?
Run npx skills add Dynatrace/dynatrace-for-ai --skill dt-obs-gcp -a claude-code. The skill file lands at ~/.claude/skills/dt-obs-gcp/SKILL.md.
What does dt-obs-gcp do?
It gives the agent DQL query patterns for GCP resources in Dynatrace Smartscape: inventory, config parsing, relationship traversal and label grouping. Service-specific queries come from reference files under references/.
Why do my queries return nothing?
The skill reads what Dynatrace has already collected from your GCP project. If resources are not modeled in Smartscape, a query finds nothing — check your GCP monitoring setup.
Source text
SKILL.md · Apache-2.0
---
name: dt-obs-gcp
description: 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.
license: Apache-2.0
---
# GCP Cloud Infrastructure
Monitor and analyze GCP resources using Dynatrace Smartscape and DQL. Query GCP services, manage organizational hierarchy, audit security posture, and track resource ownership across your GCP infrastructure.
## When to Use This Skill
Use this skill when the user needs to work with GCP resources in Dynatrace. Load the reference file for the task type:
| Task | File to load |
|---|---|
| Inventory and topology queries | (no additional file — use core patterns above) |
| Compute Engine instances, machine types, IP addresses | Load `references/compute-instances.md` |
| GKE clusters, node pools, pods, deployments, services, RBAC | Load `references/kubernetes-gke.md` |
| Cloud Run services, revisions, executions | Load `references/serverless-containers.md` |
| VPC networks, subnets, routes, DNS records | Load `references/networking-dns.md` |
| Pub/Sub topics | Load `references/messaging-pubsub.md` |
| IAM service accounts, roles, Secret Manager | Load `references/iam-security.md` |
| Monitoring dashboards, logging, saved queries | Load `references/monitoring-logging.md` |
| GCP projects, regions, organizational hierarchy | Load `references/resource-management.md` |
| Resource ownership, GCP labels, organizational structure | Load `references/resource-ownership.md` |
---
## Core Concepts
### Entity Types
GCP resources use the `GCP_*` prefix and can be queried using the `smartscapeNodes` function. All GCP entities are automatically discovered and modeled in Dynatrace Smartscape.
**Compute:** `GCP_COMPUTE_GOOGLEAPIS_COM_INSTANCE`, `GCP_COMPUTE_GOOGLEAPIS_COM_ADDRESS`
**Networking:** `GCP_COMPUTE_GOOGLEAPIS_COM_NETWORK`, `GCP_COMPUTE_GOOGLEAPIS_COM_SUBNETWORK`, `GCP_COMPUTE_GOOGLEAPIS_COM_ROUTE`, `GCP_DNS_GOOGLEAPIS_COM_RESOURCERECORDSET`
**Kubernetes (GKE):** `GCP_K8S_IO_POD`, `GCP_K8S_IO_NODE`, `GCP_K8S_IO_SERVICE`, `GCP_K8S_IO_SERVICEACCOUNT`, `GCP_K8S_IO_PERSISTENTVOLUMECLAIM`, `GCP_APPS_K8S_IO_DEPLOYMENT`, `GCP_APPS_K8S_IO_STATEFULSET`, `GCP_CONTAINER_GOOGLEAPIS_COM_NODEPOOL`, `GCP_RBAC_AUTHORIZATION_K8S_IO_CLUSTERROLEBINDING`, `GCP_RBAC_AUTHORIZATION_K8S_IO_ROLEBINDING`
**Serverless:** `GCP_RUN_GOOGLEAPIS_COM_SERVICE`, `GCP_RUN_GOOGLEAPIS_COM_REVISION`, `GCP_RUN_GOOGLEAPIS_COM_EXECUTION`
**IAM & Security:** `GCP_IAM_GOOGLEAPIS_COM_SERVICEACCOUNT`, `GCP_IAM_GOOGLEAPIS_COM_ROLE`, `GCP_SECRETMANAGER_GOOGLEAPIS_COM_SECRETVERSION`
**Messaging:** `GCP_PUBSUB_GOOGLEAPIS_COM_TOPIC`
**Monitoring:** `GCP_MONITORING_GOOGLEAPIS_COM_DASHBOARD`, `GCP_LOGGING_GOOGLEAPIS_COM_SAVEDQUERY`
**Infrastructure:** `GCP_REGION`
### Common GCP Fields
All GCP entities include:
- `gcp.project.id` — GCP project identifier
- `gcp.region` — GCP region (e.g., us-central1)
- `gcp.zone` — GCP zone (e.g., us-central1-a)
- `gcp.organization.id` — GCP organization identifier
- `gcp.resource.name` — Resource name
- `gcp.resource.type` — Resource type identifier
- `gcp.asset.type` — GCP asset type
- `gcp.object` — JSON blob containing full resource configuration
### GCP Organizational Hierarchy
GCP resources are organized in a hierarchy:
- **Organization** — Top-level container (`gcp.organization.id`)
- **Folder** — Logical grouping within an organization
- **Project** — Resource container (`gcp.project.id`)
- **Region/Zone** — Physical location (`gcp.region`, `gcp.zone`)
### Entity Naming Convention
GCP entity types follow the pattern `GCP_<SERVICE_API>_<RESOURCE>`:
- Service API maps to the Google API domain (e.g., `compute.googleapis.com` → `COMPUTE_GOOGLEAPIS_COM`)
- Resource is the specific resource type (e.g., `INSTANCE`, `NETWORK`)
Examples:
- `GCP_COMPUTE_GOOGLEAPIS_COM_INSTANCE` — Compute Engine VM
- `GCP_K8S_IO_POD` — GKE pod
- `GCP_RUN_GOOGLEAPIS_COM_SERVICE` — Cloud Run service
---
## Query Patterns
All GCP queries build on four core patterns. Master these and adapt them to any entity type.
### Pattern 1: Resource Discovery
List resources by type, filter by project/region/zone, summarize counts:
```dql
smartscapeNodes "GCP_COMPUTE_GOOGLEAPIS_COM_INSTANCE"
| fields name, gcp.project.id, gcp.region, gcp.zone, gcp.resource.name
```
To list all GCP resource types, replace with `"GCP_*"` and add `| summarize count = count(), by: {type} | sort count desc`. Add filters like `| filter gcp.project.id == "<PROJECT_ID>"` or `| filter gcp.region == "<REGION>"` to scope results.
### Pattern 2: Configuration Parsing
Parse `gcp.object` JSON for detailed configuration fields:
```dql
smartscapeNodes "GCP_COMPUTE_GOOGLEAPIS_COM_INSTANCE"
| parse gcp.object, "JSON:gcpjson"
| fieldsAdd machineType = gcpjson[configuration][resource][machineType],
status = gcpjson[configuration][resource][status]
| fields name, gcp.project.id, machineType, status
```
GCP configuration fields are nested under `gcpjson[configuration][resource][...]` for primary resource attributes and `gcpjson[configuration][additionalAttributes][...]` for extended properties.
### Pattern 3: Relationship Traversal
Follow relationships between resources:
```dql
smartscapeNodes "GCP_COMPUTE_GOOGLEAPIS_COM_INSTANCE"
| traverse "*", "GCP_COMPUTE_GOOGLEAPIS_COM_SUBNETWORK"
| fields name, gcp.project.id
```
GCP entities use `"*"` as the relationship name in traversals because GCP entities do not have named relationship types. Use `fieldsKeep` to carry fields through traversals and `dt.traverse.history[-N]` to access ancestor fields.
### Pattern 4: Label-Based Ownership
Group resources by GCP labels for ownership and organizational tracking:
```dql
smartscapeNodes "GCP_*"
| filter isNotNull(`tags:gcp_labels`)
| fields name, gcp.project.id, `tags:gcp_labels`
```
GCP labels are exposed via the `tags:gcp_labels` field and must be accessed using backtick syntax. Replace `"GCP_*"` with a specific type to scope to one service.
---
## Reference Guide
Load reference files for detailed queries when the core patterns above need service-specific adaptation.
| Reference | When to load | Key content |
|---|---|---|
| [compute-instances.md](references/compute-instances.md) | Compute Engine VMs, machine types, IP addresses, disks | Instance inventory, machine type distribution, status checks |
| [kubernetes-gke.md](references/kubernetes-gke.md) | GKE clusters, node pools, pods, deployments, services, RBAC | Cluster topology, workload distribution, RBAC bindings |
| [serverless-containers.md](references/serverless-containers.md) | Cloud Run services, revisions, executions | Service inventory, revision tracking, execution analysis |
| [networking-dns.md](references/networking-dns.md) | VPC networks, subnets, routes, DNS records | Network topology, subnet analysis, route tables, DNS record sets |
| [messaging-pubsub.md](references/messaging-pubsub.md) | Pub/Sub topics | Topic inventory, messaging topology |
| [iam-security.md](references/iam-security.md) | IAM service accounts, roles, Secret Manager | Service account audit, role analysis, secret version tracking |
| [monitoring-logging.md](references/monitoring-logging.md) | Monitoring dashboards, logging, saved queries | Dashboard inventory, saved query analysis |
| [resource-management.md](references/resource-management.md) | GCP projects, regions, organizational hierarchy | Project inventory, region distribution, hierarchy mapping |
| [resource-ownership.md](references/resource-ownership.md) | Resource ownership, GCP labels, organizational structure | Label-based grouping, project-level summaries, chargeback |
---
## Best Practices
### Configuration Parsing
1. Always parse `gcp.object` with JSON parser: `parse gcp.object, "JSON:gcpjson"`
2. Access primary resource attributes via `gcpjson[configuration][resource][...]`
3. Access extended properties via `gcpjson[configuration][additionalAttributes][...]`
4. Check for null values after parsing with `isNotNull()`
### GCP Hierarchy
1. Organization → Folder → Project → Region/Zone
2. Use `gcp.project.id` as the primary scoping filter
3. Use `gcp.organization.id` for cross-project queries
4. Use `gcp.region` and `gcp.zone` for location-based analysis
### Entity Naming
1. Entity types follow the `GCP_<SERVICE_API>_<RESOURCE>` format
2. Service API maps to the Google API domain with underscores replacing dots and hyphens
3. Use specific entity types (avoid `"GCP_*"` wildcards when possible)
### Labels
1. GCP labels must be accessed via backtick syntax: `` `tags:gcp_labels` ``
2. Use `isNotNull(`tags:gcp_labels`)` for label-based filtering
3. Track label coverage with summarize operations
### Relationship Traversal
1. Use `"*"` as the relationship name — GCP entities do not have named relationship types
2. Use `fieldsKeep` to maintain important fields through traversal
3. Access traversal history with `dt.traverse.history[-N]`
4. Complex topologies may require multiple traverse operations
---
## Limitations and Notes
### Smartscape Limitations
- Smartscape data reflects the most recent scan; there may be a delay between GCP changes and Dynatrace visibility
- Not all GCP services are represented as entity types
- Some configuration fields may be null depending on resource setup
- Resource discovery depends on GCP integration configuration
### GCP-Specific Notes
- GCP labels must be accessed via backtick syntax: `` `tags:gcp_labels` ``
- GCP entities use `"*"` for relationship traversal (no named relationship types)
- GCP object configuration requires parsing with `parse gcp.object, "JSON:gcpjson"`
- Configuration fields nest under `gcpjson[configuration][resource][...]` (differs from AWS pattern)
### General Tips
- Filter early by project and region for better performance
- Use `isNotNull()` and `isNull()` for graceful null handling
- Combine project and region filters for large environments
- Use `countDistinct()` for unique resource counts
- Limit results with `| limit N` during exploration
© Dynatrace · Apache-2.0 · Dynatrace/dynatrace-for-ai