From dynatrace
Queries and analyzes GCP infrastructure in Dynatrace: Compute Engine, GKE, Cloud Run, Pub/Sub, VPC, DNS, IAM, Secret Manager, monitoring dashboards, and organizational hierarchy.
How this skill is triggered — by the user, by Claude, or both
Slash command
/dynatrace:dt-obs-gcpThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
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.
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.
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 |
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
All GCP entities include:
gcp.project.id — GCP project identifiergcp.region — GCP region (e.g., us-central1)gcp.zone — GCP zone (e.g., us-central1-a)gcp.organization.id — GCP organization identifiergcp.resource.name — Resource namegcp.resource.type — Resource type identifiergcp.asset.type — GCP asset typegcp.object — JSON blob containing full resource configurationGCP resources are organized in a hierarchy:
gcp.organization.id)gcp.project.id)gcp.region, gcp.zone)GCP entity types follow the pattern GCP_<SERVICE_API>_<RESOURCE>:
compute.googleapis.com → COMPUTE_GOOGLEAPIS_COM)INSTANCE, NETWORK)Examples:
GCP_COMPUTE_GOOGLEAPIS_COM_INSTANCE — Compute Engine VMGCP_K8S_IO_POD — GKE podGCP_RUN_GOOGLEAPIS_COM_SERVICE — Cloud Run serviceAll GCP queries build on four core patterns. Master these and adapt them to any entity type.
List resources by type, filter by project/region/zone, summarize counts:
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.
Parse gcp.object JSON for detailed configuration fields:
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.
Follow relationships between resources:
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.
Group resources by GCP labels for ownership and organizational tracking:
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.
Load reference files for detailed queries when the core patterns above need service-specific adaptation.
| Reference | When to load | Key content |
|---|---|---|
| compute-instances.md | Compute Engine VMs, machine types, IP addresses, disks | Instance inventory, machine type distribution, status checks |
| kubernetes-gke.md | GKE clusters, node pools, pods, deployments, services, RBAC | Cluster topology, workload distribution, RBAC bindings |
| serverless-containers.md | Cloud Run services, revisions, executions | Service inventory, revision tracking, execution analysis |
| networking-dns.md | VPC networks, subnets, routes, DNS records | Network topology, subnet analysis, route tables, DNS record sets |
| messaging-pubsub.md | Pub/Sub topics | Topic inventory, messaging topology |
| iam-security.md | IAM service accounts, roles, Secret Manager | Service account audit, role analysis, secret version tracking |
| monitoring-logging.md | Monitoring dashboards, logging, saved queries | Dashboard inventory, saved query analysis |
| resource-management.md | GCP projects, regions, organizational hierarchy | Project inventory, region distribution, hierarchy mapping |
| resource-ownership.md | Resource ownership, GCP labels, organizational structure | Label-based grouping, project-level summaries, chargeback |
gcp.object with JSON parser: parse gcp.object, "JSON:gcpjson"gcpjson[configuration][resource][...]gcpjson[configuration][additionalAttributes][...]isNotNull()gcp.project.id as the primary scoping filtergcp.organization.id for cross-project queriesgcp.region and gcp.zone for location-based analysisGCP_<SERVICE_API>_<RESOURCE> format"GCP_*" wildcards when possible)`tags:gcp_labels`isNotNull(tags:gcp_labels) for label-based filtering"*" as the relationship name — GCP entities do not have named relationship typesfieldsKeep to maintain important fields through traversaldt.traverse.history[-N]`tags:gcp_labels`"*" for relationship traversal (no named relationship types)parse gcp.object, "JSON:gcpjson"gcpjson[configuration][resource][...] (differs from AWS pattern)isNotNull() and isNull() for graceful null handlingcountDistinct() for unique resource counts| limit N during explorationnpx claudepluginhub dynatrace/dynatrace-for-ai --plugin dynatraceQueries GCP Asset Inventory API for resource discovery, label/tag coverage audits, stale or orphaned resource detection, change history review, and inventory reports across projects and folders.
Provides deep expertise on production GCP workloads: IAM/Workload Identity, VPC networking, GKE/Cloud Run, Cloud SQL/Spanner/Bigtable/BigQuery, Pub/Sub, security/observability with Cloud Armor/KMS/Logging/Monitoring, and cost optimization.
Provides GCP observability best practices: structured JSON logging, query filters, metrics/logs/traces guidance, alert policies, and log cost optimization.