| name | grafana-query |
| description | Query Grafana for logs, metrics, traces, and alerts from an osparc-simcore deployment. Use when: debugging service errors, checking logs in Loki, querying Prometheus metrics, investigating incidents, finding error patterns, viewing dashboards, checking alert rules, or analyzing service performance. |
| argument-hint | Describe what you want to investigate (e.g., 'errors in webserver last hour', 'memory usage of director-v2') |
Grafana Query
When to Use
- Investigating errors or warnings in simcore services
- Checking service logs for specific events or patterns
- Querying Prometheus metrics (request rates, latencies, resource usage)
- Viewing distributed traces via Tempo
- Checking alert rule state
- Analyzing service performance or resource consumption
IMPORTANT: If you discover that the actual Grafana data (datasource types, label names, log field structures, dashboard names, service naming patterns) is inconsistent with what this skill documents, update the skill files to reflect the correct state. This ensures the skill stays accurate for future invocations.
Datasources
Datasource UIDs differ per deployment. Always discover them dynamically at the start of a query session:
- List all datasources and their UIDs
- Filter by type when needed:
type: "loki", type: "prometheus", type: "tempo"
Expected datasource types in a typical deployment:
| Name pattern | Type | Purpose |
|---|
| loki | Loki | Log aggregation (all service logs) |
| prometheus-federation | Prometheus | Federated metrics (usually the default datasource) |
| prometheus-catchall | Prometheus | Catchall Prometheus metrics |
| tempo | Tempo | Distributed tracing |
| cloudwatch | CloudWatch | AWS infrastructure metrics (RDS, etc.) |
Dashboards
Dashboard UIDs differ per deployment. Always discover them dynamically:
Typical dashboard folders and their contents:
simcore folder
| Title | Purpose |
|---|
| Metrics | Core simcore service metrics |
| Services | Service-level overview |
| Requests load overview | HTTP request load |
| autoscaling overview | Autoscaling status |
| API server log streaming queues | API server queues |
| s4l-lite admin overview | Sim4Life Lite admin |
The Metrics dashboard contains panels for core simcore services. It contains metrics related to resources usage (e.g. RAM and CPU), HTTP request handling statistics and RPC request handling statistics. This is a very useful dashboard to investigate once it has been determined that an error happened within a specific simcore service.
ops folder
| Title | Purpose |
|---|
| Traefik2 | Reverse proxy metrics |
| RabbitMQ Overview | Message broker |
| Redis Overview | Cache/queue |
| Postgres Overview | Database metrics |
| Docker Registries | Registry health |
| AWS RDS Metrics | RDS database |
system folder
| Title | Purpose |
|---|
| Docker Swarm Overview | Cluster overview |
| Nodes - Overview | Host nodes |
| Nodes - Detailed Insights | Per-node deep dive |
Procedure
0. Discover Datasources
Before any query, resolve the datasource UIDs for this deployment.
1. Identify the Target
Determine which service(s) to investigate. The simcore platform services use the naming pattern <stack>_<prefix>_<service> (e.g., simcore_staging_webserver). The exact stack/prefix varies by deployment.
Discover the naming pattern by listing Loki label values.
Common service name patterns:
- Core services:
<stack>_<prefix>_<service> (e.g., *_webserver, *_api-server, *_director-v2)
- Dynamic proxies:
dy-proxy_<node-uuid>
- Dynamic sidecars:
dy-sidecar_<node-uuid>
- Dask:
dask_stack_<component>
Core simcore services:
webserver, api-server, director, director-v2, catalog, dynamic-schdlr, agent, autoscaling, clusters-keeper, resource-usage-tracker, wb-api-server, wb-auth, wb-db-event-listener, wb-garbage-collector, payments, invitations, efs-guardian, datcore-adapter, traefik
2. Query Logs (Loki)
Use the Loki datasource UID discovered in step 0. Available Loki labels:
service_name — service identifier (see naming patterns above)
container_name — Docker container name with replica info
host — host node name
source — log pipeline source (typically vector)
See Log Structure Reference for JSON field details.
3. Query Metrics (Prometheus)
Use the prometheus-federation datasource UID discovered in step 0. Common metric patterns:
- HTTP request metrics from gunicorn/aiohttp
- Service-specific business metrics
- Docker/container resource metrics
4. Query Traces (Tempo)
Use the Tempo datasource UID discovered in step 0. Traces are correlated with logs via log_trace_id and log_span_id fields in log entries.
Common Query Patterns
See Query Patterns Reference for ready-to-use LogQL and PromQL queries.
Last updated: 2026-05-04