> For the complete documentation index, see [llms.txt](https://docs.e6data.com/query-engine/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.e6data.com/query-engine/guides/deployment/azure-in-vpc/run-first-query.md).

# Run first query

Validate an Azure In-VPC e6data install by verifying the workspace pods, then running your first query.

Validate the install in two passes: confirm the workspace components are healthy, then run a query.

## Verify the workspace

```bash
kubectl get pods -n <WORKSPACE_NAME>
```

A healthy deployment shows `console-*`, `envoy-*`, `xds-*`, and the metadata service pods (`mds-schema-*`, `mds-storage-*`) all `Running`. Metadata service pods may take 1–2 minutes to appear after the workspace configuration is created. Confirm the query-router LoadBalancer has an external IP:

```bash
kubectl get svc -n <WORKSPACE_NAME>
```

## Run a query

1. Open the Console at your configured hostname (`https://<CONSOLE_HOSTNAME>`).
2. In the SQL Editor, select your cluster and a catalog.
3. Run a simple query against a table you can see:

```sql
SELECT * FROM your_catalog.your_schema.your_table LIMIT 10;
```

If results return, your Azure In-VPC deployment is working end to end.

## If something fails

See [Troubleshooting](/query-engine/guides/deployment/azure-in-vpc/troubleshooting.md) for pods stuck pending, image pull errors, the load balancer not getting an external IP, Workload Identity annotation issues, and stuck namespace termination.

## Next steps

* [Component versions and operations](/query-engine/guides/deployment/azure-in-vpc/component-versions-and-operations.md) - ongoing operations and upgrades.
* [Query editor](/query-engine/guides/querying/query-editor.md) - write and run queries.


---

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