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Logs in Nebius AI Cloud support the LogQL query language. You can use LogQL in the Nebius CLI, Grafana® and LogCLI. This page covers the supported syntax with examples and limitations specific to Nebius AI Cloud.

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Stream selectors

Every LogQL query starts with a stream selector inside curly braces. You must always specify the __bucket__ label (or --bucket when using the Nebius AI Cloud CLI) to select the log bucket:
  • sp_serial: Compute virtual machines (serial logs)
  • sp_mk8s_control_plane: Managed Kubernetes clusters (control plane logs)
  • sp_mk8s_audit_logs: Managed Kubernetes clusters (audit logs)
  • sp_mlflow: Managed MLflow clusters
  • sp_postgres: Managed PostgreSQL clusters
  • sp_cloudapps: Standalone Applications
  • sp_k8srelease: applications for Managed Kubernetes
  • default: user-ingested logs
{__bucket__="sp_postgres"}
Supported matching operators:
OperatorDescriptionExample
=Exact match{__bucket__="sp_postgres", container="pgbouncer"}
!=Negation{__bucket__="sp_postgres", container!="pgbouncer"}
=~Regex match{__bucket__="sp_postgres", container=~"pg.*"}
!~Regex negation{__bucket__="sp_postgres", container!~"pgbouncer|odyssey"}

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Line filters

After the stream selector, chain line filters to search the log message text:
OperatorDescriptionExample
|=Line contains text{...} |= "error"
!=Line doesn’t contain text{...} != "healthcheck"
|~Line matches regex{...} |~ "status=5\\d+"
!~Line doesn’t match regex{...} !~ "GET /health"
You can chain multiple filters to narrow results: 
{__bucket__="sp_postgres"} |= "ERROR" != "vacuum"

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Examples

Find deadlocks in PostgreSQL® logs: 
{__bucket__="sp_postgres"} |= "deadlock detected"
Find deadlocks excluding autovacuum-related messages: 
{__bucket__="sp_postgres"} |= "deadlock detected" != "autovacuum"

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Filter by log level

{__bucket__="default"} | level="error"

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Search with regex

Find HTTP 5xx status codes: 
{__bucket__="default"} |~ "status=5\\d+"

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Find slow requests

{__bucket__="default"} | duration > 1s

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Limitations

The LogQL implementation in Nebius AI Cloud has the following limitations:
  • You must always include __bucket__ in the stream selector, or use the --bucket parameter in Nebius AI Cloud CLI commands. Queries without it return no entries.
  • The step value (interval between points) must be smaller than the range value (the interval over which aggregation is performed).
  • Alerts on aggregated metrics values are not supported.
  • The entries with non-empty __error__ value are ignored. As a result, filtering by error is not possible.
  • The following functions are not supported:
    • bytes_rate, bytes_over_time functions
    • absent_over_time (because alerts on aggregated metrics values are not supported)
    • topk, bottomk without aggregation by label (because no entries are shown when labels are empty)
    • sort, sort_desc aggregations
    • without aggregation clauses
    • vector function
    • approx_topk aggregation
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