Skip to content

Commit bc82f87

Browse files
authored
Merge pull request #103229 from amanjeetsingh/patch-4
Dedicated SQL pool - added note about CPU trends
2 parents 347bbbb + 527f4f4 commit bc82f87

File tree

1 file changed

+3
-0
lines changed

1 file changed

+3
-0
lines changed

articles/synapse-analytics/monitoring/how-to-monitor-using-azure-monitor.md

Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -63,6 +63,9 @@ Here are some of the metrics emitted by dedicated SQL pools created in Azure Syn
6363
| WLGEffectiveCapResourcePercent | Effective cap resource percent | Percent | Max (default), Min, Avg | The effective cap resource percent for the workload group. If there are other workload groups with min_percentage_resource > 0, the effective_cap_percentage_resource is lowered proportionally |
6464
| WLGEffectiveMinResourcePercent | Effective min resource percent | Percent | Max (default), Min, Avg, Sum | The effective min resource percentage setting allowed considering the service level and the workload group settings. The effective min_percentage_resource can be adjusted higher on lower service levels |
6565

66+
> [!NOTE]
67+
> Dedicated SQL pool measures performance in compute data warehouse units (cDWUs). Even though we do not surface details of individual nodes such as memory per node or number of CPUs per node, the intent behind emitting metrics such as `MemoryUsedPercent`; `CPUPercent` etc. is to show general usage trend over a period of time. These trends will help administrators understand how an instance of dedicated SQL pool is utilized, and changes in footprint of memory and/or CPU could be a trigger for one or more actions such as scale-up or scale-down cDWUs, investigating a query (or queries) which may require optimization, etcetera.
68+
6669
### Apache Spark pool metrics
6770

6871
Here are some of the metrics emitted by Apache Spark pools:

0 commit comments

Comments
 (0)