6.3.8.3.5 Monitoring IORM Utilization

You can use metrics to monitor IORM utilization.

When OLTP and DSS workloads share Oracle Exadata Storage Servers, IORM determines whether to optimize for low latency or high throughput. To optimize for low latency, the concurrency of large I/O requests is reduced to ensure that I/O bandwidth is not saturated. To optimize for high throughput, each Oracle Exadata Storage Server must handle many concurrent large I/O requests, allowing the storage to be fully utilized while applying optimization algorithms. However, when a cell has many concurrent large I/O requests, average latency may increase because each I/O is queued behind other I/Os.

The utilization metrics for I/O requests from a database, pluggable database (PDB), or consumer group corresponds to the amount of time that the database, PDB, or consumer group utilized the storage server. Large I/O requests utilize the storage server more than small I/O requests. The following are the utilization metrics for determining IORM optimization:

  • CG_IO_UTIL_LG
  • CG_IO_UTIL_SM
  • PDB_IO_UTIL_LG
  • PDB_IO_UTIL_SM
  • CT_IO_UTIL_LG
  • CT_IO_UTIL_SM
  • DB_IO_UTIL_LG
  • DB_IO_UTIL_SM

By comparing the I/O resource consumption with the I/O resource allocations, the database administrator can determine if IORM should be tuned for latency or throughput, or if a balanced approach is optimal. The IORM metric, IORM_MODE, shows the mode for IORM. The metric value ranges between 1 and 3. The following are the definitions for the values:

Note:

If the current plan has the IORM attribute objective set to BASIC, then IORM_MODE has no meaning and should be ignored.
  • 1 means the cell IORM objective is set to low_latency.
  • 2 means the cell IORM objective is set to balanced.
  • 3 means the cell IORM objective is set to high_throughput.

A value in between 1 and 2, or between 2 and 3, indicates that the IORM objective changed in the metric period, and the precise value indicates proximity to a given objective. It is also indicative of a constantly-changing mix of workloads.