Advanced Monitoring

The Advanced Monitoring feature provides deep, granular performance metrics, resource utilization analytics, and system health insights for IBM® Netezza® Performance Server for IBM Cloud Pak® for Data as a Service. Dashboard components cover query workload analytics, infrastructure utilization, storage consumption, database maintenance, and object usage statistics, all from a single interface.

Access and prerequisites

Advanced Monitoring is available to administrator accounts only. Non-administrator users do not have visibility or access to these metrics.

To enable Advanced Monitoring:

  1. Navigate to the Administration page.
  2. Locate the Monitoring Dashboard tile.
  3. Toggle the Advanced Monitoring setting to ON.

Once enabled, navigate to the Monitoring Dashboard page, scroll to the bottom of the interface, and select the Advanced Monitoring tab.

Infrastructure Advanced Monitoring

For AWS SaaS and BYOC deployments that use the Lakehouse Unstructured feature, an Infrastructure Advanced Monitoring tile is also available on the Administration page. This tile provides infrastructure-level metrics specific to the Lakehouse Unstructured workload.

To access Infrastructure Advanced Monitoring:

  1. Navigate to the Administration page.
  2. Locate the Infrastructure Advanced Monitoring tile.
  3. Select the tile to open the infrastructure monitoring view.

This feature is available on AWS SaaS and BYOC deployments only.

Dashboard components

Performance and workload analytics

The following charts are available in the Performance and Workload Analytics section.

Query Summary
A line chart that plots total, submitted, completed, and failed query counts. Used to infer query throughput and track daily query volumes.
Performance Analysis
A line chart that plots average queue time (seconds) versus date, and average and maximum run time versus date. Evaluates total query processing time by aggregating queue and execution latency.
Type Analysis
A stacked bar chart that plots the total volume of queries categorized by specific query types.
Insert Operation Breakdown
A stacked bar chart that shows the volume breakdown of write operations, segmenting INSERT, INSERT (LOAD), and INSERT (SINGLETON) operations.
Success vs. Failure Rate
An area graph that plots query success rate versus query failure rate over time.
Workload Distribution by Query Type
A pie chart that shows average query type distribution across the system.

Infrastructure performance

Four independent heatmaps plot maximum utilization metrics across an Hour x Date matrix to isolate resource bottlenecks.

CPU Utilization
Plots host CPU performance and SPU CPU performance.
Memory Utilization
Plots host memory allocation and SPU memory allocation.

Storage and database metrics

Top 5 databases by size
A data table that identifies and tracks the capacity of the top five largest databases by storage volume.

Database maintenance statistics

The following maintenance statistics are available.

Last Backup Details
Summary for the most recent backup operation.
Last Vacuum Details
Summary for the most recent database vacuum operation.
Versioned Tables
Tracks table versioning overhead and history.
Skewed Tables
Identifies data distribution imbalances across cluster nodes.
Tables Needing Groom
Flags tables that require data reorganization, space reclamation, or cleanup.
Tables Needing Genstat
Identifies tables requiring updated statistics generation for the query optimizer.

Object usage statistics

Object usage statistics identify the most heavily targeted database objects to assist with indexing and schema optimization.

Most Projected Tables
Tables frequently referenced in select or projection blocks.
Most Predicated Tables
Tables frequently used in conditional filters and WHERE clauses.
Most Projected Columns
Specific columns frequently scanned or retrieved.
Most Predicated Columns
Specific columns frequently used in query predicates.