Skip to content

AxonOps — AI-Native Control Plane for Open Source Data Platforms

AxonOps Data Dashboard Metrics Mapping

This document maps the metrics used in the AxonOps Data dashboard.

The Data dashboard provides insights into data storage characteristics including compression ratios, disk space usage, SSTable counts, and partition sizes. It helps monitor data distribution and identify tables with potential issues like large partitions or poor compression.

Dashboard MetricDescriptionAttributes
cas_Table_CompressionRatioCompression effectiveness ratiokeyspace, scope (table), dc, rack, host_id
cas_Table_CompressionMetadataOffHeapMemoryUsedOff-heap memory used by compression metadatakeyspace, scope (table), dc, rack, host_id
Dashboard MetricDescriptionAttributes
cas_Table_LiveDiskSpaceUsedLive data disk space (excludes deleted data)keyspace, scope (table), function=Count, dc, rack, host_id
cas_Table_TotalDiskSpaceUsedTotal disk space including tombstoneskeyspace, scope (table), function=Count, dc, rack, host_id
cas_Table_LiveSSTableCountNumber of live SSTableskeyspace, scope (table), dc, rack, host_id
Dashboard MetricDescriptionAttributes
cas_Table_MinPartitionSizeMinimum partition size in byteskeyspace, scope (table), dc, rack, host_id
cas_Table_MeanPartitionSizeAverage partition size in byteskeyspace, scope (table), dc, rack, host_id
cas_Table_MaxPartitionSizeMaximum partition size in byteskeyspace, scope (table), dc, rack, host_id
cas_Table_CompressionRatio{scope=~'$scope', scope!='', dc=~'$dc',rack=~'$rack',host_id=~'$host_id',keyspace=~'$keyspace'}
cas_Table_CompressionMetadataOffHeapMemoryUsed{scope=~'$scope', scope!='', dc=~'$dc',rack=~'$rack',host_id=~'$host_id',keyspace=~'$keyspace'}
cas_Table_LiveDiskSpaceUsed{function='Count',dc=~'$dc',rack=~'$rack',host_id=~'$host_id',keyspace=~'$keyspace',scope=~'$scope', scope!=''}
cas_Table_TotalDiskSpaceUsed{function='Count',dc=~'$dc',rack=~'$rack',host_id=~'$host_id',keyspace=~'$keyspace',scope=~'$scope'}
cas_Table_LiveSSTableCount{dc=~'$dc',rack=~'$rack',host_id=~'$host_id',scope=~'$scope', scope!=''}
// Minimum
cas_Table_MinPartitionSize{dc=~'$dc',rack=~'$rack',host_id=~'$host_id',scope=~'$scope', scope!=''}
// Mean
cas_Table_MeanPartitionSize{dc=~'$dc',rack=~'$rack',host_id=~'$host_id',scope=~'$scope', scope!=''}
// Maximum
cas_Table_MaxPartitionSize{dc=~'$dc',rack=~'$rack',host_id=~'$host_id',scope=~'$scope', scope!=''}
  • Compression Ratio - Line chart showing compression effectiveness (lower is better)

  • Compression Metadata Off-Heap Memory per Table - Memory overhead of compression

  • Live Disk Space Per Table - Active data size per table

  • Total Disk Space Per Table - Total size including tombstones

  • Live SSTable Count Per Table - Number of SSTables per table

  • Min Partition Size Per Table - Smallest partition in each table

  • Mean Partition Size Per Table - Average partition size

  • Max Row Size Per Table - Largest partition (identifies potential hotspots)

  • data center (dc) - Filter by data center

  • rack - Filter by rack

  • node (host_id) - Filter by specific node

  • keyspace - Filter by keyspace

  • table (scope) - Filter by table

  • Shows how well data compresses
  • Lower values mean better compression
  • Typical values: 0.3-0.5 for text data
  • Depends on compression algorithm and data type
  • Live Space: Only counts active data

  • Total Space: Includes tombstones and deleted data

  • Difference indicates space that can be reclaimed by compaction

  • High counts may indicate:

    • Need for compaction tuning
    • High write load
    • Compaction falling behind
  • Affects read performance (more SSTables = more files to check)

  • Min Size: Usually very small (empty or near-empty partitions)

  • Mean Size: Average across all partitions

  • Max Size: Critical for identifying large partitions

    • Partitions > 100MB can cause performance issues
    • Partitions > 1GB should be investigated

All panels use: $dc - $host_id-$keyspace-$scope

  • Shows data center, node, keyspace, and table
  • Allows easy identification of specific table metrics

Monitor Compression Ratio:

  • Sudden changes may indicate data pattern changes
  • Poor compression might suggest wrong algorithm choice

Watch Disk Space Growth:

  • Compare live vs total space
  • Large differences suggest need for compaction

Track SSTable Counts:

  • Consistently high counts impact read performance
  • May need to adjust compaction strategy

Monitor Partition Sizes:

  • Large partitions (>100MB) need investigation
  • Very large partitions (>1GB) can cause operational issues
  • Consider data model changes for tables with large partitions
  • The scope!='' filter excludes empty table names
  • function='Count' is used for disk space metrics
  • All size metrics use binary units (bytes, not SI units)
  • Partition size metrics are estimates based on sampling