AxonOps Application Dashboard Metrics Mapping

This document maps the metrics used in the AxonOps Application dashboard to their corresponding sources.

Dashboard Overview

The Application dashboard provides visibility into client application interactions with Cassandra, including throughput metrics (reads, writes, batches) and connection information. It helps monitor application-level performance and usage patterns.

Metrics Mapping

Throughput Metrics

Dashboard Metric	Source	Description	Attributes
client_throughput_read	Client metrics	Read operations throughput	username, remoteIP, keyspace, table, dc, rack, host_id
client_throughput_write	Client metrics	Write operations throughput	username, remoteIP, keyspace, table, dc, rack, host_id
client_throughput_batch_logged	Client metrics	Logged batch operations	username, remoteIP, keyspace, table, dc, rack, host_id
client_throughput_batch_counter	Client metrics	Counter batch operations	username, remoteIP, keyspace, table, dc, rack, host_id
client_throughput_batch_unlogged	Client metrics	Unlogged batch operations	username, remoteIP, keyspace, table, dc, rack, host_id

Connection Metrics

Dashboard Metric	Description	Attributes
cas_Client_connectedNativeClients	Number of connected native protocol clients	dc, rack, host_id
cas_authentication_success	Successful authentication attempts	username, dc, rack, host_id

Query Examples

Reads per Second

sum by(remoteIP, username, keyspace, table) (client_throughput_read{axonfunction='rate',dc=~'$dc',rack=~'$rack',host_id=~'$host_id',keyspace=~'$keyspace', table=~'$scope'})

Writes per Second

sum by (remoteIP, username, keyspace, table) (client_throughput_write{axonfunction='rate',dc=~'$dc',rack=~'$rack',host_id=~'$host_id',keyspace=~'$keyspace', table=~'$scope'})

Logged Batches per Second

client_throughput_batch_logged{axonfunction='rate',dc=~'$dc',rack=~'$rack',host_id=~'$host_id',keyspace=~'$keyspace', table=~'$scope'}

Native Connections

ceil(cas_Client_connectedNativeClients{dc=~'$dc',rack=~'$rack',host_id=~'$host_id'})

Successful Authentications Rate

sum(cas_authentication_success{axonfunction='rate',dc=~'$dc',rack=~'$rack',host_id=~'$host_id'}) by (username)

Panel Types and Descriptions

Throughput Section

• Reads/sec - Line chart showing read operations per second by user, IP, keyspace, and table

• Writes/sec - Line chart showing write operations per second by user, IP, keyspace, and table

• Batches/sec (logged) - Line chart showing logged batch operations per second

• Batches/sec (counter) - Line chart showing counter batch operations per second

• Batches/sec (unlogged) - Line chart showing unlogged batch operations per second

Connections Section

• Native connections - Line chart showing number of connected native protocol clients

• Successful Authentications by user (rate) - Line chart showing authentication success rate by username

Filters

• data center (dc) - Filter by data center

• rack - Filter by rack

• node (host_id) - Filter by specific node

• username - Filter by client username

• keyspace - Filter by keyspace

• table (scope) - Filter by table

Metric Details

Client Throughput Metrics

• Track operations at the application level
• Include client identity (username, IP address)
• Provide keyspace and table level granularity
• Use axonfunction='rate' to calculate per-second rates

Connection Metrics

• connectedNativeClients shows current connection count
• authentication_success tracks login attempts
• Both metrics help monitor client access patterns

Legend Format

The dashboard uses descriptive legends combining multiple attributes:

• Throughput: $username @ $remoteIP $keyspace $table
• Connections: $dc - $host_id
• Authentication: $username

Notes

1. Client throughput metrics provide application-level visibility not available in standard Cassandra metrics
2. These metrics help identify heavy users, problematic applications, or unusual access patterns
3. The ceil() function is used for connection counts to ensure whole numbers
4. Batch type separation (logged/unlogged/counter) helps monitor different write patterns
5. Remote IP tracking enables geographic or network-based analysis of client access