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Cassandra monitoring integration

Our Cassandra integration sends performance metrics and inventory data from your Cassandra database to the New Relic platform. You can view pre-built dashboards of your Cassandra metric data, create alert policies, and create your own custom queries and charts.

Read on to install the integration and to see what data we collect.

Tip

Instrument your Cassandra database quickly and send your telemetry data with guided install. Our guided install uses our infrastructure agent and our CLI to set up the Cassandra integration, and discovers other applications and log sources running in your environment and then recommends which ones you should instrument. The guided install works with most setups. But if it doesn't suit your needs, there are other install options below.

Ready to get started? Click the relevant button, depending on which data center region you use. When you're done with the install, return to this documentation to review the configuration options.

Guided install, US region

For a more permanent and scalable solution, we recommend the standard manual install of the agent: keep reading for how to do that.

Important

This integration doesn't automatically update. For best results, regularly update the integration package and the infrastructure agent.

Configuration options

For the standard on-host installation, this integration comes with a YAML config file, cassandra-config.yml. This configuration is where you can place required login credentials and configure how data is collected. Which options you change depends on your setup and preferences. It comes with a sample config file cassandra-config.yml.sample that you can copy and edit.

Specific settings related to Cassandra are defined using the env section of the configuration file. These settings control the connection to your Cassandra instance as well as other security settings and features. The list of valid settings is described in the next section of this document.

Cassandra configuration options

The Cassandra integration collects both metrics(M) and inventory(I) information. In the table, use the Applies To column for the settings available to each collection:

Setting

Description

Default

Applies to

HOSTNAME

Hostname or IP where Cassandra is running.

localhost

M/I

PORT

Port on which Cassandra is listening.

7199

M

USERNAME

Username for accessing JMX.

N/A

M

PASSWORD

Password for the given user.

N/A

M

CONFIG_PATH

Path to the Cassandra configuration file.

/etc/cassandra/
cassandra.yaml

I

COLUMN_FAMILIES_LIMIT

Limit on number of Cassandra Column Families.

20

M

TIMEOUT

Request timeout in milliseconds.

2000

M

KEY_STORE

The filepath of the keystore containing the JMX client's SSL certificate.

N/A

M

KEY_STORE_PASSWORD

The password for the JMX SSL key store.

N/A

M

TRUST_STORE

The filepath of the trust store containing the JMX client's SSL certificate.

N/A

M

TRUST_STORE_PASSWORD

The password for the JMX SSL trust store.

N/A

M

REMOTE_MONITORING

Enable multi-tenancy monitoring.

false

M/I

METRICS

Set to true to enable metrics-only collection.

false

INVENTORY

Set to true to enable inventory-only collection.

false

You can define the values for these settings in several ways:

  • Adding the value directly in the config file. This is the most common way.
  • Replacing the values from environment variables using the {{}} notation. This requires infrastructure agent v1.14.0+. Read more here or see the example below.
  • Using secrets management. Use this to protect sensitive information, such as passwords that would be exposed in plain text on the configuration file. For more information, see Secrets management.

Labels

You can further decorate your metrics using labels. Labels allow you to add attributes (key/value pairs) to your metrics, which you can then use to query, filter, or group your metrics.

Our default sample config file includes examples of labels but, because they're not mandatory, you can remove, modify, or add new ones of your choice.

labels:
env: production
role: load_balancer

Example configurations

Here are some example YAML configurations:

Metric data

Cassandra node metrics are attached to the CassandraSample event type. The Cassandra integration collects these node metrics:

Name

Description

db.allMemtablesOffHeapSizeBytes

Total amount of bytes stored in the memtables (2i and pending flush memtables included) that resides on-heap.

db.allMemtablesOnHeapSizeBytes

Total amount of bytes stored in the memtables (2i and pending flush memtables included) that resides off-heap.

db.commitLogCompletedTasksPerSecond

The number of commit log messages written per second.

db.commitLogPendindTasks

Number of commit log messages written but yet to be fsync’ed.

db.commitLogTotalSizeBytes

Current size, in bytes, used by all the commit log segments.

db.droppedRequestTypeMessagesPerSecond

Dropped messages per second for this type of request. RequestType can be any of the following: BatchRemove, BatchStore, CounterMutation, Hint, Mutation, PagedRange, RangeSlice, Read, ReadRepair, RequestResponse, or Trace.

db.keyCacheCapacityBytes

Key cache capacity in bytes.

db.keyCacheHitRate

One-minute key cache hit rate.

db.keyCacheHitsPerSecond

Number of key cache hits per second.

db.keyCacheRequestsPerSecond

Number of requests to the key cache per second.

db.keyCacheSizeBytes

Size of occupied cache in bytes.

db.liveSSTableCount

Number of SSTables on disk for this column family.

db.loadBytes

Size, in bytes, of the on disk data size this node manages.

db.rowCacheCapacityBytes

Row cache capacity in bytes.

db.rowCacheHitRate

One-minute row cache hit rate.

db.rowCacheHitsPerSecond

Number of row cache hits per second.

db.rowCacheRequestsPerSecond

Number of requests to the row cache per second.

db.rowCacheSizeBytes

Total size of occupied row cache, in bytes.

db.threadpool.<pool>ActiveTasks

Number of tasks being actively worked on by this pool. pool can be one of the following:

  • internalAntiEntropyStage
  • internalCacheCleanupExecutor
  • internalCompactionExecutor
  • internalGossipStage
  • internalHintsDispatcher
  • internalInternalResponseStage
  • internalMemtableFlushWriter
  • internalMemtablePostFlush
  • internalMemtableReclaimMemory
  • internalMigrationStage
  • internalMiscStage
  • internalPendingRangeCalculator
  • internalSampler
  • internalSecondaryIndexManagement
  • internalValidationExecutor
  • nativeTransportRequest
  • requestCounterMutationStage
  • requestMutationStage
  • requestReadRepairStage
  • requestReadStage
  • requestRequestResponse
  • requestViewMutationStage

db.threadpool.<pool>PendingTasks

Number of queued tasks queued up on this pool. pool can be any of the items in the list provided in the description of db.threadpool.<pool>ActiveTasks.

db.threadpool.<pool>CompletedTasks

Number of tasks completed. pool can be any of the items in the list provided in the description of db.threadpool.<pool>ActiveTasks.

db.threadpool.<pool>TotalBlockedTasks

Number of tasks that were blocked due to queue saturation. pool can be any of the items in the list provided in the description of db.threadpool.<pool>ActiveTasks.

db.threadpool.<pool>CurrentlyBlockedTask

Number of tasks that are currently blocked due to queue saturation but on retry will become unblocked. pool can be any of the items in the list provided in the description of db.threadpool.<pool>ActiveTasks.

db.totalHintsInProgress

Number of hints currently attempting to be sent.

db.totalHintsPerSecond

Number of hint messages per second written to this node. Includes one entry for each host to be hinted per hint.

query.CASReadRequestsPerSecond

Transaction read latency in requests per second.

query.CASWriteRequestsPerSecond

Transaction write latency in requests per second.

query.rangeSliceRequestsPerSecond

Number of range slice requests per second.

query.rangeSliceTimeoutsPerSecond

Number of timeouts encountered per second when processing token range read requests.

query.rangeSliceUnavailablesPerSecond

Number of unavailable exceptions encountered per second when processing token range read requests.

query.readLatency50thPercentileMilliseconds

Read latency in milliseconds, 50th percentile.

query.readLatency75thPercentileMilliseconds

Read latency in milliseconds, 75th percentile.

query.readLatency95thPercentileMilliseconds

Read latency in milliseconds, 95th percentile.

query.readLatency98thPercentileMilliseconds

Read latency in milliseconds, 98th percentile.

query.readLatency999thPercentileMilliseconds

Read latency in milliseconds, 999th percentile.

query.readLatency99thPercentileMilliseconds

Read latency in milliseconds, 99th percentile.

query.readRequestsPerSecond

Number of read requests per second.

query.readTimeoutsPerSecond

Number of timeouts encountered per second when processing standard read requests.

query.readUnavailablesPerSecond

Number of unavailable exceptions encountered per second when processing standard read requests.

query.viewWriteRequestsPerSecond

Number of view write requests per second.

query.writeLatency50thPercentileMilliseconds

Write latency in milliseconds, 50th percentile.

query.writeLatency75thPercentileMilliseconds

Write latency in milliseconds, 75th percentile.

query.writeLatency95thPercentileMilliseconds

Write latency in milliseconds, 95th percentile.

query.writeLatency98thPercentileMilliseconds

Write latency in milliseconds, 98th percentile.

query.writeLatency999thPercentileMilliseconds

Write latency in milliseconds, 999th percentile.

query.writeLatency99thPercentileMilliseconds

Write latency in milliseconds, 99th percentile.

query.writeRequestsPerSecond

Number of write requests per second.

query.writeTimeoutsPerSecond

Number of timeouts encountered per second when processing regular write requests.

query.writeUnavailablesPerSecond

Number of unavailable exceptions encountered per second when processing regular write requests.

Cassandra column family metrics and metadata

The Cassandra integration retrieves column family metrics. Cassandra column family data is attached to the CassandraColumnFamilySample event type. It skips system keyspaces (system, system_auth, system_distributed, system_schema, system_traces and OpsCenter). To limit the performance impact, the integration will only capture metrics for a maximum of 20 column families.

The following metadata indicates the keyspace and column family associated with the sample metrics:

Name

Description

db.columnFamily

The Cassandra column family these metrics refer to.

db.keyspace

The Cassandra keyspace that contains this column family.

db.keyspaceAndColumnFamily

The keyspace and column family in a single metadata attribute in the following format: keyspace.columnFamily.

The list of metrics below refer to the specific keyspace and column family specified in the metadata above:

Name

Description

db.allMemtablesOffHeapSizeBytes

Total number of bytes stored in the memtables (2i and pending flush memtables included) that resides off-heap.

db.allMemtablesOnHeapSizeBytes

Total number of bytes stored in the memtables (2i and pending flush memtables included) that resides on-heap.

db.liveDiskSpaceUsedBytes

Disk space in bytes used by SSTables belonging to this column family (in bytes).

db.liveSSTableCount

Number of SSTables on disk for this column family.

db.pendingCompactions

Estimate of number of pending compactions for this column family.

db.SSTablesPerRead50thPercentileMilliseconds

Number of sstable data files accessed per read, 50th percentile.

db.SSTablesPerRead75thPercentileMilliseconds

Number of sstable data files accessed per read, 75th percentile.

db.SSTablesPerRead95thPercentileMilliseconds

Number of sstable data files accessed per read, 95th percentile.

db.SSTablesPerRead98thPercentileMilliseconds

Number of sstable data files accessed per read, 98th percentile.

db.SSTablesPerRead999thPercentileMilliseconds

Number of sstable data files accessed per read, 999th percentile.

db.SSTablesPerRead99thPercentileMilliseconds

Number of sstable data files accessed per read, 99th percentile.

query.readLatency50thPercentileMilliseconds

Local read latency in milliseconds for this column family, 50th percentile.

query.readLatency75thPercentileMilliseconds

Local read latency in milliseconds for this column family, 75th percentile.

query.readLatency95thPercentileMilliseconds

Local read latency in milliseconds for this column family, 95th percentile.

query.readLatency98thPercentileMilliseconds

Local read latency in milliseconds for this column family, 98th percentile.

query.readLatency999thPercentileMilliseconds

Local read latency in milliseconds for this column family, 999th percentile.

query.readLatency99thPercentileMilliseconds

Local read latency in milliseconds for this column family, 99th percentile.

query.readRequestsPerSecond

Number of read requests per second for this column family.

query.writeLatency50thPercentileMilliseconds

Local write latency in milliseconds for this column family, 50th percentile.

query.writeLatency75thPercentileMilliseconds

Local write latency in milliseconds for this column family, 75th percentile.

query.writeLatency95thPercentileMilliseconds

Local write latency in milliseconds for this column family, 95th percentile.

query.writeLatency98thPercentileMilliseconds

Local write latency in milliseconds for this column family, 98th percentile.

query.writeLatency999thPercentileMilliseconds

Local write latency in milliseconds for this column family, 999th percentile.

query.writeLatency99thPercentileMilliseconds

Local write latency in milliseconds for this column family, 99th percentile.

query.writeRequestsPerSecond

Number of write requests per second for this column family.

Inventory

The integration captures configuration options defined in the Cassandra configuration and reports them as inventory data in the New Relic UI.

System metadata

The Cassandra integration also collects these attributes about the service and its configuration:

Name

Description

software.version

The Cassandra version.

cluster.name

The name of the cluster this Cassandra node belongs to.

Check the source code

This integration is open source software. That means you can browse its source code and send improvements, or create your own fork and build it.

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