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Management and Metrics API

The Management and Metrics API is enabled by default for all HTTP source (outbound) connectors, and is enabled for source connectors compatible with Aerospike 5.0+ and JMS Inbound 2.0+, when the manage subsection in the service section is configured in the connector's configuration file.

tip

For an HTTP source connector, the service port and manage port are the same.

GET manage/rest/v1/metricsโ€‹

Returns JSON of all the metrics of the connector.

info

The source connector exposes several metrics. We have only highlighted some of the important ones here.

Countersโ€‹

A counter is a cumulative metric that represents a single monotonically increasing counter whose value can only increase or be reset to zero on restart.

NameDescriptionFrom Connector version
connections-activeCount of active XDR connections to the source (outbound) connector.4.0.0
connections-closedCount of closed XDR connections to the source (outbound) connector.4.0.0
requests-errorsCount of requests that could not be written to the external Kafka system. Includes all errors: permanent (as skip and parse errors) as well as retry-able (as timeout or most other backend returned error).3.0.0
requests-parse-errorCount of XDR records which could not be parsed. Parse errors are permanent and are not retried. There will be no traces of those failures on the backend system.3.0.0
requests-skippedCount of XDR records which were skipped and not written to the external Kafka system. Skip errors are permanent and will not be retried. There will be no traces of those failures on the backend system.3.0.0
requests-successCount of records written to the external Kafka system.3.0.0
requests-queuedCurrent count of records being executed by the outbound connector.4.0.0
kafka-producers-activeCount of active Kafka producers.4.0.0
kafka-producers-closedCount of closed Kafka producers.4.0.0

Timersโ€‹

Timers time the processing of tasks. A timer metric aggregates timing durations and provides duration statistics, plus throughput statistics. It provides the total count of the metric, maximum time, minimum time, mean time, times at various quantiles (99%, 95%, etc), and mean throughput value and one-minute, five-minute, and fifteen-minute moving average throughput values.

NameDescriptionFrom Connector version
record-ack-queueTime spent by a processed XDR record in the ack-queue waiting to be acknowledged to Aerospike XDR source.4.0.0
record-dispatchTime spent dispatching an XDR record to the external Kafka system.4.0.0
record-parsingTime spent parsing an XDR record.4.0.0
requests-totalTotal time a XDR record has spent in the connector.3.0.0

Histogramsโ€‹

Histograms calculate the distribution of a value. It provides the total count of the metric, maximum value, minimum value, mean value, and values at various quantiles (99%, 95%, etc).

NameDescriptionFrom Connector version
record-payload-sizeSize of records received by the connector in Bytes.4.0.0

Metersโ€‹

Meters measure the rate of events in the source connector. It provides the total count of the metric, mean value and one-minute, five-minute, and fifteen-minute moving average values.

NameDescriptionFrom Connector version
ordering-errorCount of records rejected to maintain an ordering guarantee of records having the same Aerospike key. XDR retries such a records.5.0.0

Gaugeโ€‹

A gauge metric is an instantaneous reading of a particular value such as queue's depth.

NameDescriptionFrom Connector version
requests-lagThe lag between update of a record in Aerospike and it reaching the source (outbound). Output in milliseconds. Calculated as aerospike_record.lut - current_time. It's sampled every second based on the XDR record being processed at that time, it is approximate and not exact.4.0.0

Example responseโ€‹

{
"counters": {
"connections-active": {
"count": 10
},
"connections-closed": {
"count": 48
},
"requests-queued": {
"count": 10
},
"requests-error": {
"count": 0
},
"requests-parse-error": {
"count": 0
},
"requests-skipped": {
"count": 0
},
"requests-success": {
"count": 498
}
},
"timers": {
"record-ack-queue": {
"count": 498,
"max": 2051.907832,
"mean": 1163.2236708686287,
"min": 0.16272399999999998,
"p50": 1220.575885,
"p75": 1923.971672,
"p95": 1996.4796489999999,
"p98": 2038.0708619999998,
"p99": 2048.850305,
"p999": 2051.907832,
"stddev": 664.955034643945,
"m15_rate": 0.4961578086196813,
"m1_rate": 1.6175162336487592,
"m5_rate": 1.196781946695958,
"mean_rate": 4.064848866969468,
"duration_units": "milliseconds",
"rate_units": "calls/second"
},
"record-dispatch": {
"count": 498,
"max": 4553.8197629999995,
"mean": 2715.295325838721,
"min": 2500.492921,
"p50": 2600.6392769999998,
"p75": 2643.216744,
"p95": 3476.529067,
"p98": 3813.2396289999997,
"p99": 3822.618782,
"p999": 4553.8197629999995,
"stddev": 330.19447171921576,
"m15_rate": 0.49407536855720546,
"m1_rate": 1.518561623864363,
"m5_rate": 1.181774249073358,
"mean_rate": 4.064825124292382,
"duration_units": "milliseconds",
"rate_units": "calls/second"
},
"record-parsing": {
"count": 498,
"max": 57.421721999999995,
"mean": 1.4433150983267966,
"min": 0.16609,
"p50": 0.33832799999999996,
"p75": 0.395851,
"p95": 1.013417,
"p98": 17.077586,
"p99": 56.833085,
"p999": 57.421721999999995,
"stddev": 7.137755816474087,
"m15_rate": 0.49377156430405933,
"m1_rate": 1.5041252749568248,
"m5_rate": 1.179584797165551,
"mean_rate": 4.064802337516862,
"duration_units": "milliseconds",
"rate_units": "calls/second"
},
"requests-total": {
"count": 498,
"max": 4731.708243,
"mean": 4033.1591903548174,
"min": 2776.8367359999997,
"p50": 4004.654642,
"p75": 4680.3988739999995,
"p95": 4727.156959,
"p98": 4729.64192,
"p99": 4730.605834,
"p999": 4731.708243,
"stddev": 603.790753932718,
"m15_rate": 0.4961578086196813,
"m1_rate": 1.6175162336487592,
"m5_rate": 1.196781946695958,
"mean_rate": 4.06477401807955,
"duration_units": "milliseconds",
"rate_units": "calls/second"
}
},
"gauges": {
"requests-lag": {
"value": 6486
}
},
"histograms": {
"record-size": {
"count": 506,
"max": 100,
"mean": 99.99999999999916,
"min": 100,
"p50": 100,
"p75": 100,
"p95": 100,
"p98": 100,
"p99": 100,
"p999": 100,
"stddev": 8.384404281969126e-13
}
}
}

GET manage/rest/v1/loggingโ€‹

Returns the logging configuration of the connect server.

Example responseโ€‹

{
"file": "/var/log/aerospike-xdr-proxy/aerospike-xdr-proxy.log",
"max-history": 30,
"levels": {
"io.netty": "info",
"ROOT": "info",
"org.reflections": "error",
"org.xnio": "error",
"org.jboss": "off",
"com.aerospike.connect.outbound.server.manage.app.ManageExceptionMapper": "info",
"org.glassfish": "info",
"io.undertow": "info"
},
"rolling-file-pattern": "%d{yyyy-MM-dd}",
"enable-console-logging": true,
"log-pattern": "%date{yyyy-MM-dd HH:mm:ss.SSS z__TZ__} %-5level %logger{0} - %msg%n%ex",
"ticker-interval": 1
}

POST manage/rest/v1/logging/{loggerName}โ€‹

Set the log level for a logger identified by name.

Exampleโ€‹

curl -X POST --data "ERROR" -H 'Content-Type: text/plain' http://localhost:8902/manage/rest/v1/logging/io.netty

GET manage/rest/v1/metrics/errorsโ€‹

Returns the errors encountered within the current window of metric logging. Current window is the ticker-interval value set in the logging config section.

Exampleโ€‹

{
"counters": {
"com.aerospike.client.AerospikeException$Connection - Error -8: Failed to connect to host(s): \n 192.168.1.131 32858 Error -8: java.net.SocketException: Connection reset\n": {
"count": 2
}
}
}