THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
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Currently, Sink and Source Connectors include latency metrics covering only the time expend interacting with the external systems —
put-batch-latencymetric measures the time to sink a batch of records, andpoll-batch-timemetric measures the time to poll a batch of records from
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- the external system.
At the moment it's difficult to understand another latency aspects, e.g.:
- how much latency has the connector
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- introduced in the process,
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- or
- how long after being written a record is processed.
In order to observe the connector's performance and measure its complete end-to-end latency from sources to sinks there are , this KIP is proposing the following additional measurements:
- In the source connector:
- After polling, there are transformations and conversions that happen before the records are sent to Kafka.
- In the sink connector:
- Record latency:
wall-clock time - record timestampto evaluate how late records are processed. Convert and transform time before sending records to a external system
- Record latency:
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(*) New metrics
Source Connectors have the following stages:
task implementation polling records: gather batch of records from external system
- transform: apply transformation chain individually
- convert: convert records to
ProducerRecordindividually - send records: send records to Kafka topics individually
Polling The stage for polling records stage already has a latency metric: poll-batch-time .
transform-chain-source-record-time and convert-source-record-time metric will measure the transformations applied and conversion from SourceRecord into ProducerRecord .
Send The stage for sending records stage can be monitored with Producer sender metrics, e.g. request-latency-avg/max
Sink Connectors have 3 the following stages:
consumer polling record: gather batch of consumer records
convert: convert records individually to generic
SinkRecord,- transform: apply transformation chain
process: put record batches into a external system.
Process The processing stage already has a latency metric: put-batch-time
To measure sink-'s record -latency , it'latency (i.e. processing time - event time), it's proposed to measure the different difference between record timestamp and current system time (wall-clock) just before the convert stage as it is when records are iterated already.
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Polling can be monitored with Consumer fetch metrics, e.g. fetch-latency-avg/max
| Info |
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Predicates as implemented via |
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The |
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per-record metrics will definitely be added to Kafka Connect as part of this KIP, but their metric level will be changed pending the performance testing described in
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Public Interfaces
The following metrics would be added at the Task Level:
kafka.connect:type=sink-task-metrics,connector="{connector}",task="{task}"
| Sensor / Recording Level | Attribute name | Description |
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kafka.connect:type=sink-task-metrics,connector="{connector}",task="{task}"
| Sensor / Recording Level | Attribute name | Description |
|---|---|---|
sink-record-batch-latency INFO |
| The maximum latency of a record batch, measured by comparing the oldest record timestamp in a batch with the system time (i.e. wallclock) when it has been received by the Sink task right after consumer poll and before conversions.|
sink-record-latencyDEBUG INFO |
| The maximum latency of a record, measured by comparing the record timestamp with the system time (i.e. wallclock) when it has been received by the Sink task right after consumer poll and before conversions. |
| The average latency of a record, measured by comparing the record timestamp with the system time (i.e. wallclock) when it has been received by the Sink task right after consumer poll and before conversions. | |
convert-sink-record-time INFO |
| The average time taken by this task to convert sink records, including key, value, and headers conversion. |
| The maximum time taken by this task to convert sink records, including key, value, and headers conversion. | |
convert-sink-record-key-time DEBUG |
| The average time taken by this task to convert sink record keys. |
| The maximum time taken by this task to convert sink record keys. | |
convert-sink-record-value-time DEBUG |
| The average time taken by this task to convert sink record values. |
| The maximum time taken by this task to convert sink record values. | |
convert-sink-record-headers-time DEBUG |
| The average time taken by this task to convert sink record headers. |
| The maximum time taken by this task to convert sink record headers. | |
transform-chain-sink-record-time INFO |
| The average time taken by this task to apply all the transforms included in this task. |
| The maximum time taken by this task to apply all the transforms included in this task. |
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kafka.connect:type=sink-task-transform-metrics,connector="{connector}",aliastransform="{transform_alias}",task="{task}"
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kafka.connect:type=source-task-transform-metrics,connector="{connector}",aliastransform="{transform_alias}",task="{task}"
| Sensor / Recording Level | Attribute name | Description | |
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transform-source-record-time DEBUG -record-time DEBUG |
| The average time taken by this task to apply specific transform included in this task. | |
| The average time taken by this task to apply specific transform included in this task. |
| The maximum time taken by this task to apply specific transform included in this taskmaximum time taken by this task to apply specific transform included in this task. |
Where alias is the Transform alias name used in configuration:
| Code Block |
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"transforms": "routeRecords",
"transforms.routeRecords.type": "org.apache.kafka.connect.transforms.RegexRouter" |
"routeRecords" in this example.
More granular metrics are recorded at DEBUG level to avoid performance impact.
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ConnectConfig and TransformationChain users will have to migrate to the new interfaces. Though the updates these APIs are used internally on Worker instantiations of Tasks and not meant for external usage.
Rejected Alternatives
If there are alternative ways of accomplishing the same thing, what were they? The purpose of this section is to motivate why the design is the way it is and not some other way.
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