Kafka-specific metric
A Kafka-specific metric is a measurement of the performance, operation, availability, correctness, or throughput of a Kafka component.
Apache Kafka in Action
A Kafka Streams metric is a measurement describing the performance or operation of a Kafka Streams application.
- How it is used
- Monitors Kafka Streams processing to detect failures, dropped records, throughput changes, latency, and state-store conditions.
- How deep it goes
- Descends from metric groups to task, processor-node, stream-thread, and state-store measurements, without defining alert thresholds or instrumentation procedures.
- Examples
- Uses dropped-record totals, failed-stream-thread counts, processed-record rate, processing duration, and RocksDB memory-table sizes.
- What you can do after
- Diagnose/debug with it by locating stopped stream threads, unprocessed records, slow processors, and state-store resource conditions.
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Kafka for Architects
A Kafka-specific metric measures the internal behavior, availability, correctness, or throughput of Kafka components.
- How it is used
- Monitors Kafka component behavior that host-level and JVM-level metrics cannot adequately reveal.
- How deep it goes
- Defines the metric category and its monitoring rationale, but does not enumerate individual Kafka metric names or implementation details.
- Examples
- Uses consumer lag as the concrete example of an application condition that generic monitoring may miss.
- What you can do after
- Diagnose Kafka application delays and monitoring blind spots by instrumenting and tracking Kafka-specific behavior.
Read how Kafka for Architects explains Kafka-specific metric →
Related concepts
- connectormeasures · A connector is a software element or mechanism that links components, applications, or resources to enable or represent their interaction, communication, or data exchange.
- performancemeasures · Performance is the measurable effectiveness or operational behavior of a system under specified conditions, assessed through relevant qualities such as task results, speed, responsiveness, throughput, or resource use.
- Kafka Streamsproduced by · Kafka Streams is a client library for building applications that continuously process data from and write data to Apache Kafka topics.
- monitoringused by · Monitoring is the ongoing observation and measurement of a system’s behavior, state, or operational signals to assess its condition and detect changes or problems.
- observabilityused by · Observability is the ability to infer a system’s internal state and behavior from its externally available outputs, such as logs, metrics, and traces.
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