Monitoring Kafka Lag

Kevin Feasel

2017-08-29

Hadoop

Bas Harenslak explains how to monitor consumer lag in Kafka:

So you’ve written e.g. a Spark ETL pipeline reading from a Kafka topic. There are several options for storing the topic offsets to keep track of which offset was last read. One of them is storing the offsets in Kafka itself, which will be stored in an internal topic __consumer_offsets. If you’re using the Kafka Consumer API (introduced in Kafka 0.9), your consumer will be managed in a consumer group, and you will be able to read the offsets with a Bash utility script supplied with the Kafka binaries.

The Prometheus mentioned in the article is an open-source monitoring solution.

Related Posts

Testing Kafka Streams Applications

Yeva Byzek continues her series on testing Kafka-based streaming applications: When you create a stream processing application with Kafka’s Streams API, you create a Topologyeither using the StreamsBuilder DSL or the low-level Processor API. Normally, the topology runs with the KafkaStreams class, which connects to a Kafka cluster and begins processing when you call start(). For testing though, connecting to a running […]

Read More

Auto ML With SQL Server 2019 Big Data Clusters

Marco Inchiosa has a model scenario for using Big Data Clusters to scale out a machine learning problem: H2O provides popular open source software for data science and machine learning on big data, including Apache SparkTM integration. It provides two open source python AutoML classes: h2o.automl.H2OAutoML and pysparkling.ml.H2OAutoML. Both APIs use the same underlying algorithm implementations, […]

Read More

Categories

August 2017
MTWTFSS
« Jul Sep »
 123456
78910111213
14151617181920
21222324252627
28293031