So whenever you as a consumer feel that the lag might increase there are two options in front. Kafka Lag Exporter is designed for Prometheus.ġ group -> 1 Consumer Instance Workers in a group -> Multiple threads or Go routines (In GO) working to process the load.
#KAFKA LAG EXPORTER PATCH#
For example, in Kubernetes we can react to lag by automatically modifying a Kubernetes Deployment associated with that consumer group and patch its replicas field to add or remove members to the consumer group. Or we can be more proactive and “close the loop” by taking automated action. You can think of a Kafka Broker as a Kafka server. When people talk about Kafka they are typically referring to Kafka Brokers. Kafka Consumer Lag is the indicator of how much lag there is between Kafka producers and consumers. Each partition in the topic is read by only one Consumer. A Kafka Consumer Group has the following properties: All the Consumers in a group have the same group.id. Kafka consumer group is basically a number of Kafka Consumers who can read data in parallel from a Kafka topic. KIP-32 introduced a timestamp field to the Kafka message format. Report latency metrics in the Kafka Consumer at the client (max latency) and partition level, similar to how consumer lag is currently reported. Ex) Ex) Max Consumer Group Time Lag Over Summed Offsets - One panel for each consumer group that shows the max lag in time on the left Y axis. Max Consumer Group Time Lag Over Offset Lag - One panel for each consumer group that shows the max lag in time on the left Y axis and max lag in offsets on the right Y axis. Offset lag is useful to indicate that the consumer group is lagging, but it doesn’t provide a sense of the actual latency of the consuming application. One of Kafka Lag Exporter’s more unique features is its ability to estimate the length of time that a consumer group is behind the last produced value for a particular partition, time lag. Introduction to Kafka Consumer Group Kafka consumer group is basically a number of Kafka Consumers who can read data in parallel from a Kafka topic. This value can be checked via CLI even when there are no active consumers. In case a particular consumer group gets slow or totally down, we should see growing lag and be able to react to it. Apache Kafka Tony Mancill is the author of "Linux Routers" and a long-time contributor to the FOSS community as a Debian developer.įor many applications Kafka consumer group identifiers don’t change dynamically, so tracking the commit lag seems to be very useful.
Lastly, if you’re interested in monitoring things like retention and replication, throughput, and consumer lag within your Kafka systems, take a look at our on-host integration. At a high level, they allow us to do the following. When consuming messages from Kafka it is common practice to use a consumer group, which offer a number of features that make it easier to scale up/out streaming applications. Kafka consumer group lag is one of the most important metrics to monitor on a data streaming platform. A Broker is what actually stores and serves Kafka messages. It can manage hundreds of metrics from all the components of Kafka (Broker, Producer and Consumer) to pinpoint consumer lag. Sematext has a incredibly deep monitoring solution for Kafka. This client transparently handles the failure of Kafka brokers, and transparently adapts as topic partitions it fetches migrate within the cluster. Public class KafkaConsumer extends implements Consumer A client that consumes records from a Kafka cluster. It can also be used as an input plugin for Collectd.įor many applications Kafka consumer group identifiers don’t change dynamically, so tracking the commit lag seems to be very useful. The app provides a rest endpoint that can be called on-demand to get this information. This app will collect offset information for both a regular Kafka consumer and also Storm-Kafka Spout. This is an application/plugin to track the offsets for all the consumer groups in a Kafka cluster. Kafka Lag Exporter is an Akka Typed application written in Scala. It can run anywhere, but it provides features to run easily on Kubernetes clusters against Strimzi Kafka clusters using the Prometheus and Grafana monitoring stack. Kafka Lag Exporter makes it easy to view the latency (residence time) of your Apache Kafka consumer groups.
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