Lightbend has spent a lot of time working with Apache Kafka on Kubernetes. The spec property shows configuration that defines the number of partitions and replicas for the topic. If applied to a Kafka cluster, authorization is enabled for all listeners used for client connection. To use Prometheus to obtain metrics data and provide alerts, Prometheus and the Prometheus Alertmanager plugin must be deployed. To maximise your experience of using Strimzi, you need to understand how Kafka operates as a message broker. Committed offsets are written to an offset commit log. If possible, we will maintain the support for type: jaeger tracing until June 2023 and remove it afterwards. The name of the originating cluster is prepended to the name of the topic. 2023 The Linux Foundation. The configuration describes the source input data and target output data to feed into and out of Kafka Connect. Grafana and Prometheus Setup With Strimzi, a.k.a. Kafka on - DZone Plugins allow connections to other systems and provide additional configuration to manipulate data. For example, a source connector with tasksMax: 2 might split the import of source data into two tasks. A sink connector extracts data out of Kafka. External data is translated and transformed into the appropriate format. A connector operates with a specific type of external system. CORS allows for simple and preflighted requests between origin sources on different domains. A sink connector task receives Kafka records from a worker for writing to the external data system. io.strimzi . Monitoring Kafka on Kubernetes with Prometheus - Medium MirrorMaker 2 is based on the Kafka Connect framework, connectors managing the transfer of data between clusters. The Cluster Operator deploys a corresponding Kafka cluster, based on what is declared in the Kafka resource. Must be unique for each Kafka Connect cluster. A consumer subscribes to a topic and reads messages according to topic, partition and offset. You can configure a Kafka cluster to run with multiple broker nodes across racks. By default, when you deploy Strimzi a single Cluster Operator replica is deployed. Strimzi Operators extend Kubernetes functionality, automating common and complex tasks related to a Kafka deployment. Monitor Kafka Connect and Connectors | Confluent Documentation Must be unique for each Kafka Connect cluster. Topics are split by partitions, where the data is written. See our website for more details about the project. With this configuration applied, topics retain their original names. Kubernetes and Apache Kafka are becoming de-facto platforms for developing and deploying microservice architectures. Must be unique for each Kafka Connect cluster. The sample alerting mechanism provided with Strimzi is configured to send notifications to a Slack channel. For example, through the User Operator you can create a user representing a client that requires access to the Kafka cluster, and specify tls as the authentication type. Must be unique for each Kafka Connect cluster. An include property defines the topics to mirror from the source to the target cluster. By flagging the originating cluster, topics are not replicated back to that cluster. If a worker fails, its tasks are automatically assigned to active workers in the Kafka Connect cluster. ! Strimzi kafka memory keeps increasing - Stack Overflow Connector instances create the tasks required to transfer data in and out of Kafka. Each connector defines a schema for its configuration. You can add to a group of worker pods through configuration of the replicas property in the KafkaConnect resource. Some of the configuration options common to resources are described here. Trace data is useful for monitoring application performance and investigating issues with target systems and end-user applications. The Kafka Connect cluster ID within Kafka. To rebalance the cluster, administrators must monitor the load on brokers and manually reassign busy partitions to brokers with spare capacity. One of the challenges you might face when using both technologies is deploying and managing Kafka brokers inside Kubernetesdealing with YAMLs, management, container creation, etc. For source connectors, how the source data is partitioned is defined by the connector. Installation method: YAML Kubernetes cluster: v1.19.8 Infrastructure: Amazon EKS If the pod is available when the KafkaRoller starts then I guess we can infer that the broker probably hasn't crashed, and so don't expect to spend a long time doing log recovery. It assumes the responsibility of the entire life cycle of Kafka clusters: creating, managing, and monitoring the clusters, and their associated entities (Topics and Users). The expectation is that producers and consumers connect to active clusters only. for communication between Kafka clients and Kafka brokers, and inter-cluster communication. The names of the connectors used by each Kafka Connect cluster must also be unique. In this situation, you might not want automatic renaming of remote topics. Synchronizing data between Kafka clusters using MirrorMaker 2. Schema enabled for converting message keys into structured JSON format. The Cluster Operator can also deploy the following Strimzi operators through configuration of the Kafka resource: Topic Operator to provide operator-style topic management through KafkaTopic custom resources, User Operator to provide operator-style user management through KafkaUser custom resources. You supply the configuration to Kafka Connect to create a connector instance within Kafka Connect. Kafka Bridge consumer and producer configuration is standard, as described in the Apache Kafka configuration documentation for consumers and Apache Kafka configuration documentation for producers. The User Operator manages user credentials for mTLS and SCRAM authentication, but not OAuth 2.0. Plugins for many external systems are available for use with Kafka Connect. Please migrate to OpenTelemetry as soon as possible. Strimzi provides a way to run an Apache Kafka cluster on Kubernetes in various deployment configurations. Kafka listeners use authentication to ensure a secure client connection to the Kafka cluster. After a new custom resource type is added to your cluster by installing a CRD, you can create instances of the resource based on its specification. Brokers contain topics that receive and store data. Prometheus can extract Cruise Control metrics data, including data related to optimization proposals and rebalancing operations. Kafka Connect uses connector instances to integrate with other systems to stream data. The configuration is stored in an internal Kafka topic used by Kafka Connect. KafkaConnector resources are configured to connect to external systems. Kafka Connect provides a set of standard transforms, but you can also create your own. If you are not converting data into a structured format, you dont need to enable schemas. You request CPU and memory resources for components. Transforms adjust messages, such as filtering certain data, before they are converted. However on the kube-system project, I see kafka, zookeeper and entity operator is already running. A Kafka Connect deployment can have one or more plugins, but only one version of each plugin. List of plugins and their artifacts to add to the new container image. Clients are configured with a tracing profile, and a tracer is initialized for the client application to use. Logging can be defined directly (inline) or externally using a config map. A kafka cluster comprises one or more brokers. Each worker runs as a separate pod to make the Kafka Connect cluster more fault tolerant. You can enable TLS encryption for listeners, and configure authentication. Strimzi requires block storage provisioned through StorageClass. If you are using OAuth 2.0 for token-based authentication, you can configure listeners to use the authorization server. The strimzi/kafka-connect:0.9. image is configured to automatically load all plugins or connectors that are present in the /opt/kafka/plugins directory during startup. Must be unique for each Kafka Connect cluster. Custom authentication allows for any type of kafka-supported authentication. In this way, you can make the same data available in different geographical locations. Apache Kafka components are provided for deployment to Kubernetes with the Strimzi distribution. CRDs act as configuration instructions to describe the custom resources in a Kubernetes cluster, The ID identifies the cluster within Kafka. It can provide more flexibility, but also adds complexity. MirrorMaker 2 also uses the Kafka Connect framework. Plugins provide the implementation for creating connector instances. You can also configure user quotas that control usage of Kafka resources to ensure, for example, that a user does not monopolize access to a broker. You can override automatic renaming by adding IdentityReplicationPolicy to the source connector configuration. A plugin provides the implementation artifacts for the sink connector, A single worker initiates the sink connector instance, The sink connector creates the tasks to stream data, Tasks run in parallel to poll Kafka and return records, Converters put the records into a format suitable for the external data system, The sink connector is managed using KafkaConnectors or the Kafka Connect API. Deploys and manages Apache Kafka clusters, Kafka Connect, Kafka MirrorMaker, Kafka Bridge, Kafka Exporter, Cruise Control, and the Entity Operator, Comprises the Topic Operator and User Operator. Replication factor for the Kafka topic that stores connector and task status updates. Unlike the Topic Operator, the User Operator does not sync any changes from the Kafka cluster with the Kubernetes resources. You specify converters for workers in the worker config in the KafkaConnect resource. Secure by Default Built-in security TLS, SCRAM-SHA, and OAuth authentication Automated Certificate Management Simple yet Configurable NodePort, Load balancer and Ingress options Rack awareness for HA By specifying a unique name and port for each listener within a Kafka cluster, The Cluster Operator can also deploy the following Strimzi operators through configuration of the Kafka resource: Topic Operator to provide operator-style topic management through KafkaTopic custom resources, User Operator to provide operator-style user management through KafkaUser custom resources. A secure deployment of Strimzi might encompass one or more of the following security measures: Authorization to allow or decline actions executed by users, Running Strimzi on FIPS-enabled Kubernetes clusters to ensure data security and system interoperability. Converter to transform message keys into JSON format for storage in Kafka. Strimzi provides a way to run an Apache Kafka cluster on Kubernetes or OpenShift in various deployment configurations. External clients can access the Kafka Bridge through an OpenShift Route, a loadbalancer service, or using an Ingress. Internal clients can access the Kafka Bridge on the host and port defined in the KafkaBridge custom resource. Each message in a given partition has a unique offset, which helps identify the position of a consumer within the partition to track the number of records that have been consumed. MirrorMaker 2 consumes messages from a source Kafka cluster and writes them to a target Kafka cluster. Each connector is instantiated on a single worker. The Kafka components are generally run as clusters for availability. Users and clients are matched against the policies created in the authorization server that permit access to perform specific actions on Kafka brokers. Consumer groups are used to share a typically large data stream generated by multiple producers from a given topic. You can change the frequency by adding refresh.topics.interval.seconds to the source connector configuration. The checkpoint connector periodically tracks offsets. Introduction to Strimzi: Apache Kafka on Kubernetes (KubeCon Europe Kafka MirrorMaker (also referred to as MirrorMaker 1) uses producers and consumers to replicate data across clusters as follows: Consumers consume data from the source cluster, Producers output data to the target cluster. A producer sends messages to a broker topic to be written to the end offset of a partition. monitoring via Prometheus encrypted communication using SSL automatic reaction and self healing based on alerts (plugin system, with meaningful default alert plugins) using Cruise Control Motivation Pod schedules use affinity/anti-affinity rules to determine under what circumstances a pod is scheduled onto a node. A __consumer_offsets topic stores information on committed offsets, the position of last and next offset, according to consumer group. A Kafka resource with the cluster configuration is created within the Kubernetes cluster. Use the Quick Starts to get started now! strimzi-kafka-operator/strimzi-pod-monitor.yaml at main - GitHub Strimzi simplifies the process of running Apache Kafka in a Kubernetes cluster. A Kafka Connect deployment can have one or more plugins, but only one version of each plugin. The User Operator manages Kafka users for a Kafka cluster by watching for KafkaUser resources that describe Kafka users, After plugins have been added to the container image used for the worker pods in a deployment, Connectors are plugins that provide the connection configuration needed. Each cluster replicates the data of the other cluster using the concept of source and remote topics. AclAuthorizer uses Access Control Lists (ACLs) to define which users have access to which resources. Persistent storage relates to long-term data storage independent of the lifecycle of the instance. It can provide more flexibility, but also adds complexity. Setting use-connector-resources to true enables KafkaConnectors to create, delete, and reconfigure connectors. After plugins have been added to the container image used for the worker pods in a deployment, The passive cluster remains on standby. As the same topics are stored in each cluster, remote topics are automatically renamed by MirrorMaker 2 to represent the source cluster. The Linux Foundation has registered trademarks and uses trademarks. Apache Kafka on Kubernetes with Strimzi - Sina Nourian The OpenJDK used in Strimzi container images automatically enables FIPS mode when running on a FIPS-enabled Kubernetes cluster. Location of the external data file. Consumer lag is the delay between the last message written to a partition and the message currently being picked up from that partition by a consumer. Alerting rules can provide time-critical notifications on such metrics through a specified communications channel. You can also create your own plugins. Strimzi Overview guide (0.35.0) Strimzi, Strimzi Authors 2023 | Documentation distributed under CC-BY-4.0. A task is started using the configuration supplied by a connector instance. The group ID and names of these topics must also be unique to the Kafka Connect cluster. MirrorMaker 2 is based on the Kafka Connect framework, connectors managing the transfer of data between clusters. As a consequence, the Strimzi. Example dashboards, supplied with Strimzi as JSON files, are imported through the Grafana interface to present monitoring data. Kafka Connect clusters cannot share the group ID or topic names as it will create errors. Schema enabled for converting message values into structured JSON format. If use-connector-resources is enabled in your KafkaConnect configuration, you must use the KafkaConnector resource to define and manage connectors. A replication factor is set for the internal Kafka topics used by Kafka Connect. Communication is always encrypted for communication between: You can also configure TLS encryption between Kafka brokers and clients. If multiple different Kafka Connect clusters are used, these settings must be unique for the workers of each Kafka Connect cluster created. Strimzi operates Kafka Connect in distributed mode, distributing data streaming tasks across one or more worker pods. An authorization server handles the granting of access and inquiries about access. MirrorMaker 2 also uses the Kafka Connect framework. Producers and consumers send and receive messages (publish and subscribe) through brokers. External clients are HTTP clients running outside the Kubernetes cluster in which the Kafka Bridge is deployed and running. Strimzi uses the Cluster Operator to deploy and manage clusters. Strimzi Operators are fundamental to the running of Strimzi. You can deploy Kafka Connect with build configuration that automatically builds a container image with the connector plugins you require for your data connections. Apache ZooKeeper is a core dependency for Kafka as it provides a cluster coordination service, storing and tracking the status of brokers and consumers. A deployment of Grafana is required, with Prometheus added as a data source. You can also specify where the data should sit in Kafka by specifying a target topic name. Use any name that is valid for a Kubernetes resource. The connector might create fewer tasks than the maximum setting. This guide is intended as a starting point for building an understanding of Strimzi. Healthcheck configuration introduces liveness and readiness probes to know when to restart a container (liveness) and when a container can accept traffic (readiness). Replication factor for the Kafka topic that stores connector and task status updates. you specify bootstrap server addresses (in spec.bootstrapServers) for connecting to a Kafka cluster. Kafka Exporter extracts data for analysis as Prometheus metrics, primarily data relating to offsets, consumer groups, consumer lag and topics. The Cluster Operator can deploy the Topic Operator and User Operator as part of an Entity Operator configuration at the same time as a Kafka cluster. Strimzi - Apache Kafka on Kubernetes Source connectors apply transforms before converting data into a format supported by Kafka. Consumers can subscribe to source and remote topics within the same cluster, without the need for a separate aggregation cluster. Worker configuration also specifies the names of internal Kafka Connect topics. The default full mode rebalances partitions across all brokers. The Topic Operator and User Operator function within the Entity Operator on deployment. Jaeger documentation provides distributed tracing support to track transactions between applications. Kafka Connect has some built-in transforms, but other transformations can be provided by plugins if necessary. Support for tracing is built in to the following Kafka components: MirrorMaker to trace messages from a source cluster to a target cluster, Kafka Connect to trace messages consumed and produced by Kafka Connect, Kafka Bridge to trace messages between Kafka and HTTP client applications. The plugin matches the rack IDs of brokers and consumers, so that messages are consumed from the closest replica. External listeners expose Kafka by specifying an external type: route to use OpenShift routes and the default HAProxy router, loadbalancer to use loadbalancer services, nodeport to use ports on Kubernetes nodes, ingress to use Kubernetes Ingress and the Ingress NGINX Controller for Kubernetes. Tracing is not supported for Kafka brokers. Federal Information Processing Standards (FIPS), example files for configuration and monitoring of your deployment, load confidential configuration values for a connector, Apache Kafka configuration documentation for consumers, Apache Kafka configuration documentation for producers. You define the logging level for the component. Kafka resources must also be deployed or redeployed with metrics configuration to expose the metrics data. Kafkas capabilities make it suitable for: Event sourcing to capture changes to the state of an application as a log of events, Stream processing so that applications can respond to data in real time. You can create a custom Kafka Connect image that includes your choice of plugins. Strimzi can employ the following tools for metrics and monitoring: Prometheus pulls metrics from Kafka, ZooKeeper and Kafka Connect clusters. A sink connector extracts data out of Kafka. Kafka Connect can convert data to and from formats supported by Kafka, such as JSON or Avro. If a topic is reconfigured or reassigned to other brokers, the KafkaTopic will always be up to date. You supply the configuration to Kafka Connect to create a connector instance within Kafka Connect. Istio Ingress Gateway to serve Strimzi Apache Kafka on Kubernetes The configuration describes the source input data and target output data to feed into and out of Kafka Connect. This KafkaTopic's 'spec.replicas' should be reverted to 1 and then the replication should be changed directly in Kafka. Tools Grafana and Prometheus Setup With Strimzi, a.k.a. Seek on a partition, so that a consumer starts receiving messages from the first or last offset position, or a given offset position. Workers can run one or more tasks for more than one connector instance. You configure and generate optimization proposals using a KafkaRebalance resource. This allows you to declare a KafkaTopic as part of your applications deployment and the Topic Operator will take care of creating the topic for you. It also supports schemas for structuring data. By deploying the Strimzi Drain Cleaner, you can use the Cluster Operator to move Kafka pods instead of Kubernetes. Replication across two clusters, Example showing manual addition of plugin configuration, Kafka components are contained in the same Kubernetes cluster, Example KafkaConnector source connector configuration, Example curl request to add connector configuration, 3.1. A Kafka Bridge configuration requires a bootstrap server specification for the Kafka cluster it connects to, as well as any encryption and authentication options required. You add the connector configuration as a JSON object. To set up MirrorMaker, a source and target (destination) Kafka cluster must be running. All rights reserved. Cruise Control automates the cluster rebalancing process. Kafka Connect distributes the task configurations to workers, which instantiate and execute tasks. By implementing knowledge of Kafka operations in code, Kafka administration tasks are simplified and require less manual intervention. Kafka Connect clusters cannot share the group ID or topic names as it will create errors. What is Strimzi? Sink connectors apply transforms after converting data into a format suitable for an external data system. Retrieve a list of topics that a consumer is subscribed to. To do this, you change the OpenTelemetry exporter and endpoint in the tracing configuration. In the following example worker configuration, JSON converters are specified. The configuration specifies how connector instances connect to an external data system, including any authentication. Strimzi 0.35.0 is the last version with support for Kubernetes 1.19 and 1.20. The User Operator manages user credentials for mTLS and SCRAM authentication, but not OAuth 2.0. The custom resources for Strimzi components have common configuration properties, which are defined under spec. Strimzi supports Kafka using Operators to deploy and manage the components and dependencies of Kafka to Kubernetes. Synchronizing data between Kafka clusters using MirrorMaker 2. If a worker pod fails, the tasks it was running are reassigned to active workers. Configuration points are outlined, including options to secure and monitor Kafka. The operations supported by the REST API are described in the Apache Kafka Connect API documentation. You cannot have a single ingress distributing access. For a source connector, external source data must reference specific topics that will store the messages. Example dashboards, supplied with Strimzi as JSON files, are imported through the Grafana interface to present monitoring data. The distributed approach to deploying Kafka Connect is fault tolerant and scalable. When a worker receives data, it converts the data into an appropriate format using a converter. To use Prometheus to obtain metrics data and provide alerts, Prometheus and the Prometheus Alertmanager plugin must be deployed. Limits specify the maximum resources that can be consumed by a given container. You can deploy Kafka Connect with build configuration that automatically builds a container image with the connector plugins you require for your data connections. The guide introduces some of the key concepts behind Kafka, which is central to Strimzi, explaining briefly the purpose of Kafka components. Committed offsets are written to an offset commit log. CRDs and custom resources are defined as YAML files. In this case, the external data system is another Kafka cluster. Extend the Kubernetes API with CustomResourceDefinitions. You can control the maximum number of tasks that can run in parallel by setting tasksMax in the connector configuration. The KafkaConnector resource offers a Kubernetes-native approach to management of connectors by the Cluster Operator. Full name of the connector class. The Kafka cluster doesnt need to be managed by Strimzi or deployed to a Kubernetes cluster. Use Strimzis KafkaConnect resource to quickly and easily create new Kafka Connect clusters. It also replicates ACLs and is necessary for the MirrorCheckpointConnector to run. Kafka topic that stores connector and task status configurations. Workers are assigned one or more connector instances and tasks. Each topic is split into one or more partitions. The connector might create fewer tasks than the maximum setting. If you are using OAuth 2.0 for token-based authentication, you can configure listeners to use the authorization server. Topics use a replication factor to configure the number of replicas of each partition within the cluster. JBOD allows you to use multiple disks to store commit logs in each broker. and ensuring that they are configured properly in the Kafka cluster. MirrorMaker was deprecated in Kafka 3.0.0 and will be removed in Kafka 4.0.0. Strimzi automatically downloads and adds the plugin artifacts to a new container image. This guide is intended as a starting point for building an understanding of Strimzi. Oh no! Yet another Kafka operator for Kubernetes Banzai Cloud An in-sync replica has the same number of messages as the leader. Listeners configure how clients connect to a Kafka cluster. Kafka on Kubernetes. for communication between Kafka clients and Kafka brokers, and inter-cluster communication. TLS is specified for external clients when configuring an external listener for the Kafka broker. monitoring - How to monitor apache kafka using nagios? - Stack Overflow The Kafka Connect runtime orchestrates the tasks to split the work required between the worker pods. The lists are defined in the http specification of the Kafka Bridge configuration. A distribution of Strimzi provides the files to deploy and manage a Kafka cluster, as well as example files for configuration and monitoring of your deployment. You can use the Cluster Operator with a deployment of Strimzi Drain Cleaner to help with pod evictions. Kafka Connect clusters are configured by default with the same values for these properties. You can configure a Kafka cluster to run with multiple broker nodes across racks. The topics store connector configuration, offset, and status information. The answer is Strimzi, an open source tool that lets you easily run Kafka clusters on Kubernetes . The following types of listener are supported: Internal listeners for access within Kubernetes, External listeners for access outside of Kubernetes. Noticed a behavior where in the memory graph is keep increasing from Grafana. Kafka Connect is an integration toolkit for streaming data between Kafka brokers and other systems. In Strimzi, tracing facilitates the end-to-end tracking of messages: from source systems to Kafka, and then from Kafka to target systems and applications. The heartbeat connector periodically checks connectivity between the source and target cluster. For custom authorization, you configure your own Authorizer plugin to enforce ACL rules. Restart loop after unclean shutdown Issue #5263 strimzi/strimzi Specify type:jaeger to use OpenTracing and the Jaeger client to get trace data. You can generate optimization proposals in specific modes. It constructs a workload model of resource utilization for the clusterbased on CPU, disk, and network loadand generates optimization proposals (that you can approve or reject) for more balanced partition assignments. Messages are written to partitions by a producer on a round robin basis, or to a specific partition based on the message key.