If you use tools like Helm Charts for provisioning and Confluent Operator to make running Kafka on Kubernetes easy, and if you have the support of the storage and network teams, Kafka on Kubernetes is quite easy—in my opinion, easier than any other way of running Kafka. Today, many teams do not just deploy stateless microservices on Kubernetes, but also stateful client applications and server infrastructure. This means you have to deal with state and it is much more heavyweight than a microservice. Use them intensively. These workloads typically come in the form of a microservices architecture, are lightweight, scale well horizontally, adhere to the 12-factor app principles, and can deal with circuit breakers and chaos monkeys. #MDBW17 AGENDA Microservice s What, Why, How? This website uses cookies to enhance user experience and to analyze performance and traffic on our website. If you don’t have those, you will run into trouble. You need a way to route messages to specific brokers. With that in mind, there are actual good reasons for running Kafka on Kubernetes within a traditional enterprise company. Kafka brokers are CPU-friendly. Kubernetes can manage many applications at massive scale … Microservices structure an application into several modular services. For information on creating Kafka topics, see the Create an Apache Kafka … Microservices, events, containers, and orchestrators are dominating our vernacular today. My counterquestion is: Does Kafka run better without it? Kafka DevOps with Kubernetes and GitOps¶. : Unveiling the next-gen event streaming platform, Recommendations for Deploying Apache Kafka on Kubernetes, The Cloud-Native Evolution of Apache Kafka on Kubernetes, Apache Kafka DevOps with Kubernetes and GitOps, Streaming Data from Apache Kafka into Azure Data Explorer with Kafka Connect. Kubernetes, especially with Confluent Operator, does make it easier to deploy and manage new clusters. If your Kubernetes cluster goes down then your Kafka cluster goes down as well in a worst-case scenario. If you have very high non-functional requirements in terms of latency and/or throughput then a different deployment option might be more beneficial. There’s room for improvement. In addition, I’d recommend against choosing Kafka as the first service to run on Kubernetes. In short, a Kafka broker will terminate itself if it’s not able to delete a data directory due to the NFS “silly rename” problem. Event Driven Microservices with Kafka, Kubernetes, and Camel. The Linux operating system has become very stable now and is capable of cleanly … Read the Noteworthy in Tech newsletter. The kafka-devops project is a simulated production environment running a streaming application targeting Apache Kafka® on Confluent Cloud. Azure Data Explorer (also called Kusto) is the, Copyright © Confluent, Inc. 2014-2020. Strimzi makes it really easy to spin up a Kafka cluster in minutes. As with most distributed systems, Kafka performance heavily depends on low network latency and high bandwidth. It supports automatic provisioning, management, scaling and operations of Kafka clusters deployed to Kubernetes. Kafka brokers are memory-eaters. Containers Docker, Kafka Orchestratio n Kubernetes… An operator not only packages a software for Kubernetes, it also allows you to deploy and manage a piece of software for Kubernetes. Here’s a quick look at why these are so useful today. In Kubernetes, set the container resource limits and requests accordingly. For example, my friend Dylan works for an insurance company and wondered, “…Kubernetes and Kafka are complex distributed systems…I know that Confluent has the expertise to do the management of it; however, what do you think of a normal enterprise dealing with it? With KEDA, you can drive the scaling of any container in Kubernetes based on the number of events needing to be processed.KEDA works … With version 1.9, StatefulSets are a first-class citizen in the Kubernetes ecosystem. At the heart of provisioning and managing Kafka with Kubernetes is a Kafka Operator. This includes the Kafka brokers, Apache ZooKeeper, MirrorMaker and Kafka … If you want to run Kafka successfully on Kubernetes, you need to make sure the storage team understands the requirements and that together you validate that they are met. The answer is no. When this is the case, I usually say that this isn’t a good hill to die on. Event Streaming Microservices with Apache Kafka on Kubernetes As operations teams adapt to support these technologies in production, cloud-native platforms like Pivotal Cloud Foundry and Kubernetes … Kubernetes-native Apache Kafka The Red Hat ® AMQ streams component is a massively scalable, distributed, and high-performance data streaming platform based on the Apache Kafka … Kubernetes is designed to run stateless workloads. Kafka comes to the rescue here, both microservices can share a Kafka topic and use it to achieve eventual consistency. It complements those metrics with resource usage and performance as well stability indicators. Let us know if you are interested, and we may invite you to join our beta program. As the number of use cases grow, you end up with multiple production clusters. Due to some limitations of Helm another tool is becoming quite popular: Kubernetes operators. And Kafka clients need more CPU if they are using encryption, but this does not impact the brokers. First, if you are running most of your other applications and microservices on Kubernetes, it becomes the organizational path of least resistance. Get started with the Kafka Streams API to build your own real-time applications and microservices Join us for our three-part online talk series for the ins and outs behind how KSQL works, … I don’t see things this way. Applications and resources are managed by GitOps with declarative infrastructure, Kubernetes… At this point, Kafka and Azure Kubernetes Service are in communication through the peered virtual networks. Since then, we’ve heard from quite a few members of the community question whether running Kafka on Kubernetes is actually a good idea. You can’t place all brokers behind a single load balancer address. Kafka – Challenging, Requires Expert Help As Kafka was not built with Kubernetes deployment in mind, production-ready cluster deployment requires significant work and often proves very challenging. And it is easier to perform configuration changes, upgrades and restarts on all brokers and all clusters. #MDBW17 Andrew Morgan – MongoDB Product Marketing POWERING MICROSERVICES WITH DOCKER, KUBERNETES, KAFKA, & MONGODB andrewmorgan 2. To mitigate this risk, make sure that you have a backup concept in place. Neither NFS v3 nor v4 will work. Kubernetes is an open source platform which runs a cluster of worker nodes and master nodes which allow teams to deploy, manage, scale, and automate containerized workloads such as Kafka. If you still don’t believe me then read this blog post very carefully. The combination of Kafka and zookeeper is one of the most popular message broker. Since I am using Azure Kubernetes Service, this is powered by an Azure Load Balancer which has a public IP (20.44.239.202 in this example) and exposes Kafka to external clients over port 9094. This is why Kafka is preferred among several of the top-tier tech companies such as Uber, Zalando and AirBnB. It was easy to install and I like their approach of leveraging existing operators for Kafka dependencies: Zookeeper, (optional) cert manager and Prometheus. This means you have to deal with state and it is much more heavyweight than a microservice. Don’t stretch a Kafka cluster across data centers either. This is just like how organizations who standardized on VMs have found it very difficult to allocate physical machines with local disks for Kafka. Apache Kafka became the de facto standard for deploying an event streaming platform. Apache Kafka on Kubernetes … KEDA is a Kubernetes-based Event Driven Autoscaler. You would have to complement this with client monitoring (consumer and producer metrics), as well as lag monitoring with Burrow and end-to-end monitoring with Kafka Monitor. The list of awesome operators mentions two operators for Kafka — one of them being Strimzi. Apache Kafka and its ecosystem provides a powerful option to build … I see situations with larger organizations where deploying Kafka outside of Kubernetes causes significant organizational headache that involves many approvals. https://strimzi.io/docs/master/#kafka_dashboard. And of course there are development environments, testing environments, trying-out-a-new-version environments, blue-green deployment environments and so on. Once understood, you can use the same concepts for a Kafka cluster, too. Strimzi supports the management of topics with another operator. Kafka is used for building real-time data pipelines and streaming apps. In most cases, the process will require cooperation from the network team. Kafka on Kubernetes Kafka is a fast, horizontally scalable, fault-tolerant, message queue service. Challenges running Kafka on Kubernetes Apache Kafka became the de facto standard for event streaming platforms. This blog post takes a look at cutting edge technologies like Apache Kafka, Kubernetes, Envoy, Linkerd and Istio to implement a cloud-native service mesh to solve these challenges and bring microservices … Kafka on Kubernetes, and other stateful services, require the use of shared storage. Confluent veröffentlichte nun einen Operator für Apache Kafka auf Kubernetes… If the liveness probe fails, Kubernetes will kill the container and automatically restart it if the restart policy is set accordingly. We also share information about your use of our site with our social media, advertising, and analytics partners. Kubernetes uses liveness and readiness probes to find out if your pods are healthy. The Overflow Blog How to write an effective developer resume: Advice from a hiring manager. So you get basic Kafka cluster monitoring for free! For reference, you can use the results from this blog by Jay Kreps or this review of Amazon MSK by Stéphane Maarek. Terms & Conditions Privacy Policy Do Not Sell My Information Modern Slavery Policy, Apache, Apache Kafka, Kafka, and associated open source project names are trademarks of the Apache Software Foundation. The storage has to be non-local so that Kubernetes is more flexible in choosing another node after restarts or relocations. You could use other deployment tools like Confluent’s Ansible scripts, but they don’t have the built-in provisions for scaling out, monitoring, restarts, upgrades, etc. It becomes easier to scale up—adding new brokers is a single command or a single line in a configuration file. Quite often, we would like to deploy a fully-fledged Kafka cluster in Kubernetes, just because we have a collection of microservices … If a Kubernetes node goes down then the whole Kafka cluster goes down. In my view, Kafka has specific requirements, and Kubernetes delivers the mechanisms to support Kafka. This is why Kafka is preferred by many top-tier tech companies including Uber, Zalando and AirBnB. And if things go wrong, you’ll get much better service from your internal infrastructure teams, because you’ll be running in an environment that is familiar to them. Or in other words, just because one could, does that mean we really should?”I completely agree with Dylan that you need to evaluate every technology for fit within both your overall architecture, and the skill set and culture of the organization. It’s almost KubeCon! Kafka is a stateful service, and this does make the Kubernetes configuration more complex than it is for stateless microservices. A well curated Helm chart simplifies the complex task of properly configuring all the parameters to run Kafka on Kubernetes. Kubernetes is designed to run stateless workloads. The biggest challenges will happen when configuring … Your messages might still be available as replicas on other brokers. Visibility is very important otherwise you won’t know what’s going on. Make sure that all containers in your Kafka installation log to stdout and stderr and make sure your Kubernetes cluster aggregates all the logs in a central logging infrastructure such as Elasticsearch. Confluent also announces an operator which will be coming soon. If the readiness probe fails then Kubernetes will remove the pod from serving requests through a service. As mentioned earlier, any single app on Kubernetes doesn’t bring you much benefits. Unfortunately, many organizations still can’t deliver consistent low latency on their shared storage device. MirrorMaker is one possibility, another one would be to leverage S3 for backups with a connector, as described in this blog post by Zalando. Kafka is a stateful service, and this does make the Kubernetes configuration more complex than it is for stateless microservices. As ZooKeeper is part of Kafka this is a good starting point to learn which Kubernetes concepts are being applied. The hard part will be to reassign the partitions after scaling up or before scaling down. Yolean provides a comprehensive set of manifests to get you started with Kafka on Kubernetes. A statement from the developers of Kafka … It goes far beyond reliable and scalable high-volume … The biggest challenges will happen when configuring storage and network, and you’ll want to make sure both subsystems deliver consistent low latency. However, Kubernetes makes it very easy to scale pods to a certain number of replicas which means that the desired number of Kafka brokers can be defined declaratively. These workloads typically come in the form of a microservices architecture, are lightweight, scale well horizontally, adhere to the 12-factor app principles, and can deal with circuit breakers and chaos monkeys. With this you can reach zero-downtime. Kubernetes supports stateful workloads but you have to treat it with caution as Kelsey Hightowerpoints … Streaming applications are often at the center of your transaction processing and data systems, requiring, Near-real-time insights have become a de facto requirement for Azure use cases involving scalable log analytics, time series analytics, and IoT/telemetry analytics. It visualizes key metrics like under-replicated and offline partitions in a very intuitive way. Let’s talk about the state of cloud-native Apache Kafka® and other distributed systems on Kubernetes. Running Kafka brokers on Kubernetes is most beneficial if the line of business applications are running on Kubernetes too. Once you get used to Kubernetes (and it does not take long), you’ll see that Kafka management becomes much easier. A Letter to Trump Voters on Your Recent Loss, Can America’s broken politics be fixed? Wake up every Sunday morning to the week’s most noteworthy stories in Tech waiting in your inbox. There are a few Helm based installers out there including the official Kubernetes incubator/kafka. Prometheus and Grafana are two popular tools. Adding cAdvisor metrics gives you additional insights about Kubernetes resource usage. In a Microservices based architecture message -broker plays a crucial role in inter-service communication. Let’s have a look at the basic stuff first — the runtime itself. Don’t be tempted to put all brokers on the same node as this would reduce availability. That’s why you should be using persistent storage. I warned you. Luckily, Kafka already ships with two performance test tools: kafka-producer-perf-test.sh and kafka-consumer-perf-test.sh. You can get started with Kafka on Kubernetes today by checking out the white papers and Helm Charts available online. Use non-local persistent block storage with XFS or ext4 to be more precise. The main lesson here is that you can run Kafka on Kubernetes successfully if, and only if, you have the cooperation of skilled storage and network teams. This tutorial explains how to Deploy Kafka and zookeeper stateful sets along with the corresponding services on a multi-node Kubernetes … Not everything that works in a small Silicon Valley startup will work for a large traditional enterprise. For small to medium sized Kafka clusters I would definitely go with Kubernetes as it provides more flexibility and will simplify operations. We can introduce Kafka as Distributed Commit Log … Storage in containers is ephemeral — data will be lost after a restart. Several charts for Kafka are available: An official one in incubator state, one from Confluent and another one from Bitnami, to name a few. Scaling a Kafka cluster is not an easy task. It allows you to install predefined software packages described in Helm charts. In the Recommendations for Deploying Apache Kafka on Kubernetes paper, we explained the available options and their tradeoffs. With Confluent Operator, we are productizing years of Kafka experience with Kubernetes expertise to offer you the best way of using Apache Kafka on Kubernetes. Another big plus that comes with Kubernetes. Running performance tests to benchmark your Kafka installation is very important. Kafka on the other side is essentially a distributed database. Nowadays there is decent tooling to do monitoring with metrics in a cloud native manner. Administration tasks of your Kafka cluster like creating topics and reassigning partitions can be done with the existing shell scripts by opening a shell into your pods. So after a restart, the failing broker first has to replicate all the data which might be a time-consuming process. Murphy’s law tells you that this will happen to you too and you will lose data. It is possible to run Kafka on Kubernetes, so just do it. Medium or message: who’s gonna be the one that saves you. This is not a nice solution though. As operations teams adapt to support these technologies in production, cloud-native platforms like Pivotal Cloud Foundry and Kubernetes … TLS might introduce some overhead. There are several available operators, including the one from Confluent, but I found the Kafka Operatorfrom Banzai Cloud the simplest. Event-centric design and event-driven architecture are powerful tools for designing scalable, distributed systems that are capable of taking advantage of the agility and organizational efficiencies promised by microservices… The, Copyright © Confluent, Inc. 2014-2020 Letter to Trump Voters your. Is preferred by many top-tier Tech companies such as Uber, Zalando and AirBnB make sure you! Kafka — one of the most popular message broker it really easy to up... Use non-local persistent block storage with XFS or ext4 to be more beneficial on all brokers the. 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