Visit our About page to learn how we support our clients with their Kafka, Pulsar, Elasticsearch, and OpenSearch implementations. Consulting support to implement, troubleshoot, and optimize Kafka. Operators dont help with configuring Kafka to meet your use case, capacity planning, and configuring/implementing Kafka producers and consumers. Additionally, operators lack monitoring of critical metrics like the file system cache hit/miss ratio. In the next section we will be covering some of the conflicts that arise from running Kafka on Kubernetes. We are sharing these conflicts for two reasons. Firstly, if your team is in a situation where you can just as easily spin up Kafka on a standalone cluster versus within Kubernetes, then youll have more information to help you make the decision. Secondly, for those teams who have decided deploying Kafka on K8s is the best path forward, youll have an idea of what issues youll face and timeline for fixing and verifying the fixes. In addition to making Kafka run reliably and efficiently, we also typically save our clients more money than our fees cost. The primary ways we help clients save money is by preventing the over-purchase of hardware, making more efficient use of their hardware, and reducing time to project completion., Reach out if you think your project could benefit from an outside team that focuses on deploying, optimizing, and managing Kafka on both standalone clusters and Kubernetes.. Above we touched on how operators, such as Strimzi, can help with turning off some of the functionality in Kubernetes that is incompatible with Kafka. Before we close out the article we wanted to walk you through operators in a little more detail. Strimzi is arguably the most popular operator. Its an open source project under the Apache 2.0 License and, like Kubernetes, its part of the Cloud Native Computing Foundation (CNCF). Strimzi supports both Kafka and ZooKeeper, and it additionally supports MirrorMaker, Kafka Connect clusters, Cruise Control, and Strimzi Bridge. We arent touching on every single problem here, but it gives you an idea of the types of conflicts that exist when running Kafka on Kubernetes. With the exception of the file system cache issue, all of the other issues can be addressed with a good amount of effort and expertise. From our experience, it takes months to implement fixes. There are a number of operators available: RedHats Strimzi, Banzai Cloud Operator, Ciscos koperator, and Confluents Confluent for Kubernetes. Confluent for Kubernetes (CFK) was made available in, and allows users to deploy Confluent for Kubernetes in on-premise environments. As with regular Confluent Kafka, users are limited by their licensing and applicable fees. Keep that in mind if your team is making a decision of whether to use Apache Kafka or Confluent Kafka.. Some teams prefer to run Kafka on K8s because they are running Kafka on-prem and need help with managing it. These teams might be unaware that companies like ours offer fully managed Kafka for on-prem deployments. With that kind of solution there is no concern about automating upgrades and managing the pain points of containerizing a stateful application because an expert team is managing and monitoring the deployment 24/7. Food for thought., First up, lets define the primary uses for Kafka and Kubernetes.. Strimzi, like Kafka, is written in Java.. 24/ 7 support. Calling on help from outside the organization could be the right choice for your project. However, operators dont help with things like configuring Kafka to meet your use case, capacity planning, and configuring/implementing Kafka producers and consumers. Additionally, operators lack monitoring of critical metrics like the file system cache hit/miss ratio. One last point before we move on. If you are already using Confluent Kafka, then using CFK is likely the best option because its the only operator that supports Confluents enterprise products.

Kafka is used to reliably deliver messages. Reliably is the key word here. Its Kafkas stability, high throughput, and exactly once-ness that teams rely upon. Operators also provide automated solutions to *some of* the problems that users would run into if setting up Kafka in Kubernetes manually. And operators also can assist with creating certificates automatically to make updates a little less painful. From a peak performance and reliable management perspective, its better to deploy Kafka outside of Kubernetes. Kubernetes operators can be found on the K8s website, Elasticsearch Basics: What it is, Licensing, Languages, and Getting Help, Kafka, OpenSearch, Elasticsearch Support & Managed Services, fully managed Kafka for on-prem deployments, We go into more depth about the differences between Apache Kafka and Confluent Kafka in an earlier. This might change over time with projects like virtlet that will pseudo-containerize the file system cache which normally lives outside of the K8s pod/container. More and more companies are coming to us specifically for assistance with deploying and managing, In the next section we will be covering some of the conflicts that arise from running Kafka on Kubernetes. We are sharing these conflicts for two reasons. Firstly, if your team is in a situation where you can just as easily spin up Kafka on a standalone cluster versus within Kubernetes, then youll have more information to help you make the decision. Secondly, for those teams who have decided deploying Kafka on K8s is the best path forward, youll have an idea of what issues youll face and timeline for fixing, One last point before we move on. Stateful applications, such as Kafka, contain past knowledge and reference previous interactions. Because of this necessary reference knowledge with stateful applications, the same servers need to be called on every time a request is processed. Running stateful applications on Kubernetes requires turning off many of Kubernetes features. This might change over time with the pseudo-containerization of the file system cache. Lets start with discussing the reasons why teams are choosing to deploy Kafka on Kubernetes. Its usually because of one of the following, (A) there is a good amount of internal expertise with K8s and not much inertia or bandwidth for learning a new configuration management solution, (B) the company has already chosen to host both stateless and stateful applications within K8s, or (C) the reduced reliability of Kafka running within Kubernetes is outweighed by the convenience of Kubernetes. Operators are application-specific software extensions for deploying and managing an application in Kubernetes. Kubernetes is used to orchestrate infrastructure.. We arent touching on every single problem here, but it gives you an idea of the types of conflicts that exist when running Kafka on Kubernetes. With the exception of the file system cache issue, all of the other issues can be addressed with a good amount of effort and expertise. From our experience, it takes months to implement fixes and verify that they are working as expected. These are three important and justifiable reasons, not to be taken lightly.. verify that they are working as expected. Strimzi is arguably the most popular operator. Its an open source project under the Apache 2.0 License and, like Kubernetes, its part of the Cloud Native Computing Foundation (CNCF). Strimzi supports both Kafka and ZooKeeper, and it additionally supports MirrorMaker, Kafka Connect clusters, Cruise Control, and Strimzi Bridge. If you are already using Confluent Kafka, then using CFK is likely the best option because its the only operator that supports Confluents enterprise products. Users typically provide basic cluster information such as the number of brokers, CPU and RAM limits, storage size, authentication and encryption information, and other high level configurations. The operator then takes on the tasks of deploying, managing, and updating Kuberenetes resources as needed to keep Kafka running.. Managed Kafka on your environment with Some teams prefer to run Kafka on K8s because they are running Kafka on-prem and need help with managing it. These teams might be unaware that companies like ours offer. Kafka on Kubernetes presents some challenges though, hence companies reaching out, and in this post we will introduce the most common issues we see to help you get an idea of whats ahead on your Kafka on Kubernetes journey. There are a number of operators available: RedHats Strimzi, Banzai Cloud Operator, Ciscos koperator, and Confluents Confluent for Kubernetes. Confluent for Kubernetes (CFK) was made available in spring of 2021 and allows users to deploy Confluent for Kubernetes in on-premise environments. As with regular Confluent Kafka, users are limited by their licensing and applicable fees. Keep that in mind if your team is making a decision of whether to use Apache Kafka or Confluent Kafka. We go into more depth about the differences between Apache Kafka and Confluent Kafka in an earlier blog post. Keep in mind though that from a peak performance and reliable management perspective, its better to deploy Kafka outside of Kubernetes. Contact us to learn more about how we can assist you with Kafka, Elasticsearch, OpenSearch, and Pulsar. With their primary purposes in mind, lets consider the conceptual conflicts with running Kafka on Kubernetes. A more in-depth discussion of Kubernetes operators can be found on the K8s website linked here. Learn about different aspects of Data Architecture, including specific tips for Kafka, Pulsar and Elasticsearch that you can use today. More and more companies are coming to us specifically for assistance with deploying and managing Apache Kafka on Kubernetes. With many teams already familiar with Kubernetes and its ability to orchestrate infrastructure, it can sometimes be the best choice to spin up Kafka servers on Kubernetes alongside their other applications.

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