Operate Kubernetes workloads: extend the platform with the operator pattern!
Paolo Patierno is a Principal Software Engineer working for Red Hat on the messaging and data streaming team. He is a maintainer of Strimzi, a CNCF sandbox project for running Apache Kafka on Kubernetes using operators. He also works on providing Apache Kafka as a fully managed cloud service. In his previous role, he worked on different integration projects about AMQP with Apache Kafka and Spark and on the EnMasse messaging-as-a-service project about the integration with MQTT. He is also a maintainer for different IoT related components in Eclipse Vert.x and Eclipse Paho projects. Finally, he has spoken at numerous national and international conferences about Kafka, Strimzi, and IoT.
Nowadays, Kubernetes is the “de facto” platform for distributing your workloads in cloud-native environments; from databases to messaging or data streaming systems, monitoring frameworks to security solutions, legacy applications, or advanced microservices-based business applications.
Deploying and managing these workloads is rarely simple using the Kubernetes native resources. Helm charts can help but they don’t solve all the potential problems.
What about having an operator, not a human one, looking after your Kubernetes cluster 365/24/7 helping to operate your cloud-native workloads for you?
In the end, this is how the internal mechanics of Kubernetes work but why don’t use the same approach for your own applications?
During this session we’ll explore what the “operator pattern” is and how a software-based operator, with the necessary business logic knowledge, can take care of your Kubernetes workloads, helping with installation, upgrades, certificates management, reducing the human intervention: the open-source Strimzi project will be used as an example to operate Apache Kafka in a cloud-native way.