Kubernetes (K8s) serves as a popular choice for managing Redpanda clusters due to its cloud-native environment capabilities, although it requires careful tuning to handle vast data streaming efficiently. Redpanda is optimized for performance in containerized environments and ensures quick recovery from broker failures through continuous rebalancing and separating persistent layers. The integration of Redpanda into Kubernetes is facilitated by using similar terminology and structures, making it easier for users to manage, scale, and troubleshoot. Deploying Redpanda in Kubernetes can be efficiently accomplished using the Redpanda Helm chart, which simplifies the setup of a multi-broker cluster and provides a user-friendly administration console. Key components include Redpanda brokers, K8s worker nodes, and pods, all of which need to be configured carefully to optimize resource allocation and ensure efficient networking and persistent storage. The architecture relies on StatefulSet for broker uniqueness, with partition replication and distribution managed to maintain state across restarts. Networking involves intra-broker communication using internal addresses while exposing services externally through NodePort or LoadBalancer for effective client-broker interaction. Persistent storage is managed with Persistent Volumes and can be optimized with Tiered Storage to handle data efficiently and reduce local storage needs. Ongoing maintenance, monitoring, and optimization—referred to as "day two operations"—are essential to keep the cluster running smoothly, with rolling upgrades being a critical aspect of managing software releases without disrupting service. An interactive tutorial on deploying Redpanda in Kubernetes is available on Instruqt, offering practical, hands-on experience for users to familiarize themselves with the deployment and management processes.