Kubernetes has become the industry standard for container orchestration, offering robust features for managing and scaling applications, but its full potential can only be realized by adhering to certain best practices. It is essential to define clear objectives and scope before adopting Kubernetes, ensuring that goals like improving scalability and enhancing deployment flexibility are achieved. Designing for scalability and resilience is crucial, involving the use of Kubernetes features such as pods, replicasets, and deployments, along with implementing horizontal pod autoscaling for workload efficiency. Effective resource management can be achieved through the use of namespaces, resource limits, and requests to optimize utilization and prevent contention. Regular updates and patches are necessary to stay protected against vulnerabilities, while best practices for container images, including using lightweight base images and image scanning, help maintain security. Implementing robust logging and monitoring with tools like Prometheus and Grafana, as well as regular backups and disaster recovery testing, ensure observability and resilience. Embracing GitOps and Infrastructure as Code simplifies operations, and investing in team training and comprehensive documentation fosters knowledge sharing and efficient Kubernetes management. The Split Feature Data Platform™ complements these efforts by enabling safe feature deployment and experimentation through feature flags, aiming to speed up releases and enhance team productivity.