This article is part of a series on DigitalOcean Kubernetes best practices targeted at SMBs and startups, focusing on reliability in Part 3. Reliability refers to an application's ability to work as expected in different situations. To ensure reliability, it's crucial to adhere to well-established practices in Kubernetes and cloud-native computing while considering the specific requirements and characteristics of your application. This includes understanding your application's demands, such as compute-bound, memory-bound, or I/O-bound applications, and selecting nodes that fit the resource profile closely. Node pools allow for grouping similar types of applications or workloads, facilitating better resource management and allocation efficiency. Kubernetes scheduling features like pod affinity and anti-affinity can significantly improve resource utilization. Implementing effective reliability in a Kubernetes environment requires a structured approach and adherence to best practices, including using probes for health monitoring, employing suitable deployment strategies, optimizing pod scheduling, enhancing upgrade resiliency, and leveraging tags in container images. By following these checklists and recommendations, you can build reliable and resilient applications that can withstand failures, recover gracefully, and maintain optimal performance in your Kubernetes cluster.