OpenShift is a containerization platform built on Kubernetes, offering additional features like developer tools, CI/CD pipelines, and enhanced security. While Kubernetes focuses on container orchestration, OpenShift provides a complete ecosystem for application development, deployment, and management. It includes built-in monitoring, logging, and a user-friendly interface, making it more enterprise-ready compared to vanilla Kubernetes.

Scaling in OpenShift can be achieved using Horizontal Pod Autoscaler (HPA) or manually adjusting replica counts. HPA automatically scales pods based on CPU or memory usage. For manual scaling, I use the OpenShift CLI or web console to increase or decrease replicas. Additionally, I ensure proper resource limits and requests are set to optimize performance and avoid overloading cluster nodes.

I implement role-based access control (RBAC), network policies, and secure communication using TLS. Regularly updating OpenShift and its components ensures vulnerabilities are patched. I also use secrets management for sensitive data and enable audit logging to monitor cluster activity. Integrating security tools like Clair for image scanning and enforcing pod security policies further strengthens the cluster's security posture.

OpenShift uses Persistent Volume Claims (PVCs) to manage storage. PVCs abstract the underlying storage infrastructure, allowing developers to request storage without knowing the details. I configure StorageClasses to define storage types and provisioners. For stateful applications, I use StatefulSets to ensure stable network identities and persistent storage, ensuring data is retained even if pods are rescheduled.

I start by checking pod logs using the OpenShift CLI or web console. If logs don't reveal the issue, I inspect events and resource usage to identify bottlenecks. I also verify network policies, service configurations, and persistent storage. If necessary, I use debugging tools like `oc debug` to interactively troubleshoot the pod. Collaborating with developers to understand application behavior is also crucial for resolving issues efficiently.