Add Data from Kubernetes / OpenShift

Integrating Kubernetes and OpenShift with XPLG

Modern cloud-native architectures rely heavily on orchestration platforms like Kubernetes and OpenShift to manage distributed applications at scale. To ensure seamless observability and operational intelligence across these environments, XPLG provides a robust, scalable data ingestion framework tailored for containerized workloads. Whether deployed on managed services such as Google Kubernetes Engine (GKE) and Amazon Elastic Kubernetes Service (EKS), or in self-managed, on-premises clusters of Kubernetes or Red Hat OpenShift, organizations can adopt best-practice methodologies to securely and efficiently forward logs and metrics to XPLG. This typically involves deploying lightweight log shippers such as Fluent Bit as DaemonSets, utilizing secure transports like HTTPS, implementing proper filtering and enrichment at the edge, and following a namespace-based or node-labeling strategy for scalable observability.
By aligning with these recommended practices, users can ensure high-fidelity, low-latency data flow into the XPLG platform, enabling real-time stream control, archive, intelligent forwarding, analytics, monitoring, and anomaly detection across diverse infrastructure footprints.