TDengine cluster for kubernetes

TDengine Containers

TDEngine Client, Node, Adapter and Arbitrator Rootless and smallest containers as possible.

TDengine-K8S

TDengine-K8S provides a streamlined method for deploying TDengine, a high-performance time-series database, as a clustered service on Kubernetes. It simplifies the process of running TDengine in containerized environments, enabling scalable and manageable deployments for time-series data workloads. ## Key Features - **Kubernetes Deployment** — Uses YAML manifests to define and deploy TDengine clusters within Kubernetes namespaces. - **Docker Image Support** — Includes a Dockerfile for building custom TDengine images, allowing version-specific deployments. - **Cluster Management** — Supports multi-node TDengine clusters with odd-numbered node configurations for high availability. - **Local Storage Setup** — Provides guidance for preparing local disk storage volumes to persist TDengine data. - **Status Monitoring** — Offers commands to check cluster status via kubectl exec and RESTful API endpoints. ## Philosophy The project focuses on practical, infrastructure-as-code approaches to deploy TDengine in modern cloud-native environments, emphasizing simplicity and reproducibility.