check-cluster-health

Automate multi-cloud Kubernetes health checks by running a Python script that uses provider SDKs like boto3 and azure-mgmt-* to collect and evaluate node, pod, and network status. This generates a centralized health report for troubleshooting and compliance.

An automated cluster health assessment evaluates node, pod, service, storage, networking, security, and performance health data. It uses a cluster health handler framework to collect, evaluate, and summarize this data for per-cluster drill-down reporting.

Yes, monitoring Kubernetes clusters across multiple clouds requires Python 3.8+ and specific provider SDKs including boto3, azure-mgmt-containerservice, azure-mgmt-monitor, google-cloud-container, and google-cloud-monitoring to collect health data.

Yes, you can orchestrate cross-cloud health checks for many on-prem and managed Kubernetes clusters. This scaling capability allows unified health assessments across AWS EKS, Azure AKS, Google GKE, and on-prem environments.

Multi-cloud Kubernetes environments have fragmented health data because metrics are isolated within individual provider dashboards. Centralize this data by applying a unified health handler framework to collect and summarize cluster statuses into a single report.

Yes, this approach to Kubernetes health monitoring requires a cluster health handler framework to properly collect, evaluate, and summarize health data across different providers, ensuring reliable operations and accurate centralized reporting.