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This workflow monitors Kubernetes pod CPU usage using Prometheus, and sends real-time Slack alerts when CPU consumption crosses a threshold (eg, 0.8 cores). It groups pods by application name to reduce noise and improve clarity, making it ideal for observability across multi-pod deployments like Argo CD, Loki, Promtail, applications etc.
Designed for DevOps and SRE teams and platform teams, this workflow is 100% no-code, plug-and-play, and can be easily extended to support memory, disk, or network spikes. It eliminates the need for Alertmanager by routing critical alerts directly into Slack using native n8n nodes.
This n8n workflow polls Prometheus every 5 minutes โฑ๏ธ, checks if any pod's CPU usage crosses a defined threshold (eg, 0.8 cores) ๐จ, groups them by app ๐งฉ, and sends structured alerts to a Slack channel ๐ฌ.
๐ Set your Prometheus URL with required metrics (container_cpu_usage_seconds_total, kube_pod_container_resource_limits)
๐ Add your Slack bot token with chat:write scope
๐งฉ Import the workflow, customize:
Threshold (e.g., 0.8 cores)
Slack channel
Cron schedule
๐ง Adjust threshold values โโor query interval
๐ Add memory/disk/network usage metrics
๐ก This is a plug-and-play Kubernetes alerting template for real-time observability.
Prometheus, Slack, Kubernetes, Alert, n8n, DevOps, Observability, CPU Spike, Monitoring
