🎯 Kubernetes RCA and alerting using Gemini, Loki, Prometheus, Slack
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Description
Summary
This n8n workflow automates Kubernetes root cause analysis (RCA) and incident alerting by integrating with Loki, Prometheus, and Slack. It streamlines log collection, cluster health monitoring, and AI-driven RCA with Gemini, saving DevOps teams hours of manual troubleshooting. Designed for production-grade Kubernetes environments, this plug-and-play workflow delivers actionable insights directly to your Slack channels.
Who’s It For
🛠️ DevOps Engineers automating Kubernetes monitoring and incident response.
🔍 Site Reliability Engineers (SREs) aiming to reduce mean time to resolution (MTTR).
🚀 Teams using n8n, Slack, Loki, and Prometheus for observability and automation.
What It Does
- Pulls logs from Loki, filtering for critical errors.
- Monitors cluster health, checking pending, not ready, or restarting pods.
- Fetches Prometheus metrics for nodes, namespaces, and services.
- Generates AI-driven RCA using Google Gemini to analyze logs and metrics.
- Sends formatted Slack alerts with deduplication and batching for readability.
- Tracks pod lifecycle events, including crashloop states and restarts.
How It Works
- Log Collection: The workflow uses an n8n HTTP Request node to pull logs from Loki, filtering for critical errors.
- Cluster Monitoring: A Kubernetes SSH node checks pod states (terminated or running). If terminated ignore those pods for RCA.
- Metrics Fetching: Prometheus metrics are retrieved via HTTP Request for nodes and services.
- RCA Generation: Logs and metrics are merged into structured prompts for Google Gemini AI to produce actionable RCA insights.
- Kubernetes Enrichment: RCA from Gemini will goes to this node and enriches with Kubernetes documentation and provide the documentation links in RCA
- Slack Notifications: Alerts are batched, deduplicated, and sent to Slack with clear formatting.
How to Set Up
- Import the Workflow: Download the .json file and import it into your n8n instance.
Configure Credentials:
- Add your Loki, Prometheus, and Slack API credentials in the respective nodes (use n8n Credentials Manager if required).
- Set up Google Gemini AI credentials for RCA generation.
- Test the Workflow: Run the workflow manually to ensure logs, metrics, and alerts are processed correctly.
- Schedule Execution: Use n8n’s Schedule Trigger to run the workflow at desired intervals (e.g., every 5 minutes).
Requirements
🌐 n8 K8s node installed (self-hosted only, see n8n documentation).
🔑 Access to Kubernetes clusters and API.
📊 Loki and Prometheus set up for log and metrics collection.
💬 Slack workspace with webhook access for notifications.
🤖 Google Gemini AI API key for RCA generation.
How to Customize the Workflow
- Adjust Filters: Modify the Loki query in the HTTP Request node to focus on specific error patterns.
- Change Alert Frequency: Update the Schedule Trigger node for different intervals.
- Add More Metrics: Extend the Prometheus node to include additional metrics like CPU or memory usage.
- Customize Slack Alerts: Edit the Slack node to change message formatting or add more channels.
- Enhance RCA: Adjust the Gemini AI prompt in the Set Fields node for more specific insights.
🗂️ Category
DevOps / Monitoring & Observability / Kubernetes/ AI
🏷️ Tags
kubernetes, prometheus, slack, alerting, sre, ops, kube-state-metrics, Gemini, AI
Slack Output
image.png
🔗 Nodes Used
HTTP Request, SSH, Schedule Trigger
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File