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kubesense-ai
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kubesense-logs

Discover and analyze Kubernetes logs across clusters, namespaces, and workloads.

Updated Apr 28, 2026
Search Tags:#monitoring#analytics#logs#search#kubernetes#time-series#log-discovery
One-click install
npx skills add https://github.com/kubesense-ai/kubesense-mcp-skills --skill kubesense-logs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kubesense-logs
Source: https://github.com/kubesense-ai/kubesense-mcp-skills/tree/main/kubesense-mcp/kubesense-logs
Command: npx skills add https://github.com/kubesense-ai/kubesense-mcp-skills --skill kubesense-logs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Discover and analyze Kubernetes logs to identify issues and performance patterns.

Core Features & Use Cases

  • Field discovery to understand log schema across clusters
  • Browse raw log records with filters and time ranges
  • Run aggregated analyses to reveal trends, anomalies, and performance insights across workloads, namespaces, and clusters

Quick Start

Discover available log fields and perform a basic search for ERROR-level logs in the target namespace within the last 30 minutes.

Frequently Asked Questions about kubesense-logs

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I search Kubernetes logs for errors across specific namespaces?▼

You can search Kubernetes logs by applying structured field filtering and time-bounded queries to discover raw log records within target namespaces, enabling focused investigations of ERROR-level events across workloads.

Can I analyze Kubernetes log trends across multiple clusters and workloads?▼

Run aggregated analytics on Kubernetes logs to reveal performance trends, anomalies, and insights across clusters, namespaces, and workloads. This supports repeatable investigations into workload behavior over time.

How do I discover available log fields before querying Kubernetes logs?▼

Use field discovery to understand the log schema across clusters before querying. This identifies predefined log fields available for structured filtering and enables repeatable log investigations.

Does this approach support time-bounded queries for Kubernetes log analysis?▼

Time-bounded queries allow you to filter Kubernetes logs within specific time ranges, such as the last 30 minutes. This constrains raw log searches and aggregated analytics to relevant intervals.

What are the limitations of using predefined log fields for Kubernetes log discovery?▼

Predefined log fields constrain Kubernetes log discovery to structured filtering. If logs lack schema or fields are undiscovered, raw log search may require broader queries without predefined field constraints to find relevant records.

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