AgentSkillsCN

multi-namespace-deployment-analyzer

当用户需要对多个Kubernetes命名空间中的部署情况进行筛选与分析时，该技能会识别符合特定模式的命名空间，从每个命名空间中获取部署信息，提取元数据与注解，并在各命名空间间开展对比分析。它支持批量操作，可将来自多个命名空间的查询结果进行整合。触发条件包括“以…开头的命名空间”“跨命名空间”“多个命名空间”“部署分析”“命名空间模式”“批量部署查询”“跨命名空间对比”等。

SKILL.md
--- frontmatter
name: multi-namespace-deployment-analyzer
description: When the user needs to analyze deployments across multiple Kubernetes namespaces with filtering criteria. This skill discovers namespaces matching patterns, retrieves deployment information from each namespace, extracts metadata and annotations, and performs comparative analysis across namespaces. It handles batch operations and consolidates results from multiple namespace queries. Triggers include 'namespaces starting with', 'across namespaces', 'multiple namespaces', 'deployment analysis', 'namespace pattern', 'batch deployment query', 'cross-namespace comparison'.

Instructions

Overview

This skill analyzes Kubernetes deployments across multiple namespaces based on filtering criteria. It discovers namespaces matching patterns, retrieves deployment information, extracts metadata/annotations, performs comparative analysis, and can execute batch operations.

Core Workflow

1. Discover Target Namespaces

  • •Use k8s-kubectl_get to list all namespaces
  • •Filter namespaces based on user criteria (e.g., names starting with 'dev-')
  • •Store the filtered namespace list for subsequent operations

2. Retrieve Deployments from Each Namespace

  • •For each target namespace, use k8s-kubectl_get to list deployments
  • •Collect deployment metadata: name, namespace, status, creation timestamp
  • •Handle empty namespaces gracefully

3. Extract Detailed Deployment Information

  • •For each deployment, use k8s-kubectl_describe to get detailed information
  • •Focus on extracting annotations, particularly app-version-release-date or similar version metadata
  • •Note container images, resource limits, and other relevant configuration

4. Perform Analysis

  • •Calculate age of deployments based on release date annotations
  • •Apply filtering criteria (e.g., "more than 30 days ago")
  • •Sort results chronologically (oldest to newest)
  • •Count affected deployments for reporting

5. Execute Batch Operations (If Required)

  • •Based on analysis results, perform actions like scaling deployments to 0 replicas
  • •Use k8s-kubectl_scale for each outdated deployment
  • •Verify operations completed successfully

6. Identify Responsible Personnel

  • •Search for contact information using multiple approaches:
    • •Search emails for relevant keywords ("cluster management", "cluster admin", "kubernetes", "infrastructure")
    • •Examine available files and directories for contact information
    • •Check PDF documents for organizational charts or responsibility matrices
    • •Look for configuration files that might contain contact details

7. Generate and Send Report

  • •Compile results in the specified format
  • •Include: number of affected deployments, sorted list with namespace/deployment names and days since release
  • •Use emails-send_email to notify the identified responsible party
  • •Use professional email format with clear subject and body

Key Considerations

Error Handling

  • •Handle cases where no namespaces match the pattern
  • •Handle deployments without version annotations gracefully
  • •Provide clear feedback when contact information cannot be found
  • •Verify email sending was successful

Performance Optimization

  • •Batch namespace queries when possible
  • •Cache results to avoid redundant API calls
  • •Process deployments in parallel where appropriate

Output Formatting

  • •Always sort deployments chronologically from oldest to newest
  • •Include both namespace and deployment name in listings
  • •Calculate days accurately based on current date
  • •Use consistent formatting throughout the report

Common Patterns

  • •Namespace filtering: typically prefixes like 'dev-', 'staging-', 'prod-'
  • •Age filtering: 30, 60, 90 days common thresholds
  • •Actions: scale to 0, delete, annotate, or just report
  • •Contacts: cluster admins, team leads, infrastructure managers