Kai

# 상태 점검
@kai check EKS cluster health and pod distribution

# 리소스 사용률
@kai analyze cluster resource utilization and identify bottlenecks

# 노드 분석
@kai identify nodes with <30% CPU utilization for consolidation

# 멀티클러스터 뷰
@kai provide health summary across all Kubernetes clusters

# 파드 적정 크기 조정
@kai analyze pod resource requests/limits and recommend right-sizing

# 스케줄링 효율화
@kai identify pods with resource requests far exceeding actual usage

# 비용 최적화
@kai identify underutilized nodes and recommend consolidation strategy

# 네임스페이스 분석
@kai analyze resource allocation across namespaces

# HPA 검토
@kai review Horizontal Pod Autoscaler policies and recommend improvements

# 스케일링 분석
@kai analyze scaling patterns and recommend threshold adjustments

# VPA 평가
@kai evaluate whether Vertical Pod Autoscaler would benefit our workloads

# 클러스터 자동 스케일링
@kai review Cluster Autoscaler configuration for cost efficiency

# 크래시 조사
@kai investigate pod crash loops in payment namespace

# OOM 분석
@kai identify pods experiencing OOMKilled events and recommend fixes

# 스케줄링 문제
@kai analyze pending pods and identify scheduling constraints

# 네트워크 문제
@kai investigate network connectivity issues between services

# RBAC 감사
@kai audit RBAC configuration against least-privilege principles

# 네트워크 정책
@kai analyze network policies and recommend security improvements

# 파드 보안
@kai identify pods running with excessive privileges

# 시크릿 감사
@kai audit secrets management and recommend rotation strategy

@kai #dashboard EKS cluster health with node and pod metrics
@kai #report cluster optimization opportunities with implementation plan
@kai #recommend HPA policies for variable workloads
@kai #alert on pod OOMKilled events or node pressure conditions

# 좋은 예
@kai analyze production EKS cluster
in us-west-2 for pod resource
optimization

# 피해야 할 예
@kai check our containers

# 좋은 예
@kai improve cluster utilization
while maintaining <30s pod startup
and 99.9% availability

# 피해야 할 예
@kai make cluster better

# 1단계: 평가
@kai analyze cluster resource utilization

# 2단계: 낭비 식별
@kai identify pods with >50% overprovisioned resources

# 3단계: 계획
@kai #recommend right-sizing with zero-downtime approach

# 4단계: 모니터링
@kai #dashboard track resource utilization after changes

# 1단계: 식별
@kai identify unhealthy pods and failing deployments

# 2단계: 조사
@kai analyze logs and events for root cause

# 3단계: 해결
@kai #recommend immediate actions to restore service

# 4단계: 재발 방지
@kai #recommend changes to prevent recurrence

# 1단계: 기준선 설정
@kai analyze current resource consumption patterns

# 2단계: 예측
@kai forecast resource needs for 2x growth

# 3단계: 계획
@kai #recommend node pool configuration for projected growth

# 4단계: 자동화
@kai #recommend autoscaling policies for demand variations