Kai

# Health check
@kai check EKS cluster health and pod distribution

# Resource utilization
@kai analyze cluster resource utilization and identify bottlenecks

# Node analysis
@kai identify nodes with <30% CPU utilization for consolidation

# Multi-cluster view
@kai provide health summary across all Kubernetes clusters

# Pod right-sizing
@kai analyze pod resource requests/limits and recommend right-sizing

# Scheduling efficiency
@kai identify pods with resource requests far exceeding actual usage

# Cost optimization
@kai identify underutilized nodes and recommend consolidation strategy

# Namespace analysis
@kai analyze resource allocation across namespaces

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

# Scaling analysis
@kai analyze scaling patterns and recommend threshold adjustments

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

# Cluster autoscaling
@kai review Cluster Autoscaler configuration for cost efficiency

# Crash investigation
@kai investigate pod crash loops in payment namespace

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

# Scheduling issues
@kai analyze pending pods and identify scheduling constraints

# Network problems
@kai investigate network connectivity issues between services

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

# Network policies
@kai analyze network policies and recommend security improvements

# Pod security
@kai identify pods running with excessive privileges

# Secrets audit
@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

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

# Avoid
@kai check our containers

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

# Avoid
@kai make cluster better

# Step 1: Assess
@kai analyze cluster resource utilization

# Step 2: Identify waste
@kai identify pods with >50% overprovisioned resources

# Step 3: Plan
@kai #recommend right-sizing with zero-downtime approach

# Step 4: Monitor
@kai #dashboard track resource utilization after changes

# Step 1: Identify
@kai identify unhealthy pods and failing deployments

# Step 2: Investigate
@kai analyze logs and events for root cause

# Step 3: Remediate
@kai #recommend immediate actions to restore service

# Step 4: Prevent
@kai #recommend changes to prevent recurrence

# Step 1: Baseline
@kai analyze current resource consumption patterns

# Step 2: Project
@kai forecast resource needs for 2x growth

# Step 3: Plan
@kai #recommend node pool configuration for projected growth

# Step 4: Automate
@kai #recommend autoscaling policies for demand variations