Dapper Cluster Documentation

This documentation covers the architecture, configuration, and operations of the Dapper Kubernetes cluster, a high-performance home lab infrastructure with GPU capabilities.

Cluster Overview

graph TD
    subgraph Control Plane
        CP1[Control Plane 1<br>4 CPU, 16GB]
        CP2[Control Plane 2<br>4 CPU, 16GB]
        CP3[Control Plane 3<br>4 CPU, 16GB]
    end

    subgraph Worker Nodes
        W1[Worker 1<br>16 CPU, 128GB]
        W2[Worker 2<br>16 CPU, 128GB]
        GPU[GPU Node<br>16 CPU, 128GB<br>4x Tesla P100]
    end

    CP1 --- CP2
    CP2 --- CP3
    CP3 --- CP1

    Control Plane --> Worker Nodes

Hardware Specifications

Control Plane

  • 3 nodes for high availability
  • 4 CPU cores per node
  • 16GB RAM per node
  • Dedicated to cluster control plane operations

Worker Nodes

  • 2 general-purpose worker nodes
  • 16 CPU cores per node
  • 128GB RAM per node
  • Handles general workloads and applications

GPU Node

  • Specialized GPU worker node
  • 16 CPU cores
  • 128GB RAM
  • 4x NVIDIA Tesla P100 GPUs
  • Handles ML/AI and GPU-accelerated workloads

Key Features

  • High-availability Kubernetes cluster
  • GPU acceleration support
  • Automated deployment using Flux CD
  • Secure secrets management with SOPS
  • NFS and OpenEBS storage integration
  • Comprehensive monitoring and observability
  • Media services automation

Infrastructure Components

graph TD
    subgraph Core Services
        Flux[Flux CD]
        Storage[Storage Layer]
        Network[Network Layer]
    end

    subgraph Applications
        Media[Media Stack]
        Monitor[Monitoring]
        GPU[GPU Workloads]
    end

    Core Services --> Applications

    Storage --> |NFS/OpenEBS| Applications
    Network --> |Ingress/DNS| Applications

Documentation Structure

  • Architecture: Detailed technical documentation about cluster design and components

    • High-availability control plane design
    • Storage architecture and configuration
    • Network topology and policies
    • GPU integration and management
  • Applications: Information about deployed applications and their configurations

    • Media services stack
    • Monitoring and observability
    • GPU-accelerated applications
  • Operations: Guides for installation, maintenance, and troubleshooting

    • Cluster setup procedures
    • Node management
    • GPU configuration
    • Maintenance tasks

Getting Started

For new users, we recommend starting with:

  1. Architecture Overview - Understanding the cluster design
  2. Installation Guide - Setting up the cluster
  3. Application Stack - Deploying applications

Architecture Overview

Cluster Architecture

graph TD
    subgraph Control Plane
        CP1[Control Plane 1<br>4 CPU, 16GB]
        CP2[Control Plane 2<br>4 CPU, 16GB]
        CP3[Control Plane 3<br>4 CPU, 16GB]

        CP1 --- CP2
        CP2 --- CP3
        CP3 --- CP1
    end

    subgraph Worker Nodes
        W1[Worker 1<br>16 CPU, 128GB]
        W2[Worker 2<br>16 CPU, 128GB]
    end

    subgraph GPU Node
        GPU[GPU Worker<br>16 CPU, 128GB<br>4x Tesla P100]
    end

    Control Plane --> Worker Nodes
    Control Plane --> GPU

Core Components

Control Plane

  • High Availability: 3-node control plane configuration
  • Resource Allocation: 4 CPU, 16GB RAM per node
  • Components:
    • etcd cluster
    • API Server
    • Controller Manager
    • Scheduler

Worker Nodes

  • General Purpose Workers: 2 nodes
  • Resources per Node:
    • 16 CPU cores
    • 128GB RAM
  • Workload Types:
    • Application deployments
    • Database workloads
    • Media services
    • Monitoring systems

GPU Node

  • Specialized Worker: 1 node
  • Hardware:
    • 16 CPU cores
    • 128GB RAM
    • 4x NVIDIA Tesla P100 GPUs
  • Workload Types:
    • ML/AI workloads
    • Video transcoding
    • GPU-accelerated applications

Network Architecture

graph TD
    subgraph External
        Internet((Internet))
        DNS((DNS))
    end

    subgraph Network Edge
        FW[Firewall]
        LB[Load Balancer]
    end

    subgraph Kubernetes Network
        CP[Control Plane]
        Workers[Worker Nodes]
        GPUNode[GPU Node]

        subgraph Services
            Ingress[Ingress Controller]
            CoreDNS[CoreDNS]
            CNI[Network Plugin]
        end
    end

    Internet --> FW
    DNS --> FW
    FW --> LB
    LB --> CP
    CP --> Workers
    CP --> GPUNode
    Services --> Workers
    Services --> GPUNode

Storage Architecture

graph TD
    subgraph Storage Classes
        NFS[NFS Storage Class]
        OpenEBS[OpenEBS Storage Class]
    end

    subgraph Persistent Volumes
        NFS --> NFS_PV[NFS PVs]
        OpenEBS --> Local_PV[Local PVs]
    end

    subgraph Workload Types
        NFS_PV --> Media[Media Storage]
        NFS_PV --> Shared[Shared Config]
        Local_PV --> DB[Databases]
        Local_PV --> Cache[Cache Storage]
    end

Security Considerations

  • Network segmentation using Kubernetes network policies
  • Encrypted secrets management with SOPS
  • TLS encryption for all external services
  • Regular security updates via automated pipelines
  • GPU access controls and resource quotas

Scalability

The cluster architecture is designed to be scalable:

  • High-availability control plane (3 nodes)
  • Expandable worker node pool
  • Specialized GPU node for compute-intensive tasks
  • Dynamic storage provisioning
  • Load balancing for external services
  • Resource quotas and limits management

Monitoring and Observability

graph LR
    subgraph Monitoring Stack
        Prom[Prometheus]
        Graf[Grafana]
        Alert[Alertmanager]
    end

    subgraph Node Types
        CP[Control Plane Metrics]
        Work[Worker Metrics]
        GPU[GPU Metrics]
    end

    CP --> Prom
    Work --> Prom
    GPU --> Prom
    Prom --> Graf
    Prom --> Alert

Resource Management

Control Plane

  • Reserved for kubernetes control plane components
  • Optimized for control plane operations
  • High availability configuration

Worker Nodes

  • General purpose workloads
  • Balanced resource allocation
  • Flexible scheduling options

GPU Node

  • Dedicated for GPU workloads
  • NVIDIA GPU operator integration
  • Specialized resource scheduling

Network Architecture

Network Overview

graph TD
    subgraph External
        Internet((Internet))
        DNS((DNS))
    end

    subgraph Network Edge
        FW[Firewall]
        LB[Load Balancer]
        Internet --> FW
        DNS --> FW
        FW --> LB
    end

    subgraph Kubernetes Network
        subgraph Ingress
            LB --> Traefik[Traefik]
            Traefik --> Services[Internal Services]
        end

        subgraph Network Policies
            Services --> Apps[Applications]
            Services --> DBs[Databases]
        end

        subgraph CNI[Container Network]
            Apps --> Pod1[Pod Network]
            DBs --> Pod1
        end
    end

Components

Ingress Controller

  • Traefik: Main ingress controller
    • SSL/TLS termination
    • Automatic certificate management
    • Route configuration
    • Load balancing

Network Policies

graph LR
    subgraph Policies
        Default[Default Deny]
        Allow[Allowed Routes]
    end

    subgraph Apps
        Media[Media Stack]
        Monitor[Monitoring]
        DB[Databases]
    end

    Allow --> Media
    Allow --> Monitor
    Default --> DB

DNS Configuration

  • External DNS for automatic DNS management
  • Internal DNS resolution
  • Split DNS configuration

Security

Network Policies

apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: default-deny
spec:
  podSelector: {}
  policyTypes:
  - Ingress
  - Egress

TLS Configuration

  • Automatic certificate management via cert-manager
  • Let's Encrypt integration
  • Internal PKI for service mesh

Service Mesh

Traffic Flow

graph LR
    subgraph Ingress
        External[External Traffic]
        Traefik[Traefik]
    end

    subgraph Services
        App1[Service 1]
        App2[Service 2]
        DB[Database]
    end

    External --> Traefik
    Traefik --> App1
    Traefik --> App2
    App1 --> DB
    App2 --> DB

Best Practices

  1. Security

    • Implement default deny policies
    • Use TLS everywhere
    • Regular security audits
    • Network segmentation
  2. Performance

    • Load balancer optimization
    • Connection pooling
    • Proper resource allocation
    • Traffic monitoring
  3. Reliability

    • High availability configuration
    • Failover planning
    • Backup routes
    • Health checks
  4. Monitoring

    • Network metrics collection
    • Traffic analysis
    • Latency monitoring
    • Bandwidth usage tracking

Troubleshooting

Common network issues and resolution steps:

  1. Connectivity Issues

    • Check network policies
    • Verify DNS resolution
    • Inspect service endpoints
    • Review ingress configuration
  2. Performance Problems

    • Monitor network metrics
    • Check for bottlenecks
    • Analyze traffic patterns
    • Review resource allocation

Storage Architecture

Storage Overview

graph TD
    subgraph Storage Classes
        NFS[NFS Storage Class]
        OpenEBS[OpenEBS Storage Class]
    end

    subgraph Persistent Volumes
        NFS --> NFS_PV[NFS PVs]
        OpenEBS --> Local_PV[Local PVs]
    end

    subgraph Applications
        NFS_PV --> Media[Media Apps]
        NFS_PV --> Backup[Backup Storage]
        Local_PV --> Database[Databases]
        Local_PV --> Cache[Cache Storage]
    end

Storage Classes

NFS Storage Class

  • Used for shared storage across nodes
  • Ideal for media storage and shared configurations
  • Supports ReadWriteMany (RWX) access mode
  • Configuration:
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: nfs-csi
provisioner: nfs.csi.k8s.io
parameters:
  server: nfs-server
  share: /export/nfs

OpenEBS Storage Class

  • Local storage for performance-critical applications
  • Used for databases and caching layers
  • Supports ReadWriteOnce (RWO) access mode
  • Configuration:
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: openebs-local
provisioner: openebs.io/local
volumeBindingMode: WaitForFirstConsumer

Storage Considerations

Performance

  • Use OpenEBS local storage for:
    • Databases requiring low latency
    • Cache storage
    • Write-intensive workloads
  • Use NFS storage for:
    • Media files
    • Shared configurations
    • Backup storage
    • Read-intensive workloads

Backup Strategy

graph LR
    Apps[Applications] --> PV[Persistent Volumes]
    PV --> Backup[Backup Jobs]
    Backup --> Remote[Remote Storage]

Volume Snapshots

  • Regular snapshots for data protection
  • Snapshot schedules based on data criticality
  • Retention policies for space management

Best Practices

  1. Storage Class Selection

    • Use appropriate storage class based on workload requirements
    • Consider access modes needed by applications
    • Account for performance requirements
  2. Resource Management

    • Set appropriate storage quotas
    • Monitor storage usage
    • Plan for capacity expansion
  3. Data Protection

    • Regular backups
    • Snapshot scheduling
    • Replication where needed
  4. Performance Optimization

    • Use local storage for performance-critical workloads
    • Implement caching strategies
    • Monitor I/O patterns

Media Applications

Media Stack Overview

graph TD
    subgraph Media Management
        Wizarr[Wizarr]
        Plex[Plex Media Server]
        Wizarr --> Plex
    end

    subgraph Storage
        NFS[NFS Storage]
        Plex --> NFS
    end

    subgraph Access Control
        Auth[Authentication]
        Wizarr --> Auth
    end

Components

Media Server

  • Plex Media Server
    • Media streaming service
    • Transcoding capabilities
    • Library management
    • Multi-user support

User Management

  • Wizarr
    • User invitation system
    • Plex account management
    • Access control
    • Integration with authentication

Storage Configuration

Media Storage

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: media-storage
spec:
  accessModes:
    - ReadWriteMany
  storageClassName: nfs-csi
  resources:
    requests:
      storage: 1Ti

Network Configuration

Service Configuration

  • Internal service discovery
  • External access through ingress
  • Secure connections with TLS

Example Ingress

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: media-ingress
  annotations:
    cert-manager.io/cluster-issuer: letsencrypt-prod
spec:
  rules:
    - host: plex.example.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: plex
                port:
                  number: 32400

Resource Management

Resource Allocation

  • CPU and memory limits
  • Storage quotas
  • Network bandwidth considerations

Example Resource Configuration

resources:
  limits:
    cpu: "4"
    memory: 8Gi
  requests:
    cpu: "2"
    memory: 4Gi

Maintenance

Backup Strategy

graph LR
    Media[Media Files] --> Backup[Backup Storage]
    Config[Configurations] --> Backup
    Meta[Metadata] --> Backup

Regular Tasks

  1. Database backups
  2. Configuration backups
  3. Media library scans
  4. Storage cleanup

Monitoring

Key Metrics

  • Server health
  • Transcoding performance
  • Storage usage
  • Network bandwidth
  • User activity

Alerts

  • Storage capacity warnings
  • Service availability
  • Performance degradation
  • Failed transcoding jobs

Troubleshooting

Common issues and resolution steps:

  1. Streaming Issues

    • Check network connectivity
    • Verify transcoding settings
    • Monitor resource usage
    • Review logs
  2. Storage Problems

    • Verify mount points
    • Check permissions
    • Monitor disk space
    • Review I/O performance
  3. User Access Issues

    • Verify authentication
    • Check authorization
    • Review user permissions
    • Check invitation system

Observability

Installation Guide

Prerequisites

graph TD
    subgraph Hardware
        CP[Control Plane Nodes]
        GPU[GPU Worker Node]
        Worker[Worker Nodes]
    end

    subgraph Software
        OS[Operating System]
        Tools[Required Tools]
        Network[Network Setup]
    end

    subgraph Configuration
        Git[Git Repository]
        Secrets[SOPS Setup]
        Certs[Certificates]
    end

Hardware Requirements

Control Plane Nodes (3x)

  • CPU: 4 cores per node
  • RAM: 16GB per node
  • Role: Cluster control plane

GPU Worker Node (1x)

  • CPU: 16 cores
  • RAM: 128GB
  • GPU: 4x NVIDIA Tesla P100
  • Role: GPU-accelerated workloads

Worker Nodes (2x)

  • CPU: 16 cores per node
  • RAM: 128GB per node
  • Role: General workloads

Software Prerequisites

  1. Operating System

    • Linux distribution
    • Updated system packages
    • Required kernel modules
    • NVIDIA drivers (for GPU node)
  2. Required Tools

    • kubectl
    • flux
    • SOPS
    • age/gpg
    • task

Initial Setup

1. Repository Setup

# Clone the repository
git clone https://github.com/username/dapper-cluster.git
cd dapper-cluster

# Create configuration
cp config.sample.yaml config.yaml

2. Configuration

graph LR
    Config[Configuration] --> Secrets[Secrets Management]
    Config --> Network[Network Settings]
    Config --> Storage[Storage Setup]
    Secrets --> SOPS[SOPS Encryption]
    Network --> DNS[DNS Setup]
    Storage --> CSI[CSI Drivers]

Edit Configuration

cluster:
  name: dapper-cluster
  domain: example.com

network:
  cidr: 10.0.0.0/16

storage:
  nfs:
    server: nfs.example.com
    path: /export/nfs

3. Secrets Management

  • Generate age key
  • Configure SOPS
  • Encrypt sensitive files

4. Bootstrap Process

graph TD
    Start[Start Installation] --> CP[Bootstrap Control Plane]
    CP --> Workers[Join Worker Nodes]
    Workers --> GPU[Configure GPU Node]
    GPU --> Flux[Install Flux]
    Flux --> Apps[Deploy Apps]

Bootstrap Commands

# Initialize flux
task flux:bootstrap

# Verify installation
task cluster:verify

# Verify GPU support
kubectl get nodes -o wide
nvidia-smi # on GPU node

Post-Installation

1. Verify Components

  • Check control plane health
  • Verify worker node status
  • Test GPU functionality
  • Check storage provisioners
  • Verify network connectivity

2. Deploy Applications

  • Deploy core services
  • Configure monitoring
  • Setup backup systems
  • Deploy GPU-enabled workloads

3. Security Setup

  • Configure network policies
  • Setup certificate management
  • Enable monitoring and alerts
  • Secure GPU access

Troubleshooting

Common installation issues and solutions:

  1. Control Plane Issues

    • Verify etcd cluster health
    • Check control plane components
    • Review system logs
  2. Worker Node Issues

    • Verify node join process
    • Check kubelet status
    • Review node logs
  3. GPU Node Issues

    • Verify NVIDIA driver installation
    • Check NVIDIA container runtime
    • Validate GPU visibility in cluster
  4. Storage Issues

    • Verify NFS connectivity
    • Check storage class configuration
    • Review PV/PVC status
  5. Network Problems

    • Check DNS resolution
    • Verify network policies
    • Review ingress configuration

Maintenance

Regular Tasks

  1. System updates
  2. Certificate renewal
  3. Backup verification
  4. Security audits
  5. GPU driver updates

Health Checks

  • Component status
  • Resource usage
  • Storage capacity
  • Network connectivity
  • GPU health

Next Steps

After successful installation:

  1. Review Architecture Overview
  2. Configure Storage
  3. Setup Network
  4. Deploy Applications

Maintenance Guide

Maintenance Overview

graph TD
    subgraph Regular Tasks
        Updates[System Updates]
        Backups[Backup Tasks]
        Monitoring[Health Checks]
    end

    subgraph Periodic Tasks
        Audit[Security Audits]
        Cleanup[Resource Cleanup]
        Review[Config Review]
    end

    Updates --> Verify[Verification]
    Backups --> Test[Backup Testing]
    Monitoring --> Alert[Alert Response]

Regular Maintenance

Daily Tasks

  1. Monitor system health
    • Check cluster status
    • Review resource usage
    • Verify backup completion
    • Check alert status

Weekly Tasks

  1. Review system logs
  2. Check storage usage
  3. Verify backup integrity
  4. Update documentation

Monthly Tasks

  1. Security updates
  2. Certificate rotation
  3. Resource optimization
  4. Performance review

Update Procedures

Flux Updates

graph LR
    PR[Pull Request] --> Review[Review Changes]
    Review --> Test[Test Environment]
    Test --> Deploy[Deploy to Prod]
    Deploy --> Monitor[Monitor Status]

Application Updates

  1. Review release notes
  2. Test in staging if available
  3. Update flux manifests
  4. Monitor deployment
  5. Verify functionality

Backup Management

Backup Strategy

graph TD
    Apps[Applications] --> Data[Data Backup]
    Config[Configurations] --> Git[Git Repository]
    Secrets[Secrets] --> Vault[Secret Storage]

    Data --> Verify[Verification]
    Git --> Verify
    Vault --> Verify

Backup Verification

  • Regular restore testing
  • Data integrity checks
  • Recovery time objectives
  • Backup retention policy

Resource Management

Cleanup Procedures

  1. Remove unused resources

    • Orphaned PVCs
    • Completed jobs
    • Old backups
    • Unused configs
  2. Storage optimization

    • Compress old logs
    • Archive unused data
    • Clean container cache

Monitoring and Alerts

Key Metrics

  • Node health
  • Pod status
  • Resource usage
  • Storage capacity
  • Network performance

Alert Response

  1. Acknowledge alert
  2. Assess impact
  3. Investigate root cause
  4. Apply fix
  5. Document resolution

Security Maintenance

Regular Tasks

graph TD
    Audit[Security Audit] --> Review[Review Findings]
    Review --> Update[Update Policies]
    Update --> Test[Test Changes]
    Test --> Document[Document Changes]

Security Checklist

  • Review network policies
  • Check certificate expiration
  • Audit access controls
  • Review secret rotation
  • Scan for vulnerabilities

Troubleshooting Guide

Common Issues

  1. Node Problems

    • Check node status
    • Review system logs
    • Verify resource usage
    • Check connectivity
  2. Storage Issues

    • Verify mount points
    • Check permissions
    • Monitor capacity
    • Review I/O performance
  3. Network Problems

    • Check DNS resolution
    • Verify network policies
    • Review ingress status
    • Test connectivity

Recovery Procedures

  1. Node Recovery
# Check node status
kubectl get nodes

# Drain node for maintenance
kubectl drain node-name

# Perform maintenance
# ...

# Uncordon node
kubectl uncordon node-name
  1. Storage Recovery
# Check PV status
kubectl get pv

# Check PVC status
kubectl get pvc

# Verify storage class
kubectl get sc

Documentation

Maintenance Logs

  • Keep detailed records
  • Document changes
  • Track issues
  • Update procedures

Review Process

  1. Regular documentation review
  2. Update procedures
  3. Verify accuracy
  4. Add new sections

Best Practices

  1. Change Management

    • Use git workflow
    • Test changes
    • Document updates
    • Monitor results
  2. Resource Management

    • Regular cleanup
    • Optimize usage
    • Monitor trends
    • Plan capacity
  3. Security

    • Regular audits
    • Update policies
    • Monitor access
    • Review logs

Troubleshooting Guide

Diagnostic Workflow

graph TD
    Issue[Issue Detected] --> Triage[Triage]
    Triage --> Diagnose[Diagnose]
    Diagnose --> Fix[Apply Fix]
    Fix --> Verify[Verify]
    Verify --> Document[Document]

Common Issues

1. Cluster Health Issues

Node Problems

graph TD
    Node[Node Issue] --> Check[Check Status]
    Check --> |Healthy| Resources[Resource Issue]
    Check --> |Unhealthy| System[System Issue]
    Resources --> Memory[Memory]
    Resources --> CPU[CPU]
    Resources --> Disk[Disk]
    System --> Logs[Check Logs]
    System --> Network[Network]

Diagnosis Steps:

# Check node status
kubectl get nodes
kubectl describe node <node-name>

# Check system resources
kubectl top nodes
kubectl top pods --all-namespaces

# Check system logs
kubectl logs -n kube-system <pod-name>

2. Storage Issues

Volume Problems

graph LR
    PV[PV Issue] --> Status[Check Status]
    Status --> |Bound| Access[Access Issue]
    Status --> |Pending| Provision[Provisioning Issue]
    Status --> |Failed| Storage[Storage System]

Resolution Steps:

# Check PV/PVC status
kubectl get pv,pvc --all-namespaces

# Check storage class
kubectl get sc

# Check provisioner pods
kubectl get pods -n storage

3. Network Issues

Connectivity Problems

graph TD
    Net[Network Issue] --> DNS[DNS Check]
    Net --> Ingress[Ingress Check]
    Net --> Policy[Network Policy]

    DNS --> CoreDNS[CoreDNS Pods]
    Ingress --> Traefik[Traefik Logs]
    Policy --> Rules[Policy Rules]

Diagnostic Commands:

# Check DNS
kubectl get pods -n kube-system -l k8s-app=kube-dns
kubectl logs -n kube-system -l k8s-app=kube-dns

# Check ingress
kubectl get ingress --all-namespaces
kubectl describe ingress <ingress-name> -n <namespace>

4. Application Issues

Pod Problems

graph TD
    Pod[Pod Issue] --> Status[Check Status]
    Status --> |Pending| Schedule[Scheduling]
    Status --> |CrashLoop| Crash[Container Crash]
    Status --> |Error| Logs[Check Logs]

Troubleshooting Steps:

# Check pod status
kubectl get pods -n <namespace>
kubectl describe pod <pod-name> -n <namespace>

# Check logs
kubectl logs <pod-name> -n <namespace>
kubectl logs <pod-name> -n <namespace> --previous

Flux Issues

GitOps Troubleshooting

graph TD
    Flux[Flux Issue] --> Source[Source Controller]
    Flux --> Kust[Kustomize Controller]
    Flux --> Helm[Helm Controller]

    Source --> Git[Git Repository]
    Kust --> Sync[Sync Status]
    Helm --> Release[Release Status]

Resolution Steps:

# Check Flux components
flux check

# Check sources
flux get sources git
flux get sources helm

# Check reconciliation
flux get kustomizations
flux get helmreleases

Performance Issues

Resource Constraints

graph LR
    Perf[Performance] --> CPU[CPU Usage]
    Perf --> Memory[Memory Usage]
    Perf --> IO[I/O Usage]

    CPU --> Limit[Resource Limits]
    Memory --> Constraint[Memory Constraints]
    IO --> Bottleneck[I/O Bottleneck]

Analysis Commands:

# Check resource usage
kubectl top pods -n <namespace>
kubectl top nodes

# Check resource quotas
kubectl get resourcequota -n <namespace>

Recovery Procedures

1. Node Recovery

  1. Drain node
  2. Perform maintenance
  3. Uncordon node
  4. Verify workloads

2. Storage Recovery

  1. Backup data
  2. Fix storage issues
  3. Restore data
  4. Verify access

3. Network Recovery

  1. Check connectivity
  2. Verify DNS
  3. Test ingress
  4. Update policies

Best Practices

1. Logging

  • Maintain detailed logs
  • Set appropriate retention
  • Use structured logging
  • Enable audit logging

2. Monitoring

  • Set up alerts
  • Monitor resources
  • Track metrics
  • Use dashboards

3. Documentation

  • Document issues
  • Record solutions
  • Update procedures
  • Share knowledge

Emergency Procedures

Critical Issues

  1. Assess impact
  2. Implement temporary fix
  3. Plan permanent solution
  4. Update documentation

Contact Information

  • Maintain escalation paths
  • Keep contact list updated
  • Document response times
  • Track incidents