Deploying Pixashot

Comprehensive guide to Pixashot deployment options, platform comparisons, and deployment strategy selection.

Quick Platform Comparison

Feature Google Cloud Run Docker Self-Hosted AWS ECS/Fargate Azure Container Apps
Management Overhead Minimal High Medium Medium
Auto-scaling Yes Manual Yes Yes
Cost Model Pay-per-use Fixed + Variable Pay-per-use Pay-per-use
Cold Starts Yes No No Yes
Max Memory 32GB Unlimited 120GB 32GB
Setup Complexity Low High Medium Low
Monitoring Built-in Manual Built-in Built-in
Offline Support No Yes No No

Platform Deep Dives

# Basic deployment
gcloud run deploy pixashot \
  --image gpriday/pixashot:latest \
  --memory 2Gi \
  --cpu 1 \
  --min-instances 1 \
  --max-instances 10

Ideal Use Cases

  • Most production deployments
  • Variable traffic patterns
  • Cost-sensitive deployments
  • Global distribution needs
  • Serverless preferences

Key Benefits

  • Zero infrastructure management
  • Automatic scaling
  • Pay-per-use pricing
  • Built-in monitoring
  • Global deployment options
  • Easy integration with other GCP services

Limitations

  • Cold starts (mitigatable)
  • 32GB memory limit
  • Regional deployment required
  • No persistent storage

Docker Self-Hosted

# Production deployment example
docker run -d \
  --name pixashot \
  --memory=4g \
  --cpus=2 \
  --restart=unless-stopped \
  -e AUTH_TOKEN=${AUTH_TOKEN} \
  -e WORKERS=4 \
  -p 8080:8080 \
  gpriday/pixashot:latest

Ideal Use Cases

  • Local development
  • Air-gapped environments
  • Complete control requirements
  • Existing infrastructure
  • Specific compliance needs

Key Benefits

  • Complete control
  • No vendor lock-in
  • Predictable costs
  • Offline capability
  • Custom hardware options
  • Direct resource access

Limitations

  • Manual scaling
  • Infrastructure management
  • Operational overhead
  • Self-managed security
  • Manual monitoring setup

AWS ECS/Fargate

# Task definition example
{
  "family": "pixashot",
  "containerDefinitions": [{
    "name": "pixashot",
    "image": "gpriday/pixashot:latest",
    "memory": 2048,
    "cpu": 1024,
    "essential": true,
    "portMappings": [{
      "containerPort": 8080,
      "protocol": "tcp"
    }],
    "environment": [{
      "name": "AUTH_TOKEN",
      "value": "your_secret_token"
    }]
  }]
}

Ideal Use Cases

  • AWS-integrated systems
  • Complex networking needs
  • Regional deployment requirements
  • High availability needs
  • Existing AWS expertise

Key Benefits

  • AWS ecosystem integration
  • Flexible scaling
  • Rich monitoring
  • VPC integration
  • Route 53 integration
  • Load balancer integration

Limitations

  • Setup complexity
  • Cost management needs
  • AWS knowledge required
  • Initial configuration time

Azure Container Apps

# Basic deployment
az containerapp create \
  --name pixashot \
  --resource-group mygroup \
  --image gpriday/pixashot:latest \
  --target-port 8080 \
  --ingress external \
  --cpu 1.0 \
  --memory 2.0Gi

Ideal Use Cases

  • Azure-integrated systems
  • Simple deployment needs
  • Microsoft ecosystem
  • Existing Azure expertise

Key Benefits

  • Azure ecosystem integration
  • Simple deployment
  • Built-in monitoring
  • Azure DevOps integration
  • Key Vault integration

Limitations

  • Scale limitations
  • Cost optimization needs
  • Regional constraints
  • Cold start impact

Resource Planning

Development Environment

Minimum Requirements:
- CPU: 1 core
- RAM: 2GB
- Storage: 1GB
- Network: Basic internet

Production Environment

Recommended Requirements:
- CPU: 2+ cores
- RAM: 4GB+
- Storage: 5GB+
- Network: Low-latency

High-Traffic Environment

Enterprise Requirements:
- CPU: 4+ cores
- RAM: 8GB+
- Storage: 10GB+
- Network: High bandwidth

Cost Optimization Strategies

Free Tier Maximization

  1. Google Cloud Run
  • 2M requests/month free
  • Optimize instance count
  • Use minimum instances wisely
  • Monitor cold starts
  1. AWS Fargate
  • Use Spot instances
  • Implement auto-scaling
  • Optimize task size
  • Use Application Load Balancer
  1. Azure Container Apps
  • Use consumption plan
  • Optimize scaling rules
  • Monitor instance usage
  • Use reserved instances

Cost Control Measures

# Example budget alert (GCP)
gcloud billing budgets create \
  --billing-account=$BILLING_ACCOUNT_ID \
  --display-name="Pixashot Budget" \
  --budget-amount=100 \
  --threshold-rule=percent=80

Deployment Checklist

Pre-Deployment

  • Choose deployment platform
  • Calculate resource requirements
  • Plan monitoring strategy
  • Set up security measures
  • Configure backup strategy

Deployment

  • Set up authentication
  • Configure networking
  • Set resource limits
  • Enable monitoring
  • Configure scaling rules

Post-Deployment

  • Verify health checks
  • Test performance
  • Monitor resources
  • Set up alerts
  • Document deployment

Common Issues & Solutions

Performance Optimization

# Example monitoring setup (Docker)
docker stats pixashot --format \
  "table {{.Container}}\t{{.CPUPerc}}\t{{.MemUsage}}"

Memory Issues

  • Monitor usage patterns
  • Set appropriate limits
  • Implement cleanup routines
  • Use proper scaling rules

Network Issues

  • Configure timeouts
  • Implement retry logic
  • Use health checks
  • Monitor latency

Security Concerns

  • Implement authentication
  • Configure network policies
  • Enable rate limiting
  • Regular security audits

Monitoring Setup

Health Endpoints

# Basic health monitoring
curl http://your-instance/health/live
curl http://your-instance/health/ready
curl http://your-instance/health/metrics

Key Metrics

  1. System Health
  • CPU utilization
  • Memory usage
  • Disk I/O
  • Network traffic
  1. Application Metrics
  • Request latency
  • Error rates
  • Success rates
  • Queue length
  1. Business Metrics
  • Capture success rate
  • Processing time
  • Cache hit ratio
  • Cost per capture

Next Steps

Platform-Specific Guides

Additional Resources

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