cloud-platforms

name	cloud-platforms
description	AWS, Azure, and GCP cloud services and best practices

Cloud Platforms

AWS Services and Best Practices

Compute Services

• EC2 (Elastic Compute Cloud): Virtual servers in the cloud

  • Use instance types appropriate for workload requirements
  • Implement Auto Scaling Groups for elasticity
  • Use Spot Instances for fault-tolerant, interruptible workloads
  • Leverage EC2 Fleet for diverse instance strategies

• Lambda: Serverless compute service

  • Ideal for event-driven architectures
  • Use for short-lived, stateless functions
  • Implement dead-letter queues for failed invocations
  • Monitor with CloudWatch metrics and logs

• ECS (Elastic Container Service): Container orchestration

  • Use Fargate for serverless container execution
  • Implement task definitions with resource limits
  • Use service auto-scaling based on metrics
  • Configure load balancing with ALB/NLB

• EKS (Elastic Kubernetes Service): Managed Kubernetes

  • Use managed node groups for simplified operations
  • Implement pod autoscaling (HPA, VPA)
  • Use AWS VPC CNI for networking
  • Integrate with IAM for service accounts

Storage Services

• S3 (Simple Storage Service): Object storage

  • Use lifecycle policies for cost optimization
  • Implement versioning for data protection
  • Use S3 Transfer Acceleration for faster uploads
  • Configure CORS for cross-origin access
  • Enable S3 Event Notifications for automation

• EBS (Elastic Block Store): Block storage

  • Choose volume type based on workload (gp3, io2, etc.)
  • Use multi-attach for high availability
  • Implement snapshots for backup
  • Monitor volume metrics for performance

Database Services

• RDS (Relational Database Service): Managed relational databases

  • Use Multi-AZ deployments for high availability
  • Enable read replicas for scaling reads
  • Use automated backups and point-in-time recovery
  • Implement parameter groups for configuration

• DynamoDB: NoSQL database

  • Design partition keys for even distribution
  • Use on-demand mode for unpredictable workloads
  • Implement TTL for automatic data expiration
  • Use DynamoDB Accelerator (DAX) for caching

Infrastructure as Code

• CloudFormation: AWS native IaC
  • Use stacks for resource organization
  • Implement nested stacks for modularity
  • Use change sets for safe updates
  • Leverage CloudFormation exports for cross-stack references

Networking

• VPC (Virtual Private Cloud): Isolated network environment
  • Use public and private subnets for tiered architecture
  • Implement NAT Gateways for private subnet outbound access
  • Use VPC endpoints for private connectivity to AWS services
  • Configure route tables and security groups properly

Azure Services and Best Practices

Compute Services

• Azure Virtual Machines: Virtual servers

  • Use managed disks for storage
  • Implement availability sets for high availability
  • Use Azure Spot VMs for cost savings
  • Configure extensions for monitoring and management

• Azure Functions: Serverless compute

  • Use Consumption plan for event-driven workloads
  • Implement Durable Functions for stateful orchestrations
  • Use Application Insights for monitoring
  • Configure function app scaling

• Azure Kubernetes Service (AKS): Managed Kubernetes

  • Use Azure CNI for advanced networking
  • Implement cluster autoscaler
  • Use Azure AD integration for authentication
  • Configure pod identity for secure access to Azure resources

Storage Services

• Azure Blob Storage: Object storage

  • Use access tiers (Hot, Cool, Archive) for cost optimization
  • Implement lifecycle management policies
  • Use blob versioning for data protection
  • Configure CORS and shared access signatures

• Azure Disk Storage: Block storage

  • Choose disk type based on workload (Premium SSD, Ultra Disk)
  • Use Azure Disk Encryption for data at rest
  • Implement snapshots for backup
  • Monitor disk performance metrics

Database Services

• Azure SQL Database: Managed SQL database

  • Use vCore-based or DTU-based purchasing models
  • Implement geo-replication for disaster recovery
  • Use transparent data encryption
  • Configure automatic backups

• Azure Cosmos DB: Globally distributed NoSQL database

  • Choose appropriate API (SQL, MongoDB, Cassandra, etc.)
  • Use multi-master replication for global availability
  • Implement consistency levels based on requirements
  • Use throughput provisioning with RU/s

Infrastructure as Code

• Azure Resource Manager (ARM) Templates: Azure native IaC
  • Use parameter files for environment-specific configurations
  • Implement linked templates for modularity
  • Use deployment scripts for post-deployment actions
  • Leverage template specs for reusability

Networking

• Azure Virtual Network (VNet): Isolated network
  • Use subnets for network segmentation
  • Implement NSGs for security rules
  • Use Azure Firewall for network protection
  • Configure VNet peering for connectivity

GCP Services and Best Practices

Compute Services

• Compute Engine: Virtual machines

  • Use custom machine types for optimized workloads
  • Implement instance groups for auto-scaling
  • Use preemptible VMs for cost savings
  • Configure startup and shutdown scripts

• Cloud Functions: Serverless compute

  • Use 2nd generation functions for better performance
  • Implement event triggers for automation
  • Use Cloud Logging and Cloud Monitoring
  • Configure function deployment settings

• Google Kubernetes Engine (GKE): Managed Kubernetes

  • Use Autopilot for fully managed clusters
  • Implement node auto-provisioning
  • Use Workload Identity for secure access
  • Configure network policies for pod security

Storage Services

• Cloud Storage: Object storage

  • Use storage classes (Standard, Nearline, Coldline, Archive)
  • Implement lifecycle management rules
  • Use object versioning for data protection
  • Configure signed URLs and ACLs

• Persistent Disks: Block storage

  • Choose disk type (Standard, Balanced, Extreme)
  • Use regional disks for high availability
  • Implement snapshots for backup
  • Monitor disk I/O and throughput

Database Services

• Cloud SQL: Managed relational databases

  • Use high availability configuration
  • Implement read replicas for scaling
  • Use automated backups and point-in-time recovery
  • Configure SSL/TLS connections

• Cloud Spanner: Globally distributed SQL database

  • Use multi-region configuration for global availability
  • Design schema for optimal performance
  • Implement instance sizing and scaling
  • Use database roles for access control

Infrastructure as Code

• Deployment Manager: GCP native IaC
  • Use Jinja or Python templates
  • Implement composite types for reusability
  • Use deployment manifests for organization
  • Configure preview deployments

Networking

• Virtual Private Cloud (VPC): Isolated network
  • Use subnets for network segmentation
  • Implement VPC peering for connectivity
  • Use Cloud NAT for private subnet outbound access
  • Configure firewall rules for security

Multi-Cloud Strategies and Considerations

Multi-Cloud Approaches

• Multi-Cloud for Resilience: Distribute workloads across providers for disaster recovery
• Best-of-Breed Services: Use specific services from each provider based on strengths
• Vendor Lockout Mitigation: Avoid single-provider dependencies
• Cost Optimization: Leverage competitive pricing and spot markets

Multi-Cloud Challenges

• Complexity: Increased operational complexity and management overhead
• Consistency: Maintaining consistency across different platforms
• Networking: Cross-cloud connectivity and latency considerations
• Identity and Access Management: Unified identity across providers

Multi-Cloud Best Practices

• Abstraction Layers: Use abstraction layers (Terraform, Pulumi) for multi-cloud deployments
• Standardization: Standardize on common tools and practices
• Observability: Implement unified monitoring and logging across clouds
• Security: Implement consistent security policies across all platforms