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Cloud-Native Application Guidelines

This document outlines the standards and best practices for developing cloud-native applications at Bayat.

Table of Contents

  1. Introduction
  2. Cloud-Native Architecture Principles
  3. Multi-Cloud Strategy
  4. Provider-Specific Guidelines
  5. Serverless Architecture
  6. Containerization
  7. Infrastructure as Code
  8. Observability
  9. Cost Optimization
  10. Security
  11. Disaster Recovery

Introduction

Cloud-native applications are designed and built to exploit the characteristics of cloud computing delivery models. These applications are developed to leverage cloud services, scale elastically, and be resilient to failures.

Core Characteristics

  • Microservices architecture: Building small, focused services rather than monolithic applications
  • Containerization: Packaging applications in containers for consistent deployment
  • Dynamic orchestration: Using container orchestrators like Kubernetes to manage deployments
  • API-driven communication: Services communicate through well-defined APIs
  • Infrastructure automation: Using IaC to provision and manage resources

Cloud-Native Architecture Principles

Design Principles

  1. Design for self-healing

    • Implement health checks and automated recovery
    • Define appropriate liveness and readiness probes
    • Build circuit breakers for service dependencies

  2. Design for scalability

    • Create stateless services where possible
    • Implement horizontal scaling over vertical scaling
    • Design for zero-downtime deployments

  3. Design for observability

    • Implement consistent logging patterns
    • Use structured logging formats (JSON)
    • Define and track key metrics
    • Implement distributed tracing

  4. Design for automation

    • Automate all aspects of the software delivery lifecycle
    • Implement CI/CD pipelines
    • Use infrastructure as code for all environments

Application Patterns

  • Event-driven architecture: Use events to coordinate between services
  • CQRS pattern: Separate read and write operations for better scalability
  • API Gateway pattern: Centralize API access through a gateway
  • Sidecar pattern: Deploy helper containers alongside application containers
  • Circuit Breaker pattern: Handle failures in service dependencies gracefully

Multi-Cloud Strategy

When to Use Multi-Cloud

  • Business continuity requirements
  • Regulatory compliance requirements
  • Leveraging unique services from different providers
  • Avoiding vendor lock-in

Implementation Strategies

  1. Abstraction Layer Approach

    • Implement abstraction layers over cloud-specific services
    • Use cloud-agnostic frameworks and libraries
    • Standardize on common denominators across providers

  2. Best-of-Breed Approach

    • Use specific providers for their strengths
    • Implement robust integration between clouds
    • Accept some provider-specific implementations

  3. Redundant Implementation

    • Deploy the same application across multiple clouds
    • Implement traffic routing and load balancing
    • Use global DNS and CDN services

Challenges and Mitigations

  • Complexity: Document architecture decisions and standardize approaches
  • Cost: Implement cloud cost management and optimization tools
  • Skill sets: Train teams on multiple cloud platforms
  • Data synchronization: Implement robust data replication strategies

Provider-Specific Guidelines

AWS

  • Use AWS Well-Architected Framework
  • Prefer managed services over self-managed alternatives
  • Implement AWS-specific security best practices:
    • Least privilege IAM policies
    • S3 bucket security
    • KMS for encryption

Recommended Services:

  • Compute: ECS/EKS for containers, Lambda for serverless
  • Storage: S3 for objects, RDS for relational data, DynamoDB for NoSQL
  • Networking: VPC, CloudFront, Route53
  • Integration: SQS, SNS, EventBridge

Azure

  • Follow Azure Well-Architected Framework
  • Use Azure Resource Manager templates for IaC
  • Implement Azure-specific security best practices:
    • Azure Active Directory integration
    • Role-based access control
    • Key Vault for secrets

Recommended Services:

  • Compute: AKS for containers, Azure Functions for serverless
  • Storage: Blob Storage, Azure SQL, Cosmos DB
  • Networking: VNET, Front Door, Azure DNS
  • Integration: Service Bus, Event Grid

GCP

  • Follow Google Cloud Architecture Framework
  • Use Cloud Deployment Manager or Terraform
  • Implement GCP-specific security best practices:
    • Service accounts with minimal permissions
    • Cloud KMS for key management
    • VPC Service Controls

Recommended Services:

  • Compute: GKE for containers, Cloud Functions for serverless
  • Storage: Cloud Storage, Cloud SQL, Firestore
  • Networking: VPC, Cloud CDN, Cloud DNS
  • Integration: Pub/Sub, Cloud Tasks

Serverless Architecture

Use Cases

  • Event-driven processing
  • Microservices implementation
  • Backend APIs
  • Real-time file processing
  • Scheduled tasks
  • Stream processing

Design Patterns

  1. Function Composition Pattern

    • Chain functions together to create workflows
    • Use event triggers to coordinate function execution

  2. Routing Pattern

    • Route events to appropriate functions
    • Implement event filtering and transformation

  3. Aggregator Pattern

    • Collect data from multiple sources
    • Combine and process data before storage

  4. Saga Pattern

    • Implement distributed transactions
    • Use compensation actions for rollbacks

Best Practices

  • Keep functions focused and small
  • Design for cold starts
  • Implement proper error handling and retries
  • Optimize function dependencies and package size
  • Use environment variables for configuration
  • Implement proper logging and monitoring

Challenges and Mitigations

  • Cold starts: Optimize code, use provisioned concurrency
  • Debugging: Implement comprehensive logging, use tracing
  • Testing: Create local testing environments, use mocks
  • Vendor lock-in: Use abstraction layers, focus on standards

Containerization

Refer to the \1\2) document for comprehensive guidelines.

Infrastructure as Code

Refer to the \1\2) document for comprehensive guidelines.

Observability

Logging Strategy

  • Use structured logging (JSON format)
  • Include consistent fields in all logs:
    • Timestamp
    • Service name
    • Request ID (trace ID)
    • Log level
    • Short message
    • Detailed context
  • Implement appropriate log levels
  • Centralize log aggregation

Metrics Collection

  • Define key performance indicators (KPIs)
  • Implement the RED method:
    • Rate: Requests per second
    • Errors: Failed requests per second
    • Duration: Distribution of request latencies
  • Implement the USE method:
    • Utilization: Percent time the resource is busy
    • Saturation: Amount of work resource has to do
    • Errors: Count of error events

Distributed Tracing

  • Implement trace context propagation
  • Use standard tracing libraries (OpenTelemetry)
  • Sample traces appropriately
  • Create meaningful span names
  • Add relevant attributes to spans

Dashboard and Alerting

  • Create dashboards for key metrics
  • Implement alerting for critical conditions
  • Avoid alert fatigue by tuning thresholds
  • Implement escalation policies
  • Document incident response procedures

Cost Optimization

Cost Management Principles

  1. Right-sizing resources

    • Match resource capacity to requirements
    • Implement autoscaling
    • Use appropriate instance types

  2. Elasticity

    • Scale resources based on demand
    • Schedule scaling for predictable workloads
    • Implement scale-to-zero when possible

  3. Reserved capacity

    • Use reserved instances for stable workloads
    • Implement savings plans
    • Balance on-demand and reserved resources

  4. Storage optimization

    • Use appropriate storage tiers
    • Implement lifecycle policies
    • Compress and optimize data

Monitoring and Analysis

  • Implement cloud cost allocation tags
  • Set up cost monitoring and alerting
  • Perform regular cost reviews
  • Identify and eliminate waste

Cost Optimization Tools

  • Use cloud provider cost management tools
  • Implement third-party optimization tools
  • Set up resource scheduling

Security

Identity and Access Management

  • Implement least privilege principles
  • Use temporary credentials
  • Implement MFA for all user accounts
  • Regularly audit access permissions

Data Protection

  • Encrypt data at rest and in transit
  • Implement secure key management
  • Classify data according to sensitivity
  • Implement data loss prevention measures

Network Security

  • Implement network segmentation
  • Use private connectivity where possible
  • Configure proper security groups and firewall rules
  • Implement DDoS protection

Security Monitoring

  • Enable cloud provider security services
  • Implement automated vulnerability scanning
  • Set up security event monitoring
  • Conduct regular security reviews

Disaster Recovery

DR Strategy

  • Define recovery time objectives (RTO)
  • Define recovery point objectives (RPO)
  • Implement appropriate backup strategies
  • Document disaster recovery procedures

DR Patterns

  1. Backup and Restore

    • Regular backups stored in multiple regions
    • Tested restoration procedures
    • Automated backup verification

  2. Pilot Light

    • Minimal version of environment in standby
    • Core systems ready to scale
    • Regular synchronization of data

  3. Warm Standby

    • Scaled-down but functional copy
    • Regular data replication
    • Ready for traffic redirection

  4. Multi-Site Active/Active

    • Full applications running in multiple regions
    • Load balancing across regions
    • Automatic failover capabilities

Testing and Validation

  • Conduct regular DR drills
  • Document results and improvements
  • Automate recovery where possible
  • Validate RPO and RTO metrics