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Deployment & Operational Patterns

Compute Resource Consolidation Pattern

Problem: Multiple tasks consume resources inefficiently when isolated.

Solution: Consolidate multiple tasks or operations into a single computational unit.

When to Use:

  • Reducing infrastructure costs
  • Improving resource utilization
  • Simplifying deployment and management

Implementation Considerations:

  • Group related tasks with similar scaling requirements
  • Use containers or microservices hosting
  • Monitor resource usage per task
  • Ensure isolation where needed for security/reliability
  • Balance between consolidation and failure isolation

Deployment Stamps Pattern

Problem: Applications need to scale across regions or customer segments.

Solution: Deploy multiple independent copies of application components (stamps), including data stores, to serve different regions or customer segments.

When to Use:

  • Scaling beyond single stamp limits
  • Providing regional data residency
  • Isolating tenants for security or performance

Implementation Considerations:

  • Each stamp is a complete, self-contained deployment
  • Deploy stamps across regions for geo-distribution
  • Route requests to appropriate stamp
  • Manage stamp deployments consistently (IaC)
  • Plan for stamp capacity and when to add new stamps

External Configuration Store Pattern

Problem: Application configuration is embedded in deployment packages.

Solution: Move configuration information out of the application deployment package to a centralized location.

When to Use:

  • Managing configuration across multiple environments
  • Updating configuration without redeployment
  • Sharing configuration across multiple applications

Implementation Considerations:

  • Use Azure App Configuration, Key Vault, or similar services
  • Implement configuration change notifications
  • Cache configuration locally to reduce dependencies
  • Secure sensitive configuration (connection strings, secrets)
  • Version configuration changes

Geode Pattern

Problem: Users in different regions experience high latency.

Solution: Deploy backend services into a set of geographical nodes, each of which can service any client request in any region.

When to Use:

  • Reducing latency for globally distributed users
  • Providing high availability across regions
  • Implementing active-active geo-distribution

Implementation Considerations:

  • Deploy application instances in multiple regions
  • Replicate data globally (consider consistency implications)
  • Route users to nearest healthy region
  • Implement conflict resolution for multi-master writes
  • Monitor regional health and performance

Static Content Hosting Pattern

Problem: Serving static content from compute instances is inefficient.

Solution: Deploy static content to a cloud-based storage service that can deliver content directly to the client.

When to Use:

  • Hosting images, videos, CSS, JavaScript files
  • Reducing load on web servers
  • Improving content delivery performance

Implementation Considerations:

  • Use blob storage, CDN, or static website hosting
  • Enable CORS for cross-origin access
  • Implement caching headers appropriately
  • Use CDN for global content distribution
  • Secure content with SAS tokens if needed