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