# 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