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2018-07-10-cloud-design-patterns.md

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layout title date comments categories language references
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Cloud Design Patterns
2018-07-10 11:16
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design patterns, system design
en

Availability patterns

  • Health Endpoint Monitoring: Implement functional checks in an application that external tools can access through exposed endpoints at regular intervals.
  • Queue-Based Load Leveling: Use a queue that acts as a buffer between a task and a service that it invokes in order to smooth intermittent heavy loads.
  • Throttling: Control the consumption of resources used by an instance of an application, an individual tenant, or an entire service.

Data Management patterns

  • Cache-Aside: Load data on demand into a cache from a data store
  • Command and Query Responsibility Segregation: Segregate operations that read data from operations that update data by using separate interfaces.
  • Event Sourcing: Use an append-only store to record the full series of events that describe actions taken on data in a domain.
  • Index Table: Create indexes over the fields in data stores that are frequently referenced by queries.
  • Materialized View: Generate prepopulated views over the data in one or more data stores when the data isn't ideally formatted for required query operations.
  • Sharding: Divide a data store into a set of horizontal partitions or shards.
  • Static Content Hosting: Deploy static content to a cloud-based storage service that can deliver them directly to the client.

Security Patterns

  • Federated Identity: Delegate authentication to an external identity provider.
  • Gatekeeper: Protect applications and services by using a dedicated host instance that acts as a broker between clients and the application or service, validates and sanitizes requests, and passes requests and data between them.
  • Valet Key: Use a token or key that provides clients with restricted direct access to a specific resource or service.