// There are no clear architecture patterns for the Cloud? (Azure Mythbusters)

Cloud does not lack architecture patterns — the Azure Architecture Center hosts a large and growing catalogue, and many patterns predating cloud remain equally applicable in distributed systems today.

The episode walks through four patterns in depth:

• Cache-aside — lazily populates a cache by reading from the data store on a cache miss and storing the result so subsequent reads are served from cache. Key considerations include cache expiry, eviction policy, and write invalidation (remove from cache on write so the next read refreshes it).
• Circuit breaker — prevents cascading failures by tracking a downstream dependency’s health through three states: closed (normal traffic), open (dependency known-failed, calls rejected immediately), and half-open (probe traffic allowed to test recovery). Requires a companion pattern (e.g., queue-based load levelling) to handle traffic diverted when the circuit is open.
• Health endpoint monitoring — extends a simple liveness probe to a deep health check that queries each sub-component (database, queue, cache) and aggregates their status, making it especially valuable in microservices architectures to surface partial failures before they cascade.
• Materialized view — pre-aggregates data from an ingestion store into a query-optimised read model, commonly used with event sourcing and CQRS to separate the write model from the reporting view without running expensive aggregation queries at read time.