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Data residency is crucial for compliance with laws about where data can be stored.

Distributed caching spreads data across multiple servers for better performance and reliability.

A CDN speeds up web applications by caching content closer to users.

Caching helps applications respond faster by serving data from memory instead of hitting the database.

Elasticsearch ILM automates index management to reduce storage costs and meet data needs.

Choosing between single and multi-region architecture affects system resilience and cost.

Redis is a fast in-memory data store used for caching and low-latency applications.

Sharding splits databases into smaller parts to improve performance and scalability.

Database per Service ensures each microservice owns its data, reducing dependencies.

Event Sourcing stores every action as an event to recreate the current state.

Session-based authentication uses cookies to remember users after login.

Choosing between a shared database and a database per service affects system design significantly.

Data warehouses help businesses analyze large amounts of data for better decision-making.

Elasticsearch Data Streams simplify time-series data management with one name for many indices.

Active-Active Architecture uses multiple regions to serve traffic simultaneously for better resilience.

The Cache-Aside Pattern speeds up data retrieval by using a cache to store frequently accessed data.

Search engines collect, index, retrieve, and rank documents to provide relevant results.

Retention policies help manage how long data is kept in databases.

Containers share the host OS kernel, while VMs virtualize hardware with separate OS.

The Transactional Outbox Pattern ensures database updates and event publishing are synchronized to avoid losing events.

Stream Processing Architecture helps turn incoming events into real-time insights efficiently.

Elasticsearch offers Data Streams for simplicity and Time-Based Indices for control in managing time-series data.

The choice between SQL and NoSQL databases depends on your application's specific needs.

Scaling databases involves deciding whether to enhance read or write capabilities based on traffic patterns.

Elasticsearch CCR allows real-time data replication for faster disaster recovery.

A single component's failure can take down your entire application, even with redundancy.