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

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

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

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

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

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

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

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

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

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

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

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

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

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

Fault domains help prevent multiple servers from failing together in an architecture.

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

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

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

Disaster recovery ensures systems can restore services and data after major disruptions.

Choosing the right boundaries for microservices is crucial for effective architecture.

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

Time-series databases are designed to store and query time-stamped metrics efficiently.

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

CQRS separates how we change data from how we read data, improving scalability.

OLTP handles transactions while OLAP is for data analysis and reporting.

Availability is about access; reliability is about correct performance.

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

High Availability ensures your application remains operational even during server failures.

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

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

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