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Container data can be lost unless stored in persistent volumes.

Data lakes store large volumes of diverse data for analytics and processing.

Data Lakehouse architecture merges flexible data storage with reliable analytics capabilities.

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

Cassandra uses a masterless architecture to distribute and replicate data efficiently.

Stateless servers are easier to scale because they don't store user session data locally.

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.

Backup strategies include Full, Incremental, and Differential, each with unique benefits.

Dynamo-style databases are designed for high availability and fault tolerance in distributed systems.

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.

Encryption at rest and in transit are essential for protecting data both stored and in motion.

MongoDB uses replica sets for data redundancy and sharding for scalability.

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

Availability Zones help prevent downtime by isolating failures across multiple locations.

Replicas keep your system available, while snapshots allow for data recovery.

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

Kafka Streams uses local state for quick data access and changelogs for recovery.

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

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

Elasticsearch uses distributed architecture to search data quickly across multiple servers.

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

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

Kubernetes uses a Control Plane to manage Worker Nodes and ensure application reliability.

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

Cassandra uses clustering keys to sort rows within a partition for efficient querying.

Kubernetes uses Pods, ReplicaSets, and Deployments to manage application availability and updates.

Kafka uses state stores to remember previous events in stateful stream processing.

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.

FAANG engineers use high-level design principles to create scalable systems.

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

Structured logging helps in quickly identifying issues by organizing log data consistently.

Cross-region database replication keeps databases synchronized across different geographical locations.

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

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

OAuth 2.0 lets apps access user data securely without passwords.

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.

HTTPS is a secure version of HTTP that encrypts data for safety.

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.

Cache eviction policies determine which data to remove when caches are full.

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.