A distributed system is a collection of independent computers that appear to its users as a single coherent system.

• Resource Sharing: Sharing storage, computational power, or data.
• Reliability: If one node fails, others can take its place.
• Scalability: Add more nodes to handle more load.

• Transparency: The user shouldn't know they are interacting with multiple machines.
• Concurrency: Components execute in parallel.
• No Global Clock: Each node has its own timing; ordering events is a challenge (see Lamport timestamps).
• Independent Failures: Parts of the system may fail while others continue to work.

• Remote Procedure Call (RPC): Making a function call on a remote server as if it were local (e.g., gRPC, Thrift).
• Message Passing: Sending asynchronous messages (e.g., RabbitMQ, Kafka).

• Network Partitions: The "split-brain" scenario where nodes cannot see each other.
• Data Consistency: Synchronization across multiple physical locations.
• Latency: Communication over a network is orders of magnitude slower than local memory access.