Meaning
A computing architecture consists of multiple autonomous computers that communicate through a network to coordinate their actions. In distributed systems, these separate machines cooperate to solve a common problem while appearing to the end-user as a single coherent system. This approach allows for horizontal scaling and prevents a single point of failure from disabling the entire system.
Network Communication
Nodes must exchange messages across a network to synchronize their activities because they do not share a common clock or memory. In distributed systems, this reliance on networks introduces latencies and the possibility of message loss or reordering. Consequently, protocols must be designed to handle these network issues to ensure that the system remains correct under varying loads.
State Consistency
Maintaining a single agreed-upon state across all nodes is one of the most difficult challenges when building these networks. For distributed systems, consistency models like linearizability or eventual consistency define how updates are propagated and visible to different nodes. In cases where network partitions occur, the system must choose between consistency and availability, which is a fundamental trade-off.
Fault Tolerance
Designing these architectures requires a resilient strategy for handling the failure of individual nodes or network links. In distributed systems, replication is used to ensure that data is not lost when a single node fails, and consensus algorithms help the remaining nodes agree on the state. This redundancy is expensive in terms of network bandwidth and storage, but it prevents the entire system from going offline when a hardware failure occurs.
It also reduces the likelihood of long outages by allowing the system to continue operating even when several nodes are offline or unreachable, which is essential for modern high-availability applications.
