Distributed System Architecture
Updated 2026-08-10
INTRODUCTION
English translation pending.
CORE DEFINITION
A distributed system architecture deploys functional units across multiple nodes that communicate by protocol to deliver one service. The goal is to avoid single points of failure and bottlenecks: redundancy lets surviving nodes take over from a failed one, and load sharing lets capacity grow by adding nodes. Under the CAP constraint, the design must trade consistency, availability, and partition tolerance according to what the business can actually tolerate.
SCAFFOLDING EFFECT
Reduce cognitive load
- Remove the single point: replicate state so any one node can fail without loss. - Split the load: distribute work across nodes to grow capacity horizontally. - Choose the consistency level: match the tradeoff to what the business genuinely tolerates.
Anchor fast decisions
Coordination moves from one machine to a protocol. Because state is replicated and work is shared, the failure of a single node is absorbed by the others, which raises availability and lets capacity grow with nodes, at the cost of whatever consistency guarantees the protocol can still make.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Distributed_computingverified
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