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Topic · IT & Coding
distributed systems
60 shorts across 1 course, in learning order
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Results · 9 for “Distributed Transactions”
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⚡ One HLD concept. 60 seconds. Interview ready
Kafka Exactly-Once Processing: Avoiding Duplicates
Kafka can help ensure messages are processed once, but requires careful design.
⚡ One HLD concept. 60 seconds. Interview ready
Understanding Lamport Timestamps in Distributed Systems
Lamport Timestamps help order events in distributed systems while preserving causality.
⚡ One HLD concept. 60 seconds. Interview ready
Understanding Distributed Clocks in Systems Design
In distributed systems, timestamps don't always reflect the true order of events.
⚡ One HLD concept. 60 seconds. Interview ready
Paxos Consensus: Understanding Distributed Agreement
Paxos is a protocol that helps distributed systems agree on one value despite failures.
⚡ One HLD concept. 60 seconds. Interview ready
Message Delivery Semantics: At-Most-Once vs At-Least-Once vs Exactly-Once
Message delivery semantics define how messages are sent in distributed systems and handle failures.
⚡ One HLD concept. 60 seconds. Interview ready
Understanding Network Partitions in Distributed Systems
Network partitions occur when servers are operational but can't communicate, affecting system performance.
⚡ One HLD concept. 60 seconds. Interview ready
Understanding Idempotency in System Design
Idempotency ensures that repeated operations in APIs do not cause duplicate effects.
⚡ One HLD concept. 60 seconds. Interview ready
Understanding CAP Theorem: Trade-offs in Distributed Systems
The CAP Theorem explains the trade-offs in distributed systems during network failures.
⚡ One HLD concept. 60 seconds. Interview ready
Log Replication and Majority Commit in Distributed Systems
Log replication ensures data consistency by requiring majority acknowledgment before committing changes.
🧠Related by meaning
Not tagged “distributed systems”, but closely connected
