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Distributed Systems

Availability Models
Highly available is too vague; watch out when you read or hear it.
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Teiva Harsanyi
Working on Complex Systems
This is why recognizing whether a system is complicated or complex is so important: it shapes how we should approach problem-solving.
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Teiva Harsanyi
Bloom Filters
Bloom filters offer a space-efficient solution for checking set membership, trading accuracy for reduced memory usage.
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Teiva Harsanyi
Probabilistic Increment
This problem here is called a hot row, and it occurs when a specific row in the database is modified frequently by multiple concurrent transactions.
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Teiva Harsanyi
9
Exploring Database Isolation Levels
The higher the isolation level, the more anomalies are prevented—but it comes at a cost.
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Teiva Harsanyi
2
Latency and User Experience
Sometimes, we can’t make things faster—but we can make them feel faster.
 • 
Teiva Harsanyi
Consensus
Consensus ensures that all nodes in a distributed system agree on the same value, even in the presence of failures or network partitions.
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Teiva Harsanyi
Consistency Model
Stronger consistency models come with trade-offs: higher overhead and slower performance, while weaker consistency improves speed by tolerating…
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Teiva Harsanyi
Isolation Level
Strong isolation levels ensure data consistency, but at the cost of performance, while weaker isolation levels improve performance but increase the risk…
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Teiva Harsanyi
Transactions
Only transactions with the highest isolation level are fully ACID-compliant, ensuring strict adherence to all ACID properties.
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Teiva Harsanyi
Safety and Liveness
In leader election, avoiding two nodes mistakenly thinking they are the leader is a safety property, while guaranteeing the process eventually completes…
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Teiva Harsanyi
The PACELC Theorem
The PACELC theorem provides a more comprehensive framework for reasoning about distributed systems, ensuring we consider both partition scenarios and…
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Teiva Harsanyi
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