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Items tagged brandurleach in Nov, 2017

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Scaling Postgres with Read Replicas & Using WAL to Counter Stale Reads (via) The problem with sending writes to the primary and balancing reads across replicas is dealing with replica lag—what if you write to the primary and then read from a replica that hasn’t had the new state applied to it yet? Brandur Leach dives deep into an elegant solution using PostgreSQL’s LSN (log sequence numbers) accesesed using pg_last_wal_replay_lsn(). An observer process continuously polls the replicas for their most recently applied LSN and stores them in a table. A column in the Users table then records the min_lsn valid for that user, updating it to the pg_current_wal_lsn() of the primary whenever that user makes a write. Combining the two allows the application to randomly select a replica that is up-to-date for the purposes of a specific user any time it needs to make a read. # 18th November 2017, 6:42 pm

Redis Streams and the Unified Log. In which Brandur Leach explores the new Kafka-style streams functionality coming to Redis 4.0, and shows an example of a robust at-least once processing architecture built on a combination of Redis streams and PostgreSQL transactions. I really like the pattern of writing log records to a staging table in PostgreSQL first in order to bundle them up in the same transaction as the originating state change, then have a separate process read them from that table and publish them to Redis. # 8th November 2017, 4:37 pm

Redis streams aren’t exciting for their innovativeness, but rather than they bring building a unified log architecture within reach of a small and/or inexpensive app. Kafka is infamously difficult to configure and get running, and is expensive to operate once you do. [...] Redis on the other hand is probably already in your stack.

Brandur Leach # 8th November 2017, 4:23 pm

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