This post is explains how we developed personalized snippet suggestions without storing user text. We utilize locality-sensitive hashing (SimHash) to identify frequently used sentences, ensuring user privacy. This method enhances productivity by offering tailored suggestions while safeguarding data security.
This story is about how we faced some critical performance issues with one of our database replicas and how we resolved all that burden with the correct Postgres autovacuum config.
In this post, we're going to analyze different QEMU features that may help live migrations converge. The most important features are Post-Copy and Auto-Converge.