Blog
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What to monitor on a vector database
The handful of signals that predict an incident, the ones that only confirm one, and why recall needs a synthetic probe rather than a metric.
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When your vector database gets slow
A diagnosis order for rising query latency: read the percentile shape first, then work through memory, filters, segments, tombstones, and search parameters.
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Backing up a vector database
Snapshots, what they miss, and why a vector-store backup is only real once you've restored it and run a recall check against a known query set.
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Reindexing without downtime
Embedding model changed, so the whole index has to be rebuilt. Four strategies, what each costs in memory and complexity, and how to roll back.
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Sizing a vector index in memory
Why your index needs several times the RAM of the raw vectors, which terms drive the total, and how to estimate before you provision.