The Agent Harness: Where Reliability Actually Lives
The model is a dependency you will swap twice a year; the harness around it is the product. A redesigned architecture, stage by stage, and an honest guess at where failures come from.
Notes on caching, vector search, agentic memory and production architecture.
The model is a dependency you will swap twice a year; the harness around it is the product. A redesigned architecture, stage by stage, and an honest guess at where failures come from.
Redis has two ways to search vectors and the docs never put them side by side. One is a data type, the other a search engine, and cluster mode settles it more often than latency does.
Catalogue, rights windows and entitlements are a near-perfect fit. Watch progress, session limits and live feeds are not, and the two look alike on a whiteboard.
Break-even sits near a 1% hit rate, so the cost case is easy. The threshold, the tenant boundary and what you refuse to cache are where it actually gets decided.
How RDI is actually built, from Debezium through to the three planes, and the specific workloads where it is the wrong answer. Including the throughput numbers worth memorising.
SELECT looks like free multi-tenancy until it follows you into production. Where the model breaks down, why it does not exist in Cluster Mode, and what proper isolation looks like.
MGET is fine until Cluster Mode returns CROSSSLOT. Hash tags, pipelining and data modelling are the real fixes, and Lua is not one of them.
Import and export for a maintenance window, RIOT for near-zero downtime. But the data copy is the easy half; the client-side assumptions are what decide the cutover.