Comment on The infrastructure behind modern ranking systems (serving, data, MLOps)Comments−semi_sentientOP10moFollow-up posts for context (same series):Part 2 – Data Layer (feature store to prevent online/offline skew; vector DB choices and pre- vs post-filtering): https://www.shaped.ai/blog/the-infrastructure-of-modern-rank...Part 3 – MLOps Backbone (training pipelines, registry, GitOps deployment, monitoring/drift/A-B): https://www.shaped.ai/blog/the-infrastructure-of-modern-rank...Happy to share more detail (autoscaling policies, index swaps, point-in-time joins, GPU batching) if helpful.
Comments
Follow-up posts for context (same series):
Part 2 – Data Layer (feature store to prevent online/offline skew; vector DB choices and pre- vs post-filtering): https://www.shaped.ai/blog/the-infrastructure-of-modern-rank...
Part 3 – MLOps Backbone (training pipelines, registry, GitOps deployment, monitoring/drift/A-B): https://www.shaped.ai/blog/the-infrastructure-of-modern-rank...
Happy to share more detail (autoscaling policies, index swaps, point-in-time joins, GPU batching) if helpful.