docs: Blog post about Feature Server Sub-2ms Performance#6465
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Signed-off-by: ntkathole <nikhilkathole2683@gmail.com>
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What this PR does / why we need it:
Adds a blog post documenting a performance tuning exercise for the
Feast Python feature server on Kubernetes, covering the full journey from
default configuration to sub-2ms p99 latency.
The post covers:
HPA), client-side tuning (connection pooling, access mode selection), and
code-level enhancements (serialization optimization, async batched pipelines,
cached checks, session wrapping fix).
decisions, and benchmark results showing 6–9x speedup over the regular
per-feature-view read path.