You're running gRPC services in Kubernetes, load balancing looks fine on the dashboard — but some pods are burning at 80% CPU while others sit idle, and adding more replicas only partially helps.

Rohit Agrawal, a Staff Software Engineer on the traffic platform team at Databricks, explains why this happens and how his team replaced Kubernetes's default networking with a proxy-less, client-side load-balancing system built on the xDS protocol.

In this episode:

Why KubeProxy's Layer 4 routing breaks down under high-throughput gRPC: it picks a backend once per TCP connection, not per request
How Databricks built an Endpoint Discovery Service (EDS) that watches Kubernetes directly and streams real-time pod metadata to every client
How zone-aware spillover cut cross-availability-zone costs without sacrificing availability
Why CPU-based routing failed (monitoring lag creates oscillation) and what signals to use instead

The system has been running in production for three years across hundreds of services, handling millions of requests.

Sponsor

This episode is sponsored by LearnKube — get started on your Kubernetes journey through comprehensive online, in-person or remote training.

More info

Find all the links and info for this episode here: https://ku.bz/y803JMhBk
Interested in sponsoring an episode? Learn more.

Intelligent Kubernetes Load Balancing, with Rohit Agrawal

KubeFM

Intelligent Kubernetes Load Balancing, with Rohit Agrawal