Max Hausner & Yves Fauser
gRPC Load Balancing Deep Dive
#1about 4 minutes
An overview of gRPC fundamentals and its trade-offs
gRPC is a high-performance framework using Protobuf for efficiency, but it has limitations in browser support and tooling maturity compared to REST.
#2about 4 minutes
How gRPC streaming and HTTP/2 affect load balancing
gRPC supports various streaming patterns over persistent HTTP/2 connections, which can cause traffic hotspots with traditional Layer 4 load balancing.
#3about 3 minutes
Client-side versus infrastructure-based load balancing strategies
Choose client-side load balancing for low-latency internal services and infrastructure-based load balancing for external APIs that require a clear demarcation point.
#4about 7 minutes
Exploring different types of load balancing algorithms
A review of basic, load-based, and hash-based algorithms reveals that options like "least outstanding requests" can outperform simple round robin for uneven loads.
#5about 2 minutes
Why autoscaling gRPC services can be challenging
Long-lived streaming connections can prevent traffic from being distributed to newly scaled instances, making traditional CPU-based autoscaling ineffective.
#6about 4 minutes
Tools for functional and performance testing of gRPC
Use tools like grpcurl for functional API testing with proto files and ghz for comprehensive performance and load testing of your gRPC services.
#7about 3 minutes
Case study: Separating unary and streaming calls
A practical example shows how separating unary and streaming gRPC calls into different Kubernetes services and target groups solves uneven load distribution.
#8about 1 minute
Key takeaways for effective gRPC load balancing
Successfully load balance gRPC by being mindful of long-lived sessions, understanding client traffic patterns, and selecting L7-based algorithms when possible.
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