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title: gRPC-Go performance Improvements | daily.dev
description: gRPC-Go maintainers detail flow control and performance work including expanding stream windows for large messages, decoupling connection-level flow control...
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# gRPC-Go performance Improvements

**[gRPC Blog](https://daily.dev/sources/grpc-blog)** · 9 min read · 0 upvotes · 0 comments

## Summary

gRPC-Go maintainers detail flow control and performance work including expanding stream windows for large messages, decoupling connection-level flow control from application reads, piggybacking window updates onto existing flushes, and BDP (Bandwidth Delay Product) estimation for dynamic window sizing. These changes yielded up to a 10x improvement for large messages on high-latency networks and closed the gap with HTTP/1.1 performance. Planned future work covers reducing flush syscalls and reducing memory allocations via buffer pooling. Benchmark tables compare gRPC against HTTP/1.1 and HTTP/2.0 across real and simulated networks with varying RTT and payload sizes.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://grpc.io/blog/grpc-go-perf-improvements>

## Questions this post answers

### What is BDP (Bandwidth Delay Product) estimation in gRPC-Go and how does it improve performance?

BDP estimation is a gRPC-Go feature that dynamically adjusts flow control window sizes based on measured network bandwidth and round-trip time. A receiver sends a BDP ping on receiving a data frame, counts bytes received over roughly 1.5 RTTs, and doubles the window size if the sampled bandwidth exceeds the previous maximum, up to a 4MB cap matching typical TCP flow control limits. It is enabled by default and closed the performance gap with HTTP/1.1 on high-latency networks.

_daily.dev surfaces deep dives like this for teams tuning gRPC performance on high-latency links._

### How much faster is gRPC-Go after expanding the stream window for large messages?

Expanding the stream window when an application is actively reading a large message gave a 10x performance improvement on high-latency networks. Instead of receiving large payloads in chunks and issuing window updates as the window runs low, gRPC-Go proactively requests the whole message once it knows the application is committed to reading and has allocated memory for it, a technique originally used in gRPC-C.

_Engineers optimizing RPC throughput can find this kind of benchmark data on daily.dev._

### Why does gRPC-Go decouple connection-level flow control from application reads?

Connection-level flow control in gRPC-Go was decoupled from application reads because a single slow or inactive stream sharing a connection could stall window updates for all other streams on that connection, hampering overall performance. Stream-level flow control still depends on application reads, but the connection-level window is instead capped near the network's Bandwidth Delay Product to bound throughput without letting one slow stream block others.

_daily.dev helps developers track this kind of gRPC internals discussion when debugging multiplexed RPC performance._

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---

Tags: [#performance](https://daily.dev/tags/performance), [#golang](https://daily.dev/tags/golang), [#grpc](https://daily.dev/tags/grpc)

[View this post on daily.dev](https://daily.dev/posts/grpc-go-performance-improvements-bsbvkhfga)

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