rpc-perf
rpc-perf is a tool for measuring the performance of RPC services and is primarily used to benchmark caching systems.
Content
- Getting rpc-perf
- Configuration
- Sample Usage
- Sample Output
- Practices
- Features
- Future Work
- Contributing
Getting rpc-perf
rpc-perf is built through the cargo
command which ships with rust. If you
don't have Rust installed, you can use rustup to manage your Rust
installation. Otherwise, follow the instructions on
rust-lang.org to get Rust and Cargo installed. rpc-perf
is developed and tested against the stable Rust toolchain.
Build from source
With Rust installed, clone this repo, and cd into this folder:
git clone https://github.com/twitter/rpc-perf.git
cd rpc-perf
cargo build --release
This will produce a binary at target/release/rpc-perf
which can be run
in-place or copied to a more convenient location on your system.
Configuration
rpc-perf takes a configuration file to define the test parameters and runtime options.
Sample Usage
BEWARE rpc-perf can write to its target and can generate many requests
- run only if data in the server can be lost/destroyed/corrupted/etc
- run only if you understand the impact of sending high-levels of traffic across your network
# run rpc-perf using the specified configuration file
rpc-perf configs/memcache.toml
Practices
- Start with a short test before moving on to tests spanning larger periods of time
- If comparing latency between two setups, be sure to set a ratelimit that's achievable on both
- Keep
--clients
below the number of cores on the machine generating workload - Increase
--poolsize
as necessary to simulate production-like connection numbers - You may need to use multiple machines to generate enough workload and/or connections to the target
- Log your configuration and results to make repeating and sharing experiments easy
- Use waterfalls to help visualize latency distribution over time and see anomalies
Features
- high-resolution latency metrics
- supports memcache and redis protocols
- mio for async networking
- optional waterfall visualization of latencies
- powerful workload configuration
Support
Create a new issue on GitHub.
Contributing
We feel that a welcoming community is important and we ask that you follow Twitter's Open Source Code of Conduct in all interactions with the community.
Authors
- Brian Martin [email protected]
A full list of contributors can be found on GitHub.
Follow @TwitterOSS on Twitter for updates.
License
Copyright 2015-2019 Twitter, Inc.
Licensed under the Apache License, Version 2.0: https://www.apache.org/licenses/LICENSE-2.0
Security Issues?
Please report sensitive security issues via Twitter's bug-bounty program (https://hackerone.com/twitter) rather than GitHub.