SeaStar is an event-driven framework allowing you to write non-blocking, asynchronous code in a relatively straightforward manner (once understood). It is based on futures.

For more details and alternative work-flows, read HACKING.md.

Assuming that you would like to use system packages (RPMs or DEBs) for Seastar's dependencies, first install them:

$ sudo ./install-dependencies.sh

then configure (in "release" mode):

$ ./configure.py --mode=release

then compile:

$ ninja -C build/release

In case there are compilation issues, especially like g++: internal compiler error: Killed (program cc1plus) try giving more memory to gcc, either by limiting the amount of threads ( -j1 ) and/or allowing at least 4g ram to your machine.

If you're missing a dependency of Seastar, then it is possible to have the configuration process fetch a version of the dependency locally for development.

For example, to fetch fmt locally, configure Seastar like this:

$ ./configure.py --mode=dev --cook fmt

--cook can be repeated many times for selecting multiple dependencies.

The configure.py script is a wrapper around cmake. The --mode argument maps to CMAKE_BUILD_TYPE, and supports the following modes

Note that seastar is more sensitive to allocators and optimizations than usual. A quick rule of the thumb of the relative performances is that release is 2 times faster than dev, 150 times faster than sanitize and 300 times faster than debug.

It's possible to consume Seastar directly from its build directory with CMake or pkg-config.

We'll assume that the Seastar repository is located in a directory at $seastar_dir.

Via pkg-config:

$ g++ my_app.cc $(pkg-config --libs --cflags --static $seastar_dir/build/release/seastar.pc) -o my_app

and with CMake using the Seastar package:

CMakeLists.txt for my_app:

find_package (Seastar REQUIRED)

add_executable (my_app
  my_app.cc)
  
target_link_libraries (my_app
  Seastar::seastar)

$ mkdir $my_app_dir/build
$ cd $my_app_dir/build
$ cmake -DCMAKE_PREFIX_PATH="$seastar_dir/build/release;$seastar_dir/build/release/_cooking/installed" -DCMAKE_MODULE_PATH=$seastar_dir/cmake $my_app_dir

The CMAKE_PREFIX_PATH values ensure that CMake can locate Seastar and its compiled submodules. The CMAKE_MODULE_PATH value ensures that CMake can uses Seastar's CMake scripts for locating its dependencies.

You can also consume Seastar after it has been installed to the file-system.

Important:

• Seastar works with a customized version of DPDK, so by default builds and installs the DPDK submodule to $build_dir/_cooking/installed

First, configure the installation path:

$ ./configure.py --mode=release --prefix=/usr/local

then run the install target:

$ ninja -C build/release install

then consume it from pkg-config:

$ g++ my_app.cc $(pkg-config --libs --cflags --static seastar) -o my_app

or consume it with the same CMakeLists.txt as before but with a simpler CMake invocation:

$ cmake ..

(If Seastar has not been installed to a "standard" location like /usr or /usr/local, then you can invoke CMake with -DCMAKE_PREFIX_PATH=$my_install_root.)

There are also instructions for building on any host that supports Docker.

Use of the DPDK is optional.

Seastar supports both C++17, and C++20. The build defaults to the latest standard supported by your compiler, but can be explicitly selected with the --c++-standard configure option, e.g., --c++-standard=17, or if using CMake directly, by setting on the CMAKE_CXX_STANDARD CMake variable.

See the compatibity statement for more information.

There is a mini tutorial and a more comprehensive one.

The documentation is available on the web.

Ask questions and post patches on the development mailing list. Subscription information and archives are available here, or just send an email to [email protected].

Information can be found on the main project website.

File bug reports on the project issue tracker.

Seastar comes with its own userspace TCP/IP stack for better performance.

• CPUs - As much as you need. SeaStar is highly friendly for multi-core and NUMA
• NICs - As fast as possible, we recommend 10G or 40G cards. It's possible to use 1G too but you may be limited by their capacity. In addition, the more hardware queue per cpu the better for SeaStar. Otherwise we have to emulate that in software.
• Disks - Fast SSDs with high number of IOPS.
• Client machines - Usually a single client machine can't load our servers. Both memaslap (memcached) and WRK (httpd) cannot over load their matching server counter parts. We recommend running the client on different machine than the servers and use several of them.

• cpv-cql-driver: C++ driver for Cassandra/Scylla based on seastar framework
• cpv-framework: A web framework written in c++ based on seastar framework
• redpanda: A Kafka replacement for mission critical systems
• Scylla: A fast and reliable NoSQL data store compatible with Cassandra and DynamoDB
• smf: The fastest RPC in the West