8800f732f8
- Make framework.py classes a subset of asfframework.py classes - Remove all packet related code from asfframework.py - Add test class and test case set up debug output to log - Repatriate packet tests from asf to test directory - Remove non-packet related code from framework.py and inherit them from asfframework.py classes - Clean up unused import variables - Re-enable BFD tests on Ubuntu 22.04 and fix intermittent test failures in echo_looped_back testcases (where # control packets verified but not guaranteed to be received during test) - Re-enable Wireguard tests on Ubuntu 22.04 and fix intermittent test failures in handshake ratelimiting testcases and event testcase - Run Wiregard testcase suites solo - Improve debug output in log.txt - Increase VCL/LDP post sleep timeout to allow iperf server to finish cleanly. - Fix pcap history files to be sorted by suite and testcase and ensure order/timestamp is correct based on creation in the testcase. - Decode pcap files for each suite and testcase for all errors or if configured via comandline option / env var - Improve vpp corefile detection to allow complete corefile generation - Disable vm vpp interfaces testcases on debian11 - Clean up failed unittest dir when retrying failed testcases and unify testname directory and failed linknames into framwork functions Type: test Change-Id: I0764f79ea5bb639d278bf635ed2408d4d5220e1e Signed-off-by: Dave Wallace <dwallacelf@gmail.com>
Vector Packet Processing
Introduction
The VPP platform is an extensible framework that provides out-of-the-box production quality switch/router functionality. It is the open source version of Cisco's Vector Packet Processing (VPP) technology: a high performance, packet-processing stack that can run on commodity CPUs.
The benefits of this implementation of VPP are its high performance, proven technology, its modularity and flexibility, and rich feature set.
For more information on VPP and its features please visit the FD.io website and What is VPP? pages.
Changes
Details of the changes leading up to this version of VPP can be found under doc/releasenotes.
Directory layout
| Directory name | Description |
|---|---|
| build-data | Build metadata |
| build-root | Build output directory |
| docs | Sphinx Documentation |
| dpdk | DPDK patches and build infrastructure |
| extras/libmemif | Client library for memif |
| src/examples | VPP example code |
| src/plugins | VPP bundled plugins directory |
| src/svm | Shared virtual memory allocation library |
| src/tests | Standalone tests (not part of test harness) |
| src/vat | VPP API test program |
| src/vlib | VPP application library |
| src/vlibapi | VPP API library |
| src/vlibmemory | VPP Memory management |
| src/vnet | VPP networking |
| src/vpp | VPP application |
| src/vpp-api | VPP application API bindings |
| src/vppinfra | VPP core library |
| src/vpp/api | Not-yet-relocated API bindings |
| test | Unit tests and Python test harness |
Getting started
In general anyone interested in building, developing or running VPP should consult the VPP wiki for more complete documentation.
In particular, readers are recommended to take a look at [Pulling, Building, Running, Hacking, Pushing](https://wiki.fd.io/view/VPP/Pulling,_Building,_Run ning,_Hacking_and_Pushing_VPP_Code) which provides extensive step-by-step coverage of the topic.
For the impatient, some salient information is distilled below.
Quick-start: On an existing Linux host
To install system dependencies, build VPP and then install it, simply run the
build script. This should be performed a non-privileged user with sudo
access from the project base directory:
./extras/vagrant/build.sh
If you want a more fine-grained approach because you intend to do some
development work, the Makefile in the root directory of the source tree
provides several convenience shortcuts as make targets that may be of
interest. To see the available targets run:
make
Quick-start: Vagrant
The directory extras/vagrant contains a VagrantFile and supporting
scripts to bootstrap a working VPP inside a Vagrant-managed Virtual Machine.
This VM can then be used to test concepts with VPP or as a development
platform to extend VPP. Some obvious caveats apply when using a VM for VPP
since its performance will never match that of bare metal; if your work is
timing or performance sensitive, consider using bare metal in addition or
instead of the VM.
For this to work you will need a working installation of Vagrant. Instructions for this can be found [on the Setting up Vagrant wiki page] (https://wiki.fd.io/view/DEV/Setting_Up_Vagrant).
More information
Several modules provide documentation, see @subpage user_doc for more end-user-oriented information. Also see @subpage dev_doc for developer notes.
Visit the VPP wiki for details on more advanced building strategies and other development notes.