af8075529f
Usage: vppapitrace.py [-h] [--debug] [--apidir APIDIR] {convert,replay} ...
optional arguments:
-h, --help show this help message and exit
--debug enable debug mode
--apidir APIDIR Location of JSON API definitions
subcommands:
valid subcommands
{convert,replay} additional help
convert Convert API trace to JSON or Python and back
replay Replay messages to running VPP instance
To convert an API trace file to JSON:
vppapitrace convert /tmp/api.trace trace.json
To convert an (edited) JSON file back to API trace for replay:
vppapitrace convert trace.json api-edited.trace
To generate a Python file that can be replayed:
vppapitrace convert /tmp/api.trace trace.py
vppapitrace convert trace.json trace.py
Replay it to a running VPP instance:
vppapitrace replay --socket /tmp/api.trace
In VPP that file can be replayed with:
vpp# api trace replay api-edited.trace
This patch also modifies the API binary trace format, to include the
message id to message name table.
Ticket: VPP-1733
Change-Id: Ie6441efb53c1c93c9f778f6ae9c1758bccc8dd87
Type: refactor
Signed-off-by: Ole Troan <ot@cisco.com>
(cherry picked from commit edfe2c0079a756f5fb1108037c39450e3521c8bd)
Signed-off-by: Andrew Yourtchenko <ayourtch@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 @ref release_notes.
Directory layout
| Directory name | Description |
|---|---|
| build-data | Build metadata |
| build-root | Build output directory |
| doxygen | Documentation generator configuration |
| dpdk | DPDK patches and build infrastructure |
| @ref extras/libmemif | Client library for memif |
| @ref src/examples | VPP example code |
| @ref src/plugins | VPP bundled plugins directory |
| @ref src/svm | Shared virtual memory allocation library |
| src/tests | Standalone tests (not part of test harness) |
| src/vat | VPP API test program |
| @ref src/vlib | VPP application library |
| @ref src/vlibapi | VPP API library |
| @ref src/vlibmemory | VPP Memory management |
| @ref src/vnet | VPP networking |
| @ref src/vpp | VPP application |
| @ref src/vpp-api | VPP application API bindings |
| @ref src/vppinfra | VPP core library |
| @ref 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.
Test Framework
There is PyDoc generated documentation available for the VPP test framework. See @ref test_framework_doc for details.