This is the Developer's Guide for Fabric CA, which is a Certificate Authority for Hyperledger Fabric.
See User's Guide for Fabric CA for information on how to use Fabric CA.
- Go 1.10+ installation or later
- GOPATH environment variable is set correctly
- docker version 17.03 or later
- docker-compose version 1.11 or later
- A Linux Foundation ID (see create a Linux Foundation ID)
You are welcome to contribute to Fabric CA!
The following are guidelines to follow when contributing:
-
See the general information about contributing to fabric.
-
To set up your development environment for doing common development tasks, see bash_profile. This contains variables and functions which can be copied directly into your
.bash_profile
file. Even if you do not use bash, you should still find the functions instructive. For example: a. clone - pulls the latest fabric-ca code from gerrit and places it based on your GOPATH setting b. cdr - cd to the fabric-ca repository root, which is equivalent to "cd $GOPATH/src/github.com/hyperledger/fabric-ca" c. gencov - generates a test coverage report -
To run the unit tests manually:
# cdr # make unit-tests
The test coverage for each package must be 75% or greater. If this fails due to insufficient test coverage, then you can run
gencov
to get a coverage report to see what code is not being tested. Once you have added additional test cases, you can rungo test -cover
in the appropriate package to see the current coverage level.WARNING: Running the unit-tests may fail due to too many open file descriptors. Depending on where the failure occurs, the error message may not be obvious and may only say something similar to "unable to open database file". Depending on the settings on your host, you may need to increase the maximum number of open file descriptors. For example, the OSX default per-process maximum number of open file descriptors is 256. You may issue the following command to display your current setting:
# ulimit -n 256
And the following command will increase this setting to 65536:
# ulimit -n 65536
Please note that this change is only temporary. To make it permanent, you will need to consult the documentation for your host operating system.
- cmd/fabric-ca-server contains the main for the fabric-ca-server command.
- cmd/fabric-ca-client contains the main for the fabric-ca-client command.
- lib contains most of the code. a) server.go contains the main Server object, which is configured by serverconfig.go. b) client.go contains the main Client object, which is configured by clientconfig.go.
- util/csp.go contains the Crypto Service Provider implementation.
- lib/dbutil contains database utility functions.
- lib/ldap contains LDAP client code.
- lib/spi contains Service Provider Interface code for the user registry.
- lib/tls contains TLS related code for server and client.
- util contains various utility functions.
Fabric CA server can be profiled two ways, namely, using benchmarks and by retrieving profiling data from the server (at /debug/pprof/ endpoint) while running load.
You can profile the benchmarks by running make bench-cpu
or make bench-mem
commands. You can profile benchmarks in one package or all the packages using these make targets. For example, to profile benchmarks in the lib package, run: make bench-cpu pkg=github.com/hyperledger/fabric-ca/lib
. This will create bench-cpu.prof, lib.test and bench files in the lib folder. The bench file will contain benchmark stats: bytes/operation, allocations/operation and nanoseconds/operation. lib.test file is the executable and bench-cpu.prof contains cpu profile information. To analyze the profile, run: go tool pprof lib.test bench-cpu.prof
. Similarly, you can run make bench-mem pkg=github.com/hyperledger/fabric-ca/lib
to perform memory profiling of the benchmarks in the lib package. The bench-mem.prof file contains memory profile information.
If you run make bench-cpu
or make bench-mem
without pkg variable, benchmarks in each package are run with cpu or memory profiling. So, executable, benchmark output, and profile info files are created in each package folder. You need to analyze these profiles separately.
To enable profiling on the server, set the FABRIC_CA_SERVER_PROFILE_PORT environment
variable to a valid, available port number and start the server. The server will start listening for profile requests at the /debug/pprof/ HTTP endpoint and the specified port. Then run go tool pprof
with server's profiling URL (http://:/debug/pprof/<profile|heap|block>) as an argument, it will download and examine a live profile.
You can start the server in the FVT image by running following docker command from the fabric-ca root directory:
docker run -p 8888:8888 -p 8054:8054 -v $PWD:/opt/gopath/src/github.com/hyperledger/fabric-ca -e FABRIC_CA_SERVER_PROFILE_PORT=8054 --name loadTest -td hyperledger/fabric-ca-fvt test/fabric-ca-load-tester/launchServer.sh 1
Then start the load by running /test/fabric-ca-load-tester/runLoad.sh -B
In other window, you can start profiling by running (assuming load test takes about a minute to complete):
curl http://localhost:8054/debug/pprof/profile?seconds=60 > load-cpu.prof
then analyze the profile:
go tool pprof bin/fabric-ca-server load-cpu.prof
OR simply run:
go tool pprof -seconds=60 -output=load-cpu.prof http://localhost:8054/debug/pprof/profile
You can use commands like top, top -cum, list and web to look at the top consumers, list the code to see the hotspots and to view the graph in a browser. You can run go tool pprof -h
to view all the options supported by the pprof tool
You can also use go-torch tool to analyze the profile:
go-torch bin/fabric-ca-server load-cpu.prof
To enable profiling on the client, set the FABRIC_CA_CLIENT_PROFILE_MODE environment variable to either "heap" or "cpu" to enable heap, cpu profiling respectively. A file containing profiling data is created in the present working directory of the client. Heap profiling data is written to mem.pprof and cpu profiling data is written to cpu.pprof. You can run go tool pprof <client executable> <profiling file>
to analyze the profiling data.
https://blog.golang.org/profiling-go-programs https://medium.com/@hackintoshrao/daily-code-optimization-using-benchmarks-and-profiling-in-golang-gophercon-india-2016-talk-874c8b4dc3c5 https://www.youtube.com/watch?v=2h_NFBFrciI https://software.intel.com/en-us/blogs/2014/05/10/debugging-performance-issues-in-go-programs http://www.soroushjp.com/2015/01/27/beautifully-simple-benchmarking-with-go/ https://vinceyuan.github.io/profiling-memory-usage-of-a-go-app/ https://www.youtube.com/watch?v=N3PWzBeLX2M&feature=youtu.be https://www.youtube.com/watch?v=oorX84tBMqo&feature=youtu.be
See FVT tests for information on functional verification test cases.
Following are the steps to update cfssl package using version 1.0.8 of govendor tool.
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Remove cfssl from vendor folder
- cd $GOPATH/src/github.com/hyperledger/fabric-ca/vendor
- govendor remove github.com/cloudflare/cfssl/...
- rm -rf github.com/cloudflare/cfssl/
-
Clone cfssl repo
- cd $GOPATH/src/github.com/
- mkdir cloudflare
- cd cloudflare
- git clone https://github.com/cloudflare/cfssl.git
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Add cfssl from $GOPATH to the vendor folder
- cd $GOPATH/src/github.com/hyperledger/fabric-ca/vendor
- govendor add github.com/cloudflare/cfssl/^
- You can optionally specify revision or tag to add a particular revision of code to the vendor folder
- govendor add github.com/cloudflare/cfssl/^@abc12032
-
Remove sqlx package from cfssl vendor folder. This is because certsql.NewAccessor (called by fabric-ca) requires sqlx.db object to be passed from the same package. If we were to have sqlx package both in fabric-ca and cfssl vendor folder, go compiler will throw an error
- rm -rf github.com/cloudflare/cfssl/vendor/github.com/jmoiron/sqlx
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Remove the packages that are added to the fabric-ca vendor folder that are not needed by fabric-ca
Hyperledger Project source code files are made available under the Apache License, Version 2.0 (Apache-2.0), located in the LICENSE file. Hyperledger Project documentation files are made available under the Creative Commons Attribution 4.0 International License (CC-BY-4.0), available at http://creativecommons.org/licenses/by/4.0/.