I've got two directories on the root of my repo: client and server; how can I run two different cycles (with pre_install, install, script &c), one on each of them?
You can traverse into the desired directories and run all subsequent commands in them:
before_install:
- pushd client
- ./pre-install-client
- popd
- pushd server
- ./pre-install-server
- popd
These you can reproduce in all relevant sections and run commands in both the client and server directories. I'd recommend extracting these things to shell scripts if possible to reduce the complexity of the .travis.yml file.
Related
Goal
I am using Docker to run JMeter in Azure Devops. I am trying to use Blazemeter's Parallel Controller, which is not native to JMeter. So, according to the justb4/jmeter image documentation, I used the following command to get the image going and run the JMeter test:
docker run --name jmetertest -i -v /home/vsts/work/1/s/plugins:/plugins -v $ROOTPATH:/test -w /test justb4/jmeter ${#:2}
Error
However, it produces the following error while trying to accommodate for the plugin (I know the plugin makes the difference due to testing without the plugin):
cp: can't create '/test/lib/ext': No such file or directory
As far as I understand, this is an error produced when one of the parent directories of the directory you are trying to make does not exist. Is there something I am doing wrong, or is there actually something wrong with the image?
References
For reference, I will include links to the image documentation and the repository.
Image: https://hub.docker.com/r/justb4/jmeter
Repository: https://github.com/justb4/docker-jmeter
Looking into the Dockerfile:
ENV JMETER_HOME /opt/apache-jmeter-${JMETER_VERSION}
Looking into entrypoint.sh
if [ -d /plugins ]
then
for plugin in /plugins/*.jar; do
cp $plugin $(pwd)/lib/ext
done;
fi
It basically copies the plugins from /plugins folder (if it is present) to /lib/ext folder relative to current working directory
I don't know why did you add this stanza -w /test to your command line but it explicitly "tells" the container that local working directory is /test, not /opt/apache-jmeter-xxxx, that's why the script is failing to copy the files.
In general I don't think that the approach is very valid because:
In Azure DevOps you won't have your "local" folder (unless you want to add plugins binaries under the version control system)
Some JMeter Plugins have other .jars as the dependencies so when you're installing the plugin you should:
put the plugin itself under /lib/ext folder of your JMeter installation
put the plugin dependencies under /lib folder of your JMeter installation
So I would recommend amending the Dockerfile, download JMeter Plugins Manager and installed the plugin(s) you need from the command line
Something like:
RUN wget https://jmeter-plugins.org/get/ -O /opt/apache-jmeter-${JMETER_VERSION}/lib/ext/jmeter-plugins-manager.jar
RUN wget https://repo1.maven.org/maven2/kg/apc/cmdrunner/2.2/cmdrunner-2.2.jar -P /opt/apache-jmeter-${JMETER_VERSION}/lib/
RUN java -cp /opt/apache-jmeter-${JMETER_VERSION}/lib/ext/jmeter-plugins-manager.jar org.jmeterplugins.repository.PluginManagerCMDInstaller
RUN /opt/apache-jmeter-${JMETER_VERSION}/bin/./PluginsManagerCMD.sh install bzm-parallel
I have a question regarding an implementation of a Dockerfile on dask-docker.
FROM continuumio/miniconda3:4.8.2
RUN conda install --yes \
-c conda-forge \
python==3.8 \
[...]
&& rm -rf /opt/conda/pkgs
COPY prepare.sh /usr/bin/prepare.sh
RUN mkdir /opt/app
ENTRYPOINT ["tini", "-g", "--", "/usr/bin/prepare.sh"]
prepare.sh is just facilitating installation of additional packages via conda, pip and apt.
There are two things I don't get about that:
Why not just place those instructions in the Dockerfile? Possibly indirectly (modularized) by COPYing dedicated files (requirements.txt, environment.yaml, ...)
Why execute this via tini? At the end it does exec "$#" where one can start a scheduler or worker - that's more what I associate with tini.
This way everytime you run the container from the built image you have to repeat the installation process!?
Maybe I'm overthinking it but it seems rather unusual - but maybe that's a Dockerfile pattern with good reasons for it.
optional bonus questions for Dask insiders:
why copy prepare.sh to /usr/bin (instead of f.x. to /tmp)?
What purpose serves the created directory /opt/app?
It really depends on the nature and usage of the files being installed by the entry point script. In general, I like to break this down into a few categories:
Local files that are subject to frequent changes on the host system, and will be rolled into the final image for production release. This is for things like the source code for an application that is under development and needs to be tested in the container. You want these to be copied into the runtime every time the image is rebuilt. Use a COPY in the Dockerfile.
Files from other places that change frequently and/or are specific to the deployment environment. This is stuff like secrets from a Hashicorp vault, network settings, server configurations, etc.... that will probably be downloaded into the container all the time, even when it goes into production. The entry point script should download these, and it should decide which files to get and from where based on environment variables that are injected by the host.
libraries, executable programs (under /bin, /usr/local/bin, etc...), and things that specifically should not change except during a planned upgrade. Usually anything that is installed using pip, maven or some other program that does dependency management, and anything installed with apt-get or equivalent. These files should not be installed from the Dockerfile or from the entrypoint script. Much, much better is to build your base image with all of the dependencies already installed, and then use that image as the FROM source for further development. This has a number of advantages: it ensures a stable, centrally located starting platform that everyone can use for development and testing (it forces uniformity where it counts); it prevents you from hammering on the servers that host those libraries (constantly re-downloading all of those libraries from pypy.org is really bad form... someone has to pay for that bandwidth); it makes the build faster; and if you have a separate security team, this might help reduce the number of files they need to scan.
You are probably looking at #3, but I'm including all three since I think it's a helpful way to categorize things.
I am trying to follow the 2 steps mentioned below:
1) Downloaded source code of
https://sourceforge.net/projects/hunspell/files/Hyphen/2.8/hyphen-2.8.8.tar.gz/download
2) Compiled it and you will get binary named example:
hyphen-2.8.8$ ./example ~/dev/smc/hyphenation/hi_IN/hyph_hi_IN.dic
~/hi_sample.text
I have downloaded and uncompressed the tar file. My question is how to create a dockerfile to automate this?
There are only 3 commands involved:
./configure
make all-recursive
make install
I can select the official python image as a base container. But how do I write the commands in a docker file?
You can do that with a RUN command:
FROM python:<version number here>
RUN ./configure && make-recursive && make install
CMD ['<some command here>']
what you use for <some command here> depends on what the image is meant to do. Remember that docker containers only run as long as that command is executing, so if you put the configure/make/install steps in a script and use that as your entry point, it's going to build your program, and then the container will halt.
Also you need to get the downloaded files into the container. That can be done using a COPY or an ADD directive (before the RUN of course). If you have the tar.gz file saved locally, then ADD will both copy the file into the container and expand it into a directory automatically. COPY will not expand it, so if you do that, you'll need to add a tar -zxvf or similar to the RUN.
If you want to download the file directly into the container, that could be done with ADD <source URL>, but in that case it won't expand it, so you'll have to do that in the RUN. COPY doesn't allow sourcing from a URL. This post explains COPY vs ADD in more detail.
You can have the three commands in a shell script and then use the following docker commands
COPY ./<path to your script>/<script-name>.sh /
ENTRYPOINT ["/<script-name>.sh"]
CMD ["run"]
For reference, you can create your docker file as they have created for one of the projects I worked on Apache Artemis Active Mq:
https://github.com/apache/activemq-artemis/blob/master/artemis-docker/Dockerfile-ubuntu
I am using GitLab Community Edition and GitLab runner CI setup to deploy (synchronize) a bunch of JSON files on a server using LFTP. This job however, seems to "freeze" for a few minutes every 10 files roughly. Having to synchronize roughly 400 files sometimes, this job simply crashes because it sometimes takes more than an hour to complete. The JSON files are all 1KB. Neither the source and target servers should have any firewalls rate limiting the FTP. Both are hosted at OVH.
The following LFTP command is executed in orer to synchronize everything:
lftp -v -c "set sftp:auto-confirm true; open sftp://$DEVELOPMENT_DEPLOY_USER:$DEVELOPMENT_DEPLOY_PASSWORD#$DEVELOPMENT_DEPLOY_HOST:$DEVELOPMENT_DEPLOY_PORT; mirror -Rev ./configuration_files configuration/configuration_files --exclude .* --exclude .*/ --include ./*.json"
Job is ran in Docker, using this container to deploy everything. What could cause this?
For those of you coming from google we had the exact same setup. The way to get LFTP to stop hanging when running in a docker or some other CI you can use this command:
lftp -c "set net:timeout 5; set net:max-retries 2; set net:reconnect-interval-base 5; set ftp:ssl-force yes; set ftp:ssl-protect-data true; open -u $USERNAME,$PASSWORD $HOST; mirror dist / -Renv --parallel=10"
This does several things:
It makes it so it won't wait forever or get into a continuous loop
when it can't do a command. This should speed things along.
Makes sure we are using SSL/TLS. If you don't need this remove those
options.
Synchronizes one folder to the new location. The options -Renv can
be explained here: https://lftp.yar.ru/lftp-man.html
Lastly in the gitlab CI I set the job to retry if it fails. This will spin up a new docker instance that gets around any open file or connection limitations. The above LFTP command will run again but since we are using the -n flag it will only move over the files that were missed on the first job if it doesn't succeed. This gets everything moved over without hassle. You can read more about CI job retrys here: https://docs.gitlab.com/ee/ci/yaml/#retry
Have you looked at using rsync instead? I'm fairly sure you can benefit from the incremental copying of files as opposed to copying the entire set over each time.
I'm not sure if I should create different Dockerfile files for my Node.js app. One for production without the development dependencies and one for testing with the development dependencies included.
Or one file which is basically the development Dockerfile.dev. Then main difference of both files is the npm install command:
Production:
FROM ...
...
RUN npm install --quiet --production
...
CMD ...
Development/Test:
FROM ...
...
RUN npm install
...
CMD ...
The question arises because I want to be able to run my tests inside the container via docker run command. Therefore I need the test dependencies (typically dev dependencies for me).
Seems a little bit odd to put dependencies not needed in production into the image. On the other hand creating/maintaining a second Dockerfile.dev which just minor differences seems also not right. So what is the a good practise for this kind of problem.
No, you don't need to have different Dockerfiles and in fact you should avoid that.
The goal of docker is to ship your app in an immutable, well tested artifact (docker images) which is identical for production and test and even dev.
Why? Because if you build different artifacts for test and production how can you guarantee what you have already tested is working in production too? you can't because they are two different things.
Given all that, if by test you mean unit tests, then you can mount your source code inside docker container and run tests without building any docker images. And that's fine. Remember you can build image for tests but that terribly slow and makes development quiet difficult and slow which is not good at all. Then if your test passed you can build you app container safely.
But if you mean acceptance test that actually needs to run against your running application then you should create one image for your app (only one) and run tests in another container (mount test source code for example) and run tests against that container. This obviously means what your build for your app is different for npm installs for your tests.
I hope this gives you some over view.
Well then you'll have to support several Dockerfiles that are almost identical. Instead I recommend to use NodeJS feature like production profile. And another one recommendation regarding to
RUN npm install --quiet --production
It is better to create separate .sh file and do something like this instead:
ADD ./scripts/run.sh /run.sh
RUN chmod +x /*.sh
And also think about to start using Gulp.
UPD #1
By default npm install installs devDependencies. In order to get around this - use npm install --production OR set the NODE_ENV environment variable to production value.
Putting script line in separate file is a good practice in order not to change Dockerfile often. If you'll need changes next time then you'll have to update only script-file and you're done. In future you could also have some additional work to do.