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Tips and Tricks for containerizing services
This document contains a list of tips and tricks that are useful when containerizing an OpenStack service.
Important Notes
Podman
Prior to Stein, containerized OpenStack deployments used Docker.
Starting with the Stein release, Docker is no longer part of OpenStack, and Podman has taken its place. The notes here are regarding Stein and later, with Rocky and earlier docker commands clearly marked.
sudo
On CentOS 7, podman cannot function with administrative privileges due to user namespaces not being enabled in an older kernel. The workaround is simply to run podman commands with sudo as a prefix.
If you see the following, simply remember to add sudo to your command:
$ podman ps
cannot clone: Invalid argument
user namespaces are not enabled in /proc/sys/user/max_user_namespaces
ERRO[0000] cannot re-exec process
Monitoring containers
It's often useful to monitor the running containers and see what has been executed and what not. The puppet containers are created and removed automatically unless they fail. For all the other containers, it's enough to monitor the output of the command below:
$ watch -n 0.5 sudo podman ps -a --filter label=managed_by=tripleo_ansible
Stein and Train
$ watch -n 0.5 sudo podman ps -a --filter label=managed_by=paunch
Rocky
$ watch -n 0.5 docker ps -a --filter label=managed_by=docker-cmd
Viewing container logs
You can view the output of the main process running in a container by running:
$ sudo podman logs $CONTAINER_ID_OR_NAME
Rocky
$ docker logs $CONTAINER_ID_OR_NAME
From Stein release, standard out and standard error from containers are captured in /var/log/containers/stdouts.
We export traditional logs from containers into the /var/log/containers directory on the host, where you can look at them.
systemd and podman
Throughout this document you'll find references to direct podman commands for things like restarting services. These are valid and supported methods, but it's worth noting that services are tied into the systemd management system, which is often the preferred way to operate.
Restarting nova_scheduler for example:
$ sudo systemctl restart tripleo_nova_scheduler
Stopping a container with systemd:
$ sudo systemctl stop tripleo_nova_scheduler
Toggle debug
For services that support reloading their configuration at runtime:
$ sudo podman exec -u root nova_scheduler crudini --set /etc/nova/nova.conf DEFAULT debug true
$ sudo podman kill -s SIGHUP nova_scheduler
Rocky
$ sudo docker exec -u root nova_scheduler crudini --set /etc/nova/nova.conf DEFAULT debug true
$ sudo docker kill -s SIGHUP nova_scheduler
Restart the container to turn back the configuration to normal:
$ sudo podman restart nova_scheduler
Rocky
$ sudo docker restart nova_scheduler
Otherwise, if the service does not yet support reloading its configuration, it is necessary to change the configuration on the host filesystem and restart the container:
$ sudo crudini --set /var/lib/config-data/puppet-generated/nova/etc/nova/nova.conf DEFAULT debug true
$ sudo podman restart nova_scheduler
Rocky
$ sudo crudini --set /var/lib/config-data/puppet-generated/nova/etc/nova/nova.conf DEFAULT debug true
$ sudo docker restart nova_scheduler
Apply the inverse change to restore the default log verbosity:
$ sudo crudini --set /var/lib/config-data/puppet-generated/nova/etc/nova/nova.conf DEFAULT debug false
$ sudo podman restart nova_scheduler
Rocky
$ sudo crudini --set /var/lib/config-data/puppet-generated/nova/etc/nova/nova.conf DEFAULT debug false
$ sudo docker restart nova_scheduler
Debugging container failures
The following commands are useful for debugging containers.
inspect: This command allows for inspecting the container's structure and metadata. It provides info about the bind mounts on the container, the container's labels, the container's command, etc:
$ sudo podman inspect $CONTAINER_ID_OR_NAME
Rocky
$ docker inspect $CONTAINER_ID_OR_NAME
top: Viewing processes running within a container is trivial with Podman:
$ sudo podman top $CONTAINER_ID_OR_NAME
exec: Running commands on or attaching to a running container is extremely useful to get a better understanding of what's happening in the container. It's possible to do so by running the following command:
$ sudo podman exec -ti $CONTAINER_ID_OR_NAME /bin/bash
Rocky
$ docker exec -ti $CONTAINER_ID_OR_NAME /bin/bash
Replace the /bin/bash above with other commands to run oneshot commands. For example:
$ sudo podman exec -ti mysql mysql -u root -p $PASSWORD
Rocky
$ docker exec -ti mysql mysql -u root -p $PASSWORD
The above will start a mysql shell on the mysql container.
export When the container fails, it's basically impossible to know what happened. It's possible to get the logs from docker but those will contain things that were printed on the stdout by the entrypoint. Exporting the filesystem structure from the container will allow for checking other logs files that may not be in the mounted volumes:
$ sudo podman export $CONTAINER_ID_OR_NAME -o $CONTAINER_ID_OR_NAME.tar
Rocky
There's no shortcut for *rebuilding* the command that was used to run the container but, it's possible to do so by using the `docker inspect` command and the format parameter $ docker inspect --format='{{range .Config.Env}} -e "{{.}}" {{end}} {{range .Mounts}} -v {{.Source}}:{{.Destination}}{{if .Mode}}:{{.Mode}}{{end}}{{end}} -ti {{.Config.Image}}' $CONTAINER_ID_OR_NAME Copy the output from the command above and append it to the one below, which will run the same container with a random name and remove it as soon as the execution exits:: $ docker run --rm $OUTPUT_FROM_PREVIOUS_COMMAND /bin/bash
Debugging with tripleo_container_manage Ansible role
The debugging manual for tripleo_container_manage is documented in the role directly.
Debugging with Paunch
Note
During Ussuri cycle, Paunch has been replaced by the tripleo_container_manage Ansible role. Therefore, the following block is deprecated in favor of the new role which contains a Debug manual.
The paunch debug
command allows you to perform specific
actions on a given container. This can be used to:
- Run a container with a specific configuration.
- Dump the configuration of a given container in either json or yaml.
- Output the docker command line used to start the container.
- Run a container with any configuration additions you wish such that you can run it with a shell as any user etc.
The configuration options you will likely be interested in include:
--file <file> YAML or JSON file containing configuration data
--action <name> Action can be one of: "dump-json", "dump-yaml",
"print-cmd", or "run"
--container <name> Name of the container you wish to manipulate
--interactive Run container in interactive mode - modifies config
and execution of container
--shell Similar to interactive but drops you into a shell
--user <name> Start container as the specified user
--overrides <name> JSON configuration information used to override
default config values
--default-runtime Default runtime for containers. Can be docker or
podman.
file
is the name of the configuration file to use
containing the configuration for the container you wish to use. TripleO
creates configuration files for starting containers in
/var/lib/tripleo-config/
. If you look in this directory you
will see a number of files corresponding with the steps in TripleO heat
templates. Most of the time, you will likely want to use
/var/lib/tripleo-config/hashed-container-startup-config-step_4.json
as it contains most of the final startup configurations for the running
containers.
shell
, user
and interactive
are available as shortcuts that modify the configuration to easily allow
you to run an interactive session in a given container.
To make sure you get the right container you can use the
paunch list
command to see what containers are running and
which config id they are using. This config id corresponds to which file
you will find the container configuration in.
Note that if you wish to replace a currently running container you
will want to sudo podman rm -f
the running container before
starting a new one.
Here is an example of using paunch debug
to start a root
shell inside the heat api container:
# paunch debug --file /var/lib/tripleo-config/hashed-container-startup-config-step_4.json --interactive --shell --user root --container heat_api --action run
This will drop you into an interactive session inside the heat api container, starting /bin/bash running as root.
To see how this container is started by TripleO:
# paunch debug --file /var/lib/tripleo-config/hashed-container-startup-config-step_4.json --container heat_api --action print-cmd
docker run --name heat_api-t7a00bfz --detach=true --env=KOLLA_CONFIG_STRATEGY=COPY_ALWAYS --env=TRIPLEO_CONFIG_HASH=b3154865d1f722ace643ffbab206bf91 --net=host --privileged=false --restart=always --user=root --volume=/etc/hosts:/etc/hosts:ro --volume=/etc/localtime:/etc/localtime:ro --volume=/etc/puppet:/etc/puppet:ro --volume=/etc/pki/ca-trust/extracted:/etc/pki/ca-trust/extracted:ro --volume=/etc/pki/tls/certs/ca-bundle.crt:/etc/pki/tls/certs/ca-bundle.crt:ro --volume=/etc/pki/tls/certs/ca-bundle.trust.crt:/etc/pki/tls/certs/ca-bundle.trust.crt:ro --volume=/etc/pki/tls/cert.pem:/etc/pki/tls/cert.pem:ro --volume=/dev/log:/dev/log --volume=/etc/ssh/ssh_known_hosts:/etc/ssh/ssh_known_hosts:ro --volume=/var/lib/kolla/config_files/heat_api.json:/var/lib/kolla/config_files/config.json:ro --volume=/var/lib/config-data/heat_api/etc/heat/:/etc/heat/:ro --volume=/var/lib/config-data/heat_api/etc/httpd/conf/:/etc/httpd/conf/:ro --volume=/var/lib/config-data/heat_api/etc/httpd/conf.d/:/etc/httpd/conf.d/:ro --volume=/var/lib/config-data/heat_api/etc/httpd/conf.modules.d/:/etc/httpd/conf.modules.d/:ro --volume=/var/lib/config-data/heat_api/var/www/:/var/www/:ro --volume=/var/log/containers/heat:/var/log/heat 192.168.24.1:8787/tripleomaster/centos-binary-heat-api:latest
You can also dump the configuration of a container to a file so you can edit it and rerun it with different a different configuration:
# paunch debug --file /var/lib/tripleo-config/hashed-container-startup-config-step_4.json --container heat_api --action dump-json > heat_api.json
You can then use heat_api.json
as your
--file
argument after editing it to your liking.
To add configuration elements on the command line you can use the
overrides
option. In this example I'm adding a health check
to the container:
# paunch debug --file /var/lib/tripleo-config/hashed-container-startup-config-step_4.json --overrides '{"health-cmd": "/usr/bin/curl -f http://localhost:8004/v1/", "health-interval": "30s"}' --container heat_api --action run
172ed68eb44ab20551a70a3e33c90a02014f530e42cd7b30255da4577c8ed80c
Debugging container-puppet.py
The container-puppet.py
script manages the config file
generation and puppet tasks for each service. This also exists in the
common directory of
tripleo-heat-templates. When writing these tasks, it's useful to be able
to run them manually instead of running them as part of the entire
stack. To do so, one can run the script as shown below:
CONFIG=/path/to/task.json /path/to/container-puppet.py
Note
Prior to the Train cycle, container-puppet.py was called docker-puppet.py which was located in the docker directory.
The json file must follow the following form:
[
{
"config_image": ...,
"config_volume": ...,
"puppet_tags": ...,
"step_config": ...
}
]
Using a more realistic example. Given a puppet_config section like this:
puppet_config:
config_volume: glance_api
puppet_tags: glance_api_config,glance_api_paste_ini,glance_swift_config,glance_cache_config
step_config: {get_attr: [GlanceApiPuppetBase, role_data, step_config]}
config_image: {get_param: DockerGlanceApiConfigImage}
Would generated a json file called /var/lib/container-puppet/container-puppet-tasks2.json that looks like:
[
{
"config_image": "tripleomaster/centos-binary-glance-api:latest",
"config_volume": "glance_api",
"puppet_tags": "glance_api_config,glance_api_paste_ini,glance_swift_config,glance_cache_config",
"step_config": "include ::tripleo::profile::base::glance::api\n"
}
]
Setting the path to the above json file as the CONFIG environment variable passed to container-puppet.py will create a container using the centos-binary-glance-api:latest image and it and run puppet on a catalog restricted to the given puppet puppet_tags.
As mentioned above, it's possible to create custom json files and call container-puppet.py manually, which makes developing and debugging puppet steps easier.
container-puppet.py also supports the environment variable SHOW_DIFF, which causes it to print out a docker diff of the container before and after the configuration step has occurred.
By default container-puppet.py runs things in parallel. This can make it hard to see the debug output of a given container so there is a PROCESS_COUNT variable that lets you override this. A typical debug run for container-puppet might look like:
SHOW_DIFF=True PROCESS_COUNT=1 CONFIG=glance_api.json ./container-puppet.py
Testing a code fix in a container
Let's assume that we need to test a code patch or an updated package in a container. We will look at a few steps that can be taken to test a fix in a container on an existing deployment.
For example let's update packages for the mariadb container:
(undercloud) [stack@undercloud ~]$ sudo podman images | grep mariadb
192.168.24.1:8787/tripleomaster/centos-binary-mariadb latest 035a8237c376 2 weeks ago 723.5 MB
So container image 035a8237c376 is the one we need to base our work on. Since container images are supposed to be immutable we will base our work off of 035a8237c376 and create a new one:
mkdir -p galera-workaround
cat > galera-workaround/Dockerfile <<EOF
FROM 192.168.24.1:8787/tripleomaster/centos-binary-mariadb:latest
USER root
RUN yum-config-manager --add-repo http://people.redhat.com/mbaldess/rpms/container-repo/pacemaker-bundle.repo && yum clean all && rm -rf /var/cache/yum
RUN yum update -y pacemaker pacemaker-remote pcs libqb resource-agents && yum clean all && rm -rf /var/cache/yum
USER mysql
EOF
To determine which user is the default one being used in a container you can run docker run -it 035a8237c376 whoami. Then we build the new image and tag it with `:workaround1`:
docker build --rm -t 192.168.24.1:8787/tripleomaster/centos-binary-mariadb:workaround1 ~/galera-workaround
Then we push it in our docker registry on the undercloud:
docker push 192.168.24.1:8787/tripleomaster/centos-binary-mariadb:workaround1
At this stage we can either point THT to use 192.168.24.1:8787/tripleomaster/centos-binary-mariadb:workaround1 as the container image by tweaking the necessary environment files and we redeploy the overcloud. If we only want to test a tweaked image, the following steps can be used: First, determine if the containers are managed by pacemaker (those will typically have a :pcmklatest tag) or by paunch. For the paunch-managed containers see Debugging with Paunch. For the pacemaker-managed containers you can (best done on your staging env, as it might be an invasive operation) do the following:
1. `pcs cluster cib cib.xml`
2. Edit the cib.xml with the changes around the bundle you are tweaking
3. `pcs cluster cib-push --config cib.xml`
Testing in CI
When new service containers are added, be sure to update the image names in container-images in the tripleo-common repo. These service images are pulled in and available in the local docker registry that the containers ci job uses.
Packages versions in containers
With the container CI jobs, it can be challenging to find which version of OpenStack runs in the containers. An easy way to find out is to use the logs/undercloud/home/zuul/overcloud_containers.yaml.txt.gz log file and see which tag was deployed.
For example:
container_images:
- imagename: docker.io/tripleomaster/centos-binary-ceilometer-central:ac82ea9271a4ae3860528eaf8a813da7209e62a6_28eeb6c7
push_destination: 192.168.24.1:8787
So we know the tag is ac82ea9271a4ae3860528eaf8a813da7209e62a6_28eeb6c7. The tag is actually a Delorean hash. You can find out the versions of packages by using this tag. For example, ac82ea9271a4ae3860528eaf8a813da7209e62a6_28eeb6c7 tag, is in fact using this Delorean repository.