I am working with a single Docker Compose YAML configuration that works for a variety of environments by using environment variables, aka ${MYENV-default}. However, I've found that the logging: section does not allow this kind of substitution in the logging option names.
logging:
# this works:
driver: ${LOGDRIVER-local}
options:
# this does NOT work:
${LOGOPT1_NAME-max-size}: ${LOGOPT1_VALUE-10m}
${LOGOPT2_NAME-max-file}: ${LOGOPT2_VALUE-3}
Is there a way to make these configurable via environment variables or some other means such that the YAML does not have to be modified depending on what logging driver is to be enabled?
(Docker Compose version v2.14.1)
Multiple compose files is probably my best bet: https://docs.docker.com/compose/extends/#multiple-compose-files
Using multiple Compose files enables you to customize a Compose application for different environments or different workflows.
I can add a secondary YAML which defines the logging and then merge them together when running:
docker-compose -f docker-compose.yaml -f logging.yaml up
Related
I'm trying to avoid race conditions with gcloud / gsutil authentication on the same system but different CI/CD jobs on my Gitlab-Runner on a Mac Mini.
I have tried setting the auth manually with
RUN gcloud auth activate-service-account --key-file="gitlab-runner.json"
RUN gcloud config set project $GCP_PROJECT_ID
for the Dockerfile (in which I'm performing a download operation from a Google Cloud Storage bucket).
I'm using a configuration in the bash script to run the docker command and in the same script for authenticating I'm using
gcloud config configurations activate $TARGET
Where I've previously done the above two commands to save them to the configuration.
The configurations are working fine if I start the CI/CD jobs one after the other has finished. But I want to trigger them for all clients at the same time, which causes race conditions with gcloud authentication and one of the jobs trying to download from the wrong project bucket.
How to avoid a race condition? I'm already authenticating before each gsutil command but still its causing the race condition. Do I need something like CloudBuild to separate the runtime environments?
You can use Cloud Build to get separate execution environments but this might be an overkill for your use case, as a Cloud Build worker uses an entire VM which might be just too heavy, linux containers / Docker can provide necessary isolation as well.
You should make sure that each container you run has a unique config file placed in the path expected by gcloud. The issue may come from improper volume mounting (all the containers share the same location from the host/OS), or maybe you should mount a directory containing their configuration file (unique for each bucket) on running an image, or perhaps you should run gcloud config configurations activate in a Dockerfile step (thus creating image variants for different buckets if it’s feasible).
Alternatively, and I think this solution might be easier, you can switch from Cloud SDK distribution to standalone gsutil distribution. That way you can provide a path to a boto configuration file through an environment variable.
Such variables can be specified on running a Docker image.
Use Case
The docker-compose.yml defines multiple services which represent the full application stack. In development mode, we'd like to dynamically exclude certain services, so that we can run them from an IDE.
As of Docker compose 1.28 it is possible to assign profiles to services as documented here but as far as I have understood, it only allows specifying which services shall be started, not which ones shall be excluded.
Another way I could imagine is to split "excludable" services into their own docker-compose.yml file but all of this seems kind of tedious to me.
Do you have a better way to exclude services?
It seems we both overlooked a certain very important thing about profiles and that is:
Services without a profiles attribute will always be enabled
So if you run docker-compose up with a file like this:
version: "3.9"
services:
database:
image: debian:buster
command: echo database
frontend:
image: debian:buster
command: echo frontend
profiles: ['frontend']
backend:
image: debian:buster
command: echo backend
profiles: ['backend']
It will start the database container only. If you run it with docker-compose --profile backend up it will bring database and backend containers. To start everything you need to docker-compose --profile backend --profile frontend up or use a single profile but several times.
That seems to me as the best way to make docker-compose not to run certain containers. You just need to mark them with a profile and it's done. I suggest you give the profiles reference a second chance as well. Apart from some good examples it explains how the feature interacts with service dependencies.
How to run docker-compose across different lifecycle environments (say dev, qa, staging, production).
Sometimes a larger VM is being shared by multiple developers, so would like to start the containers with appropriate developer specific suffixes (say dev1, dev2, dev3 ..). Should port customization be handled manually via the environment file (i.e. .env file)
This is an unusual use case for docker-compose, but I'll leave some tips anyway! :)
There's two different ways to name stuff you start with docker-compose. One is to name the service that you specify under the main services: key of your docker-compose.yml file. By default, individual running containers will be assigned names indicating what project they are from (by default, the name of the directory from which your docker-compose file is in), what service they run (this is what's specified under your services: key), and which instance of that service they are (this number changes if eg. you're using replicas). Eg. default container names for a service named myservice specified in a compose file ~/my_project/docker/docker-compose.yml will have a name like docker_myservice_1 (or _2, _3, etc if more than one container is supposed to run).
You can use environment variables to specify a lot of key-value pairs in docker-compose files, but you can't conditionally specify the service name - service keys are only allowed to have alphanumeric characters in them and compose files can't look like eg:
version: "3"
services:
${ENVVAR}:
image: ubuntu:20.04
However, you can override the container naming scheme by using the container_name field in your docker-compose file (documentation for usage here). Maybe a solution you could use looks like this:
version: "3"
services:
myservice:
image: ubuntu:20.04
container_name: ${DEVELOPER_ENVVAR?err}
this will require a developer to specify DEVELOPER_ENVVAR at runtime, either by exporting it in their shell or by running docker-compose like DEVELOPER_ENVVAR=myservice_dev1 docker-compose up. Note that using container_name is incompatible with using replicas to run multiple containers for the same service - the names have to be unique for those running containers, so you'll either have to define separate services for each name, or give up on using container_name.
However, you're in a pickle if you expect multiple developers to be able to run containers with different names using the same compose file in the same directory. That's because when starting a service, docker-compose has a Recreating step where, if there's already containers implementing that service running, they'll wait for that container to finish. Ultimately, I think this is for the best - if multiple developers were trying to run the exact same compose project at once, should a developer have control over other developers' running containers? Probably not, right?
If you want multiple developers to be able to run services at once in the same VM, I think you probably want to do two things:
first, (and you may well have already done this! but it's still a good reminder) make sure that this is a good idea. Are there going to be resource contention issues (eg. for port-forwarding) that make different running instances of your project conflict? For many Docker services, there are going to be, but there probably won't be for eg. images that are meant to be run in a swarm.
second, have different compose files checked out in different directories, so that there are separate compose projects for each developer. To use .env files one way one obvious option is to just maintain separate copies, one per developer directory. If, for your use case, it's unsatisfactory to maintain one copy of .env per developer this way, you could use symlinks named .env (or whatever your env file is named) to the same file somewhere else on the VM.
After you've done this, you'll be able to tell from the container names who is running what.
If none of these are satisfactory, you might want to consider, eg. using one VM per developer, or maybe even considering using a different container management system than docker-compose.
I have done very similar automation and I've used Ansible to create "docker compose" config on the fly.
So based on input-Environment , the ansible playbook will create the relevant docker-compose file. So basically I have a docker-compose template in my git repository with values that are dynamic and ansible playbook populates them etc.
and also you can use ansible to trigger such creation or automation one after another
A similar sample has been posted at ansible_docker_splunk repository.
Basically the whole project is to automate end-to-end docker cluster from CSV file
mem_limit is no longer supported in version 3 of docker-compose.yml file. The documentation tells that I should use the deploy.resources key instead but also that this part will only be effective with swarm or docker stack.
cpu_shares, cpu_quota, cpuset, mem_limit, memswap_limit: These have been replaced by the resources key under deploy. Note that deploy configuration only takes effect when using docker stack deploy, and is ignored by docker-compose.
... as written in the docs.
How do I set memory/cpu limits with docker-compose with v3 format of the yml file?
I was wondering the same thing and found this:
https://github.com/docker/compose/issues/4513
So in short it's just not possible to do that, you have to use the version 2.1 of the docker-compose format to be able to specify limits that are not ignored by docker-compose up
you can try docker-compose --compatibility up which is CLI flag that convert v3 files to their v2 equivalent, with deploy options translated when possible.
I was searching for this issue a while ago. I have found my answer here. At first, I tried to implement this functionality without using docker stack, but that did not work.
Here is the piece of code which you would use to limit container's CPU/memory consumption. For additional attributes, you can search the documentation of docker.
deploy:
replicas: 5
resources:
limits:
cpus: "0.1"
memory: 50M
Compose file does not recognize deploy attributes, unless you deploy the application as a stack.
This is not the case anymore. According to the new documentation here: https://docs.docker.com/compose/compose-file/compose-file-v3/#deploy
It states that resources are repspected by docker compose.
I can confirm this now.
I'm not sure I completely understand the role of Docker in the process of development and deployment.
Say, I create a Dockerfile with nginx, some database and something else which creates a container and runs fine.
I drop it somewhere in the cloud and execute it to install and configure all the dependencies and environment settings.
Next, I have a repository with a web application which I want to run inside the container I created and deployed in the first 2 steps. I regularly work on it and push the changes.
Now, how do I integrate the web application into the container?
Do I put it as a dependency inside the Dockerfile I create in the 1st step and recreate the container each time from scratch?
Or, do I deploy the container once but have procedures inside Dockerfile that install utils that pull the code from repo by command or via hooks?
What if a container is running but I want to change some settings of, say, nginx? Do I add these changes into Dockerfile and recreate the image?
In general, what's the role of Docker in the daily app development routine? Is it used often if the infrastructure is running fine and only code is changing?
I think there is no singl "use only this" answer - as you already outlined, there are different viable concepts available.
Deployment to staging/production/pre-production
a)
Do I put it as a dependency inside the Dockerfile I create in the 1st step and recreate the container each time from scratch?
This is for sure the most docker`ish way and aligns fully with he docker-philosophy. It is highly portable, reproducible and suites anything, from one container to "swarm" thousands of. E.g. this concept has no issue suddenly scaling horizontally when you need more containers, lets say due to heavy traffic / load.
It also aligns with the idea that only the configuration/data should be dynamic in a docker container, not code / binaries /artifacts
This strategy should be chosen for production use, so when not as frequent deployments happen. If you care about downtimes during container-rebuilds (on upgrade), there are good concepts to deal with that too.
We use this for production and pre-production intances.
b)
Or, do I deploy the container once but have procedures inside
Dockerfile that install utils that pull the code from repo by command
or via hooks?
This is a more common practice for very frequent deployment. You can go the pull ( what you said ) or the push (docker cp / ssh scp) concept, while i guess the latter is preferred in this kind of environment.
We use this for any kind strategy for staging instances, which basically should reflect the current "codebase" and its status. We also use this for smoke-tests and CI, but depending on the application. If the app actually changes its dependencies a lot and a clean build requires a rebuild with those to really ensure stuff is tested as it is supposed to, we actually rebuild the image during CI.
Configuration management
1.
What if a container is running but I want to change some settings of,
say, nginx? Do I add these changes into Dockerfile and recreate the
image?
I am not using this as c) since this is configuration management, not applications deployment and the answer to this can be very complicated, depending on your case. In general, if redeployment needs configuration changes, it depends on your configuration management, if you can go with b) or always have to go a).
E.g. if you use https://github.com/markround/tiller with consul as the backend, you can push the configuration changes into consul, regenerating the configuration with tiller, while using consul watch -prefix /configuration tiller as a watch-task to react on those value changes.
This enables you to go b) and fix the configuration
You can also use https://github.com/markround/tiller and on deployment, e.g. change ENV vars or some kind of yml file ( tiller supports different backends ), and call tiller during deployment yourself. This most probably needs you to have ssh or you ssh on the host and use docker cp and docker exec
Development
In development, you generally reuse your docker-compose.yml file you use for production, but overload it with docker-compose-dev.yml to e.g. mount your code-folder, set RAILS_ENV=development, reconfigurat / mount some other configurations like xdebug or more verbose nginx loggin, whatever you need. You can also add some fake MTA-services like fermata and so on
docker-compose -f docker-compose.yml -f docker-compose-dev.yml up
docker-compose-dev.yml only overloads some values, it does not redefine it or duplicate it.
Depending on how powerful your configuration management is, you can also do a pre-installation during development stack up.
We actually use scaffolding for that, we use https://github.com/xeger/docker-compose and after running it, we use docker exec and docker cp to preinstall a instance or stage something. Some examples are here https://github.com/EugenMayer/docker-sync/wiki/7.-Scripting-with-docker-sync
If you are developing under OSX and you face performance issues due to OSXFS / code shares, you probably want to have a look at http://docker-sync.io ( i am biased though )