I have a couple of questions related to the usage of Docker in a development phase.
I am going to propose three different scenarios of how I think Docker could be used in a development environment. Let's imagine that we are creating a REST API in Java and Spring Boot. For this I will need a MySQL database.
The first scenario is to have a docker-compose for development with the MySQL container and a production docker-compose with MySQL and the Java application (jar) in another container. To develop I launch the docker-compose-dev.yml to start only the database. The application is launched and debugged using the IDE, for example, IntelliJ Idea. Any changes made to the code, the IDE will recognize and relaunch the application by applying the changes.
The second scenario is to have, for both the development and production environment, a docker-compose with the database and application containers. That way, every time I make a change in the code, I have to rebuild the image so that the changes are loaded in the image and the containers are lauched again. This scenario may be the most typical and used for development with Docker, but it seems very slow due to the need to rebuild the image every time there is a change.
The third scenario consists of the mixture of the previous two. Two docker-compose. The development docker-compose contains both containers, but with mechanisms that allow a live reload of the application, mapping volumes and using, for example, Spring Dev Tools. In this way, the containers are launched and, in case of any change in the files, the application container will detect that there is a change and will be relaunched. For production, a docker-compose would be created simply with both containers, but without the functionality of live reload. This would be the ideal scenario, in my opinion, but I think it is very dependent on the technologies used since not all allow live reload.
The questions are as follows.
Which of these scenarios is the most typical when using Docker for phase?
Is scenario 1 well raised? That is, dockerize only external services, such as databases, queues, etc. and perform the development and debugging of the application with the IDE without using Docker for it.
The doubts and the scenarios that I raise came up after I raised the problem that scenario 2 has. With each change in the code, having to rebuild the image and start the containers again is a significant waste of time. In short, a question would be: How to avoid this?
Thanks in advance for your time.
NOTE: It may be a question subject to opinion, but it would be nice to know how developers usually deal with these problems.
Disclaimer: this is my own opinion on the subject as asked by Mr. Mars. Even though I did my best to back my answer with actual sources, it's mostly based on my own experience and a bit of common sense
Which of these scenarios is the most typical when using Docker for development?
I have seen all 3 scenarios iin several projects, each of them with their advantages and drawbacks. However I think scenario 3 with a Docker Compose allowing for dynamic code reload is the most advantageous in term of flexibility and consistency:
Dev and Prod Docker Compose are close matches, meaning Dev environment is as close as possible to Prod environment
You do not have to rebuild the image constantly when developping, but it's easy to do when you need to
Lots of technologies support such scenario, such as Spring Dev Tools as you mentionned, but also Python Flask, etc.
You can easily leverage Docker Compose extends a.k.a configuration sharing mechanism (also possible with scenario 2)
Is scenario 1 well raised? That is, dockerize only external services, such as databases, queues, etc. and perform the development and debugging of the application with the IDE without using Docker for it.
Scenario 1 is quite common, but the IDE environment would probably be different than the one from the Docker container (and it would be difficult to maintain a match of version for each libs, dependencies, etc. from IDE environment to Docker environment). It would also probably require to go through an intermediate step between Dev and Production to actually test the Docker image built after Dev is working before going to Production.
In my own experience doing this is great when you do not want to deal too much with Docker when actually doing dev and/or the language or technology you use is not adapted for dynamic reload as described in scenario 3. But in the end it only adds a drift between your environments and more complexity between Dev and Prod deployment method.
having to rebuild the image and start the containers again is a significant waste of time. In short, a question would be: How to avoid this?
Beside the scenarios you describe, you have ways to decently (even drastically) reduce image build time by leveraging Docker build cache and designing your Dockerfile. For example, a Python application would typically copy code as the last (or almost last) step of the build to avoid invalidating the cache, and for Java app it would be possible to split code so as to avoid compiling the entire application everytime a bit of code changes - that would depend on your actual setup.
I personally use a workflow roughly matching scenario 3 such as:
a docker-compose.yml file corresponding to my Production environment
a docker-compose.dev.yml which will override some aspect of my main Docker Compose file such as mouting code from my machine, adding dev specific flags to commands, etc. - it would be run such as
docker-compose -f docker-compose.yml -f docker-compose.dev.yml
but it would also be possible to have a docker-compose.override.yml as Docker Compose uses by default for override
in some situation I would have to use other overrides for specific situations such as docker-compose.ci.yml on my CI, but usually the main Docker Compose file is enough to describe my Prod environment (and if that's not the case, docker-compose.prod.yml does the trick)
I've seen them all used in different scenarios. There are some gotchas to avoid:
Applications inside of a container shouldn't depend on something running outside of a container on the host. So all of your dependencies should be containerized first.
File permissions with host volumes can be complicated depending on your version of docker. Some of the newer Docker Desktop installs automatically handle uid mappings, but if you develop directly on Linux you'll need to ensure the containers run as the same uid as your host user.
Avoid making changing inside the container if that isn't mapped into a host volume, since those changes will be lost when the container is recreated.
Looking at each of the options, here's my assessment of each:
Containerizing just the DB: This works well when developers already have a development environment for the language of choice, and there's no risk of external dependencies creeping in, e.g. a developer upgrading their JDK install to a newer version than the image is built with. It follows the idea of containerizing the dependencies first, while also giving developers the familiar IDE integration with their application.
Rebuilding the Image for Every Change: This tends to be the least ideal for developer workflow, but the quickest to implement when you're not familiar with the tooling. I'll give a 4th option that I consider an improvement to this.
Everything in a container, volume mounts, and live reloading: This is the most complicated to implement, and requires the language itself to support things like live reloading. However, when they do, it is nearly seamless for the developers and gets them up to speed on a new project quickly without needing to install any other tooling to get started.
Rebuild the app in the container with volume mounts: This is a halfway point between 2 and 3. When you don't have live reloading, you likely need to recompile or restart the interpreter to see any change. Rather than rebuilding the image, I put the recompile step in the entrypoint of a development image. I'll mount the code into the container, and run a full JDK instead of just a JRE (or whatever compiler is needed). I use named volumes for any dependency caches so they don't need to download on every restart. Then the method to see the changes is to restart that one container. The steps are identical to a compiled binary outside of a container, stop the old service, recompile, and restart the service, but now it happens inside of a container that should have the same tools used when building the production image.
For option 4, I tend to use a multi-stage build that has stages for build, develop, and release. The build stage pulls in the code and compiles it, the develop stage is the same base image as build but with an entrypoint that does the compile/run, and the release stage copies the result of the build stage into a minimal runtime. Developers then have a compose file for development that creates the development image and runs that with volume mounts and any debugging ports opened.
First of all, docker-compose is just for development and also testing phase, not for production. Example:
With a minimal and basic docker-compose, all your containers will run in the same machine? For development purposes it is ok, but in production, put all the apps in just one machine is a risk
Official link https://docs.docker.com/compose/production/
We will assume
01 java api
01 mysql database
01 web application that needs the api
all of these applications are already in production
Quick Answer
If you need to fix or add new feature to the java api, I advice you to use an ide like eclipse or IntelliJ Idea. Why?
Because java needs compilation.
Compile inside a docker container will take more time due to maven dependencies
IDE has code auto completion
etc
In this development phase, Docker helps you with one of its most powerful features: "Bring the production containers to your localhost". Yeah, in this case, docker-compose.yml is the best option because with one file, you could start everything you need : mysql database and web app but not your java api. Open your java api with your favorite ide.
Anyway if you want to use docker to "develop", you just need the Dockerfile and perform a docker build ... when you need to run your source code in your localhost
Basic Devops Life cycle with docker
Developer push source code changes using git
Your continuous integration (C.I) platform detect this change and perform
docker build ... (In this step, unit test are triggered)
docker push to your private hub. Container is uploaded in this step and will be used to deployments on other servers.
docker run or container deploy to the next environment : testing
Human testers ,selenium or another automation start their work
If no errors are detected, your C.I perform perform a final deploy of the uploaded container to your production environment. No docker build are required, just deploy or docker run.
Some Tips
Docker features are awesome but sometimes add too much complexity. So stop using volumes , hard disk dependency, logs, or complex configurations. If you use volumes, what will happen when your containers are in different hosts?
Java and Nodejs are a stable languages and your rest api or web apps does not need crazy configurations. Just maven compilation and java -jar ... or npm install and npm run start.
For logs you could use https://www.graylog.org/, google stasckdriver or another log management.
And like Heroku, stop using hard disk dependency as much as possible. In heroku platform disk are disposable, it means disappear when app is restarted. So instead of local file storage, you could use another file storage service with a lot of functionalities.
With this approaches, your containers can be deployed anywhere in a simple way
I'm using something similar to your 3rd scenario for my web dev, but it is Node-based. So I have 3 docker-compose files (actually 4, one is base and having all common stuff for others) for dev, staging and production environments.
Staging docker-compose config is similar to production config excluding SSL, ports and other things that may not allow to use it locally.
I have a separate container for each service (like DB, queue), and for dev, I also have additional dev DB and queue containers mostly for running auto-tests. In dev environment, all source are mounted into containers, so it allows to use IDE/editor of choice outside the container, and see changes inside.
I use supervisor to manage my workers inside a container with workers and have some commands to restart my workers manually when I need this. Maybe you can have something similar to recompile/restart your Java app. Or if you have an idea of how to organize app source code changes detection and your app auto-reloading, than could be the best variant. By the way, you gave me an idea to research something similar suitable for my case.
For staging and production environment, my source code is included inside the corresponding container using production Dockerfile. And I have some commands to restart all stuff using an environment I need, and this typically includes rebuilding containers, but because of Docker cache, it doesn't take much time (about 20 seconds). And taking into account that switching between environments is not a too frequent operation I feel quite comfortable with this.
Production docker-compose config is used only during deployment because it enables SSL, proper ports and has some additional production stuff.
Update for details on backend app restarting using Supervisor:
This is how I use it in my projects:
A part of my Dockerfile with installing Supervisor:
FROM node:10.15.2-stretch-slim
RUN apt-get update && apt-get install -y \
# Supervisor
supervisor \
...
...
# Configs for services/workers managed by supervisor
COPY some/path/worker-configs/*.conf /etc/supervisor/conf.d/
This is an example of one of Supervisor configs for a worker:
[program:myWorkerName]
command=/usr/local/bin/node /app/workers/my-worker.js
user=root
numprocs=1
stopsignal=INT
autostart=true
autorestart=true
startretries=10
In this example in your case command should run your Java app.
And this is an example of command aliases for convenient managing Supervisor from outside of containers. I'm using Makefile as a universal runner of all commands, but this can be something else.
# Used to run all workers
su-start:
#docker exec -t MY-WORKERS-CONTAINER-NAME supervisorctl start all
# Used to stop all workers
su-stop:
#docker exec -t MY-WORKERS-CONTAINER-NAME supervisorctl stop all
# Used to restart all workers
su-restart:
#docker exec -t MY-WORKERS-CONTAINER-NAME supervisorctl restart all
# Used to check status of all workers
su-status:
#docker exec -t MY-WORKERS-CONTAINER-NAME supervisorctl status
As I described above these Supervisor commands need to be run manually, but I think it is possible to implement maybe another Node-based worker or some watcher outside of a container with workers that will detect file system changes for sources directory and run these commands automatically. I think it is possible to implement something like this using Java as well like this or this.
On the other hand, it needs to be done carefully to avoid constant restarting workers on every little change.
Google Cloud Run is new. Is it possible to run WordPress docker on it? Perhaps using gce as database for the mysql/mariadb. Can't find any discussion on this
Although I think this is possible, it's not a good use of your time to go through this exercise. Cloud Run might not be the right tool for the job.
UPDATE someone blogged a tutorial about this (use at your own risk): https://medium.com/acadevmy/how-to-install-a-wordpress-site-on-google-cloud-run-828bdc0d0e96
Here are a few points to consider;
(UPDATE: this is not true anymore) Currently Cloud Run doesn't support natively connecting to Cloud SQL (mysql). There's been some hacks like spinning up a cloudsql_proxy inside the container: How to securely connect to Cloud SQL from Cloud Run? which could work OK.
You need to prepare your wp-config.php beforehand and bake it into your container image. Since your container will be wiped away every now and then, you should install your blog (creates a wp-config.php) and bake the resulting file into the container image, so that when the container restarts, it doesn't lose your wp-config.php.
Persistent storage might be a problem: Similar to point #2, restarting a container will delete the files saved to the container after it started. You need to make sure stuff like installed plugins, image uploads etc SHOULD NOT write to the local filesystem of the container. (I'm not sure if wordpress lets you write such files to other places like GCS/S3 buckets.) To achieve this, you'd probably end up using something like the https://wordpress.org/plugins/wp-stateless/ plugin or gcs-media-plugin.
Any file written to local filesystem of a Cloud Run container also count towards your container's available memory, so your application may run out of memory if you keep writing files to it.
Long story short, if you can make sure your WP installation doesn't write/modify files on your local disk, it should be working fine.
I think Cloud Run might be the wrong tool for the job here since it runs "stateless" containers, and it's pretty damn hard to make WordPress stateless, especially if you're installing themes/plugins, configuring things etc. Not to mention, your Cloud SQL server won't be "serverless", and you'll be paying for it while it's not getting any requests as well.
(P.S. This would be a good exercise to try out and write a blog post about! If you do that, add it to the awesome-cloudrun repo.)
I am venturing into using docker and trying to get a firm grasp of the product.
While I love everything it promises it is a big change from doing things manually.
Right now I understand how to build a container, attach your code, commit and push it to your repo.
But what I am really wondering is how do I update my code once deployed, for example, I have some minor bug fixes but no change to dependencies but I also run a database in the same container.
Container:
Node & NPM
Nginx
Mysql
php
Right now the only way I understand you can do it is to close thje container re pull the new container and run, but I am thinking you will lose database data.
I have been reading into https://docs.docker.com/engine/tutorials/dockervolumes/
and thinking maybe the container mounts a data file that persists between containers.
What I am trying to do is run a web app/website with the above container layout and just change code with latest bugfixes/features.
You're quite correct. Docker images are something you should be rebuilding and discarding with each update - avoid commit wherever possible (outside your build scripts anyway).
Persistent state should be managed via data containers that you then mount with your image. Thus your "data" is decoupled from that specific version and instance of the application.
I have a laravel project which I am using with docker. Currently I am using a single container to host all the services (apache, mySQL etc) as well as the needed dependencies (project files, git, composer etc) I need for my project.
From what I am reading the current best practice is to put each service into a separate container. So far this seems simple enough since these services are designed to run at length (apache server, mySQL server). When I spin up these 'service' containers using -d they remain running (docker ps) since their main process continuously runs.
However, when I remove all the services from my project container, then there is no main process left to continuously run. This means my container immediately exits once spun up.
I have read the 'hacks' of running other processes like tail -f /dev/null, sleep infinity, using interactive mode, installing supervisord (which I assume would end up watching no processes in such containers?) and even leaving the container to run in the foreground (taking up a terminal console...).
How do I network such a container to keep it running like the abstracted services but detached without these hacks? I cannot seem to find much information on this in the official docker docs nor can I find any examples of other projects (please link any)
EDIT: I am not talking about volumes / storage containers to store the data my project processes, but rather how I can use a container to store the project itself and its dependencies that aren't services (project files, git, composer)
when you run the container try running with the flags ...
docker run -dt ..... etc
you might even try .....
docker run -dti ..... etc
let me know if this brings any joy. has certainly worked for me on occassions.
i know you wanted to avoid hacks but if the above fails then also add ...
CMD cat
to the end of your Dockerfile - it is a hack but is the cleanest hack :)
So after reading this a few times along with Joachim Isaksson's comment, I finally get it. Tools don't need the containers to run continuously to use. Proper separation of the project files, services (mySQL, apache) and tools (git, composer) are done differently.
The project files are persisted within a data volume container. The services are networked since they expose ports. The tools live in their own containers which share the project files data volume - they are not networked. Logs, databases and other output can be persisted in different volumes.
When you wish to run one of these tools, you spin up the tool container by passing the relevant command using docker run. The tool then manipulates the data within the directory persisted within the shared volume. The containers only persist as long as the command to manipulate the data within the shared volume takes to run and then the container stops.
I don't know why this took me so long to grasp, but this is the aha moment for me.
I have a hunch that docker could greatly improve my webdev workflow - but I haven't quite managed to wrap my head around how to approach a project adding docker to the stack.
The basic software stack would look like this:
Software
Docker image(s) providing custom LAMP stack
Apache with several modules
MYSQL
PHP
Some CMS, e.g. Silverstripe
GIT
Workflow
I could imagine the workflow to look somewhat like the following:
Development
Write a Dockerfile that defines a LAMP-container meeting the requirements stated above
REQ: The machine should start apache/mysql right after booting
Build the docker image
Copy the files required to run the CMS into e.g. ~/dev/cmsdir
Put ~/dev/cmsdir/ under version control
Run the docker container, and somehow mount ~/dev/cmsdir to /var/www/ on the container
Populate the database
Do work in /dev/cmsdir/
Commit & shut down docker container
Deployment
Set up remote host (e.g. with ansible)
Push container image to remote host
Fetch cmsdir-project via git
Run the docker container, pull in the database and mount cmsdir into /var/www
Now, this looks all quite nice on paper, BUT I am not quite sure whether this would be the right approach at all.
Questions:
While developing locally, how would I get the database to persist between reboots of the container instance? Or would I need to run sql-dump every time before spinning down the container?
Should I have separate container instances for the db and the apache server? Or would it be sufficient to have a single container for above use case?
If using separate containers for database and server, how could I automate spinning them up and down at the same time?
How would I actually mount /dev/cmsdir/ into the containers /var/www/-directory? Should I utilize data-volumes for this?
Did I miss any pitfalls? Anything that could be simplified?
If you need database persistance indepent of your CMS container, you can use one container for MySQL and one container for your CMS. In such case, you can have your MySQL container still running and your can redeploy your CMS as often as you want independently.
For development - the another option is to map mysql data directories from your host/development machine using data volumes. This way you can manage data files for mysql (in docker) using git (on host) and "reload" initial state anytime you want (before starting mysql container).
Yes, I think you should have a separate container for db.
I am using just basic script:
#!/bin/bash
$JOB1 = (docker run ... /usr/sbin/mysqld)
$JOB2 = (docker run ... /usr/sbin/apache2)
echo MySql=$JOB1, Apache=$JOB2
Yes, you can use data-volumes -v switch. I would use this for development. You can use read-only mounting, so no changes will be made to this directory if you want (your app should store data somewhere else anyway).
docker run -v=/home/user/dev/cmsdir:/var/www/cmsdir:ro image /usr/sbin/apache2
Anyway, for final deployment, I would build and image using dockerfile with ADD /home/user/dev/cmsdir /var/www/cmsdir
I don't know :-)
You want to use docker-compose. Follow the tutorial here. Very simple. Seems to tick all your boxes.
https://docs.docker.com/compose/
I understand this post is over a year old at this time, but I have recently asked myself very similar questions and have several great answers to your questions.
You can setup a MySQL docker instance and have data persist on a stateless data container, aka the data container does not need to be actively running
Yes I would recommend having a separate instance for your web server and database. This is the power of Docker.
Check out this repo I have been building. Basically it is as simple as make build & make run and you can have a web server and database container running locally.
You use the -v argument when running the container for the first time, this will link a specific folder on the container to the host running the container.
I think your ideas are great and it is currently possible to achieve all that you are asking.
Here is a turn key solution achieving all of the needs you have listed.
I've put together an easy to use docker compose setup that should match your development workflow requirements.
https://github.com/ehyland/docker-silverstripe-dev
Main Features
Persistent DB
Your choice of HHVM + NGINX or Apache2 + PHP5
Debug and set breakpoints with xDebug
The README.md should be clear enough to get you started.