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.
Related
I dockerize my SPA web app by using nginx as base image then copy my nginx.conf and build files. As Dockerize Vue.js App mention I think many dockerizing SPA solutions are similar.
If I don't use docker I will first build SPA code then copy the build files to nginx root directory (After install/set up nginx I barely change it at all)
So what's the benefit of dockerizing SPA?
----- update -----
One answer said "If the app is dockerized each time you are releasing a new version of your app the Nginx server gets all the new updates available for it." I don't agree with that at all. I don't need the latest version of nginx, after all I only use the basic feature of nginx. Some of my team members just use the nginx version bundled with linux when doing development. If my docker image uses the latest ngixn it actually creates the different environment than the development environment.
I realize my question will be probably closed b/c it will be seen as opinion based. But I have googled it and can't find a satisfied answer.
If I don't use docker I will first build SPA code then copy the build files to nginx root directory (After install/set up nginx I barely change it at all)
This is a security concern... fire and forget is what it seems is being done here regarding the server.
If the app is dockerized each time you are releasing a new version of your app the Nginx server gets all the new updates available for it.
Bear in mind that if your App does not release new versions in a weekly bases then you need to consider to rebuild the docker images at least weekly in order to get the updates and keep everything up to date with the last security patches.
So what's the benefit of dockerizing SPA?
Same environment across development, staging and production. This is called 100% parity across all stages were you run your app, and this true for no matter what type of application you deploy.
If something doesn't work in production you can pull the docker image by the digest and run it locally to debug and try to understand where is the problem. If you need to ssh to a production server it means that you automation pipeline have failed or maybe your are not even using one...
Tools like Webpack compile Javascript applications to static files that can then be served with your choice of HTTP server. Once you’ve built your SPA, the built files are indistinguishable from pages like index.html and other assets like image files: they’re just static files that get served by some HTTP server.
A Docker container encapsulates a single running process. It doesn’t really do a good job at containing these static files per se.
You’ll frequently see “SPA Docker containers” that run a developer-oriented HTTP server. There’s no particular benefit to doing this, though. You can get an equally good developer experience just by developing your application locally, running npm run build or whatever to create a dist directory, and then publishing that the same way you’d publish other assets. An automation pipeline is helpful here, but this isn’t a task Docker makes wildly simpler.
(Also remember when you do this that the built application runs on the user’s browser. That means it can’t see any of the Docker-internal networking machinery: it can’t use the Docker-internal IP addresses and it can’t use the built-in Docker DNS service. Everything it reaches has to be on docker run -p published ports and it has to use a DNS name that reaches the host. The browser literally has no idea Docker is involved in this at all.)
There are a few benefits.
Firstly, building a Docker image means you are explicitly stating what your application's canonical run-time is - this version of nginx, with that SSL configuration, whatever. Changes to the run-time are in source control, so you can upgrade predictably and reversibly. You say you don't want "the latest version" - but what if that latest version patches a critical security vulnerability? Being able to upgrade predictably, on "disposable" containers means you upgrade when you want to.
Secondly, if the entire development team uses the same Docker image, you avoid the challenges with different configurations giving the "it works on my machine" response to bugs - in SPAs, different configurations of nginx can lead to different behaviour. New developers who join the team don't have to install or configure anything, and can use any device they want - they can be certain that what runs in Docker is the same as it is for all the other developers.
Thirdly, by having all your environments containerized (not just development, but test and production), you make it easy to move versions through the pipeline and only change the environment-specific values.
Now, for an SPA, these benefits are real, but may not outweigh the cost and effort of creating and maintaining Docker images - inevitably, the Docker image becomes a bottleneck and the first thing people blame. I'd only invest in it if you see lots of environment-specific pain (suggesting having a consistent run-time environment is necessary), or if you see lots of "it works on my machine" type of bug.
I am struggling on a question that nobody seems to answer in detail on the Internet.
"Standardizing service infrastructure across the entire pipeline allows every team member to work in a production parity environment"
This is a key benefit of Docker : it allows everybody to develop, test or whatever in a production-like environment. Because the container that is passed through the pipeline is always the same.
I get that. I understand that this is necessary and that Docker allows this easily.
But what I don't understand, is why was it so hard before Docker ? If I have a production machine and a testing machine, I won't have any problem building a script that installs the right dependencies, no matter what the machine is. So my environment in terms of libraries or frameworks will be the same.
The only thing that I understand with this whole environment-related benefit, is that Docker allows a developer to choose his OS without fear of the platform-related bugs. I've already run into features that worked on Windows and not on Mac. Worst kind of bugs in my opinion. So yeah if I had Docker at the time, I wouldn't have had this problem. But I don't understand why Docker was such a miracle for other environment-related stuff.
I think I am not understanding this because I've only worked on small scale projects. Maybe I also don't realize the full meaning of the word "environment".
What am I missing here ? Why containers were a breakthrough for standardizing environments, whereas scripts can achieve that ?
The following list is not exhaustive, it represents only three important advantages of docker. Please note that docker is not a magical solution and may not be adapted in specific contexts.
Firstly, with containers you don't have conflicts between dependencies.
If you have two programs using the same library at different version you'll have to manually install both versions and specify custom environment variables before executing your programs. (For example LD_LIBRARY_PATH). Please note that some tools exists to address this issue but only in specific cases (virtualenvs in python for example).
Secondly, with containers you don't have persistence.
For example if you write a little bash script to install your development environment based on Nginx and PHP and by mistake I install Apache, my package will still be present even if you run again your script. The thing is Apache will sometimes starts before Nginx and block the 80 port, breaking your development environment.
To sum up, without docker you're not sure about the state of untracked elements and they may break your environment.
Thirdly, docker allows you to reduce the gap between development and production.
The close environment is "everything needed for your code to run". For example libraries, config files, your interpreter (python, php, ...). Docker packages the application with its close environment so you don't have mismatches between what your app needs and the environment you provided.
This is especially important when you update dependencies during development and may forget to update them in production.
A false argument is security and isolation. The security process starts with defining your threat model and then choosing countermeasures. Adding docker because it increases security in a risky environment won't be enough (there is no kernelspace isolation) and adding docker for security if you don't need more is called paranoïa. Docker adds userspace isolation and default seccomp profiles, but this is not a reason to use it, except if it matches your threat model.
I would like a Jenkins master and slave setup for running specs on standard Rails apps (PostgreSQL, sidekiq/redis, RSPec, capybara-webkit, a common Rails stack), using docker so it can be put on other machines as well. I got a few good stationary machines collecting dust.
Can anybody share an executable docker jenkins rails stack example?
What prevents that from being done?
Preferable with master-slave setup too.
Preface:
After days online, following several tutorials with no success, I am about to abandon project. I got a basic understanding of docker, docker-machine, docker compose and volumes, I got a docker registry of a few simple apps.
I know next to nothing about Jenkins, but I've used Docker pretty extensively on other CI platforms. So I'll just write about that. The level of difficulty is going to vary a lot based on your app's dependencies and quirks. I'll try and give an outline that's pretty generally useful, and leave handling application quirks up to you.
I don't think the problem you describe should require you to mess about with docker-machine. docker build and docker-compose should be sufficient.
First, you'll need to build an image for your application. If your application has a comprehensive Gemfile, and not too many dependencies relating to infrastructure etc (e.g. files living in particular places that the application doesn't set up for itself), then you'll have a pretty easy time. If not, then setting up those dependencies will get complicated. Here's a guide from the Docker folks for a simple Rails app that will help get you started.
Once the image is built, push it to a repository such as Docker Hub. Log in to Docker Hub and create a repo, then use docker login and docker push <image-name> to make the image accessible to other machines. This will be important if you want to build the image on one machine and test it on others.
It's probably worth spinning off a job to run your app's unit tests inside the image once the image is built and pushed. That'll let you fail early and avoid wasting precious execution time on a buggy revision :)
Next you'll need to satisfy the app's external dependencies, such as Redis and postgres. This is where the Docker Compose file comes in. Use it to specify all the services your app needs, and the environment variables etc that you'll set in order to run the application for testing (e.g. RAILS_ENV).
You might find it useful to provide fakes of some non-essential services such as in-memory caches, or just leave them out entirely. This will reduce the complexity of your setup, and be less demanding on your CI system.
The guide from the link above also has an example compose file, but you'll need to expand on it. The most important thing to note is that the name you give a service (e.g. db in the example from the guide) is used as a hostname in the image. As #tomwj suggested, you can search on Docker Hub for common images like postgres and Redis and find them pretty easily. You'll probably need to configure a new Rails environment with new hostnames and so on in order to get all the service hostnames configured correctly.
You're starting all your services from scratch here, including your database, so you'll need to migrate and seed it (and any other data stores) on every run. Because you're starting from an empty postgres instance, expect that to take some time. As a shortcut, you could restore a backup from a previous version before migrating. In any case, you'll need to do some work to get your data stores into shape, so that your test results give you useful information.
One of the tricky bits will be getting Capybara to run inside your application Docker image, which won't have any X displays by default. xvfb (X Virtual Frame Buffer) can help with this. I haven't tried it, but building on top of an image like this one may be of some help.
Best of luck with this. If you have the time to persist with it, it will really help you learn about what your application really depends on in order to work. It certainly did for me and my team!
There's quite a lot to unpack in that question, this is a guide of how to get started and where to look for help.
In short there's nothing preventing it, although it's reasonably complex and bespoke to setup. So hence no off-the-shelf solution.
Assuming your aim is to have Jenkins build, deploy to Docker, then test a Rails application in a Dockerised environment.
Provision the stationary machines, I'd suggest using Ansible Galaxy roles.
Install Jenkins
Install Docker
Setup a local Docker registry
Setup Docker environment, the way to bring up multiple containers is to use docker compose this will allow you to bring up the DB, redis, Rails etc... using the public docker hub images.
Create a Jenkins pipeline
Build the rails app docker image this will contain the rails app.
Deploy the application, this updates the application in the Docker swarm, from the local Docker registry.
Test, run the tests against the application now running.
I've left out the Jenkins master/slave config because if you're only running on one machine you can increase the number of executors. E.g. the master can execute more jobs at the expense of speed.
Recently I started to practice Dockers. Basically, I am running a C application on Docker container. Now, I want to try cloud foundry, therefore, trying to understand the difference between the two.
I'll describe the application as a novice because I am.
The application I start as a service(from /etc/init.d) and it reads a config file during startup, which specifies what all modules to load and IP of other services and it's own (0.0.0.0 does not work, so I have to give actual IP).
I had to manually update the IP and some details in the config file when the container starts. So, I wrote a startup script which did all the changes when the container starts and then the service start command.
Now, moving on to Cloud Foundry, the first thing I was not able to find is 'How to deploy C application' then I found a C build pack and a binary build pack option. I still have to try those but what I am not able to understand how I can provide a startup script to a cloud foundry container or in brief how to achieve what I was doing with Dockers.
The last option I have is to use docker containers in Cloud foundry, but I want to understand if I can achieve what I described above.
I hope I was clear enough to explain my doubt.
Help appreciated.
An old question, but a lot has changed since this was posted:
Recently I started to practice Dockers. Basically, I am running a C application on Docker container. Now, I want to try cloud foundry, therefore, trying to understand the difference between the two.
...
The last option I have is to use docker containers in Cloud foundry, but I want to understand if I can achieve what I described above.
There's nothing wrong with using Docker containers on CF. If you've already got everything set up to run inside a Docker container, being able to run that on CF give you yet another place you can easily deploy your workload.
While these are pretty minor, there are a couple requirements for your Docker container, so it's worth checking those to make sure it's possible to run on CF.
https://docs.cloudfoundry.org/devguide/deploy-apps/push-docker.html#requirements
Anyways, I am not working on this now as CF is not suitable for the project. It's an SIP application and CF only accepts HTTP/S requests.
OK, the elephant in the room. This is no longer true. CF has support for TCP routes. These allow you to receive TCP traffic directly to your application. This means, it's no longer just HTTP/S apps that are suitable for running on CF.
Instructions to set up your CF environment with TCP routing: https://docs.cloudfoundry.org/adminguide/enabling-tcp-routing.html
Instructions to use TCP routes as a developer: https://docs.cloudfoundry.org/devguide/deploy-apps/routes-domains.html#create-route-with-port
Now, moving on to Cloud Foundry, the first thing I was not able to find is 'How to deploy C application' then I found a C build pack and a binary build pack option.
Picking a buildpack is an important step. The buildpack takes your app and prepares it to run on CF. A C buildpack might sound nice as it would take your source code, build and run it, but it's going to get tricky because your C app likely depends on libraries. Libraries that may or may not be installed.
If you're going to go this route, you'll probably need to use CF's multi-buildpack support. This lets you run multiple buildpacks. If you pair this with the Apt buildpack, you can install the packages that you need so that any required libraries are available for your app as it's compiled.
https://docs.cloudfoundry.org/buildpacks/use-multiple-buildpacks.html
https://github.com/cloudfoundry/apt-buildpack
Using the binary buildpack is another option. In this case, you'd build your app locally. Perhaps in a docker container or on an Ubuntu VM (it needs to match the stack being used by your CF provider, i.e. cf stacks, currently Ubuntu Trusty or Ubuntu Bionic). Once you have a binary or binary + set of libraries, you can simply cf push the compiled artifacts. The binary buildpack will "run" (it actually does nothing) and then your app will be started with the command you specify.
My $0.02 only, but the binary buildpack is probably the easier of the two options.
what I am not able to understand how I can provide a startup script to a cloud foundry container or in brief how to achieve what I was doing with Dockers.
There's a few ways you can do this. The first is to specify a custom start command. You do this with cf push -c 'command'. This would normally be used to just start your app, like './my-app', but you could also use this to do other things.
Ex: cf push -c './prep-my-app.sh && ./my-app'
Or even just call your start script:
Ex: cf push -c './start-my-app.sh'.
CF also has support for a .profile script. This can be pushed with your app (at the root of the files you push), and it will be executed by the platform prior to your application starting up.
https://docs.cloudfoundry.org/devguide/deploy-apps/deploy-app.html#profile
Normally, you'd want to use a .profile script as you'd want to let the buildpack decide how to start your app (setting -c will override the buildpack), but in your case with the C or binary buildpack's, it's unlikely the buildpack will be able to do that, so you'll end up having to set a custom start command anyway.
For this specific case, I'd suggest using cf push -c as it's slightly easier, but for all other cases and apps deployed with other buildpacks, I'd suggest a .profile script.
Hope that helps!
Docker says "it possible to build, ship and run any app, anywhere"
Dockerising the app looks promising solution to ship and run any app, anywhere with less pain.
But how it's going to help us in building an application?
There are a few interesting use cases at build time for docker.
You could use docker to brink up database with known state inside containers for your integration tests to hit. using the Docker Maven Plugin.
Having a predefined container for your application which will not change during the development cycle is useful. Especially as you can use the same container when you go to prod deployments. This is different from say vagrant which you would not use for your production deployment.
Since there are so many docker containers already available your would not need to spend time figuring out how to deploy and mange all the various tools and services your deployment may need.