Kiyoshi's Blog

How Do I Manage My Development Environment

1/31/2023|Tech|4 min read

When I was using my old Dell XPS 15, I was confronted with the issue that the battery died so fast that the battery life could not last for more than 3 hours of programming. I knew there was something wrong with my laptop on its own, computation-intensive tasks and countless energy-inefficient apps, however, drained the battery fast.

To reiterate, I am facing the following issue:

  • Installing dev tools on my PC slows my PC down
  • Computation-intensive tasks kill my battery fast
  • If I break my dev env, I have to either do research for hours to fix a single trivial issue or reinstall everything

Therefore, if I send all the computation to the cloud and let servers handle that for me, my laptop can serve solely as a client with trivial tasks. In this way, additionally, my laptop is somewhat "stateless" since all my work "states" will be stored in the cloud.

Moreover, I can exploit the power of LXCs so that once I have any issue with the dev env itself, I can simply replace one container with another.

To make it clearer: I need a docker daemon running on a server, and to establish a secure connection between the docker client on my PC to the daemon. VSCode also has an extension to "attach to container" which makes this easier than ever.

Setup Docker Daemon

Install Docker Daemon

To get started, I installed Docker on my server following the official documentation and make docker engine accessible with non-root users following post-installation steps.

Access Docker Daemon Through HTTPS

To access the daemon from my PC, the docker daemon has to be reachable from the internet securely.

First, generate a set of certificates to protect the port that I am about to open for my docker daemon following this guide.

Configure The Daemon

A docker daemon is configured with /etc/docker/daemon.json. To enable the daemon for accessing through a TCP port, I have modified the file to be like this:

    "tlsverify": true,
    "tlscacert": "/path/to/ca.pem",
    "tlscert": "/path/to/server-cert.pem",
    "tlskey": "/path/to/server-key.pem",
    "hosts": [

Note: the port has to be opened!

Configure The Service

With the daemon configured, I can modify the options of dockerd at startup.

Debian manages services using systemd, and docker has its service definition file at /lib/systemd/system/docker.service:

# ...
ExecStart=/usr/bin/dockerd $DOCKER_OPTS
# ...

By configuring the startup options, now the daemon only relies on daemon.json instead of any other flags/options provided to the binary executable.

Restart the daemon to apply the changes:

systemctl daemon-reload
systemctl restart docker.service

Setup Docker Client

Install Docker Client

There are tons of ways of installing docker client or docker CLI (not docker desktop). The easiest way to do this is to find the most appropriate package from the most appropriate package manager on a system. On the other hand, the most general way to do this is to install the docker client with binaries directly, with the server/daemon removed to cause less trouble.

Configure Docker Client

Now, I have to establish the connection between my system and the server daemon. First, I have to make a directory for certificates that I generated before:

mkdir -p ~/.docker
cp {ca,cert,key}.pem ~/.docker

With certificates settled, let the client know where to connect:

# Replace $HOST with hostname to the server

Also, to make this a default behavior, simply append this line to .zshrc or any .rc file of the preferred shell.

To test the connection, run this:

docker version

With everything configured, start a container on the server and attach it using VSCode.

Bonus - Code Server and Jupyter

Code Server is such a nice project, so read this and try this. I also created a Dockerfile on top of this image to conveniently and constantly restart my container (just in case).

Now, I can develop on my iPad by installing the PWA which is a built-in feature of Code Server. It is also worth mentioning that Code Server cannot handle port-forwarding like how VSCode does due to the limitations of browsers; this is an issue when I want HMR when doing front-end stuff since HMR is implemented with WebSocket, which is problematic when I have everything protected with SSL. Some workarounds existed in the official repository, but workarounds are just not my flavor.

As for Jupyter, since I also work on scientific computations (implying ML, CV, DL, etc.), I do need it sometimes. Grab one of the images here, configure it with documentation aside, then reverse proxy it.


All my containers are managed using Docker Compose and all services are reverse proxied with my favorite web server which is also another container. LOL.

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