Developing with Docker (danielquinn.org)

submitted 1 month ago* (last edited 1 month ago) by danielquinn@lemmy.ca to c/python@programming.dev

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I've been writing code professionally for 24 years, 15 of which has been Python and 9 years of that with Docker. I got tired of running into the same complications every time I started a new job, so I wrote this. Maybe you'll find it useful, or it could even start a conversation, but this post has been a long time coming.

Update: I had a few requests for a demo repo as a companion to this post, so I wrote one today. It includes a very small Django demo user Docker, Compose, and GitLab CI.

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[-] jacksilver@lemmy.world 8 points 1 month ago

Hey OP, it looks like you're the author of the post? If so I'm curious how you handle cloud services like AWS or Azure when taking this approach? One of the major issues I've run into when working with teams is how to test or evaluate against cloud services without creating an entire infrastructure in the cloud for testing.

[-] danielquinn@lemmy.ca 9 points 1 month ago

It's a tough one, but there are a few options.

For AWS, my favourite one is LocalStack, a Docker image that you can stand up like any other service and then tell it to emulate common AWS services: S3, Lamda, etc. They claim to support 80 different services which is... nuts. They've got a strange licensing model though, which last time I used it meant that they support some of the more common services for free, but if you want more you gotta pay... and they aren't cheap. I don't know if anything like this exists for Azure.

The next-best choice is to use a stand-in. Many cloud services are just managed+branded Free software projects. RDS is either PostgreSQL or MySQL, ElastiCache is just Redis, etc. For these, you can just stand up a copy of the actual service and since the APIs are identical, you should be fine. Where it gets tricky is when the cloud provider has messed with the API or added functionality that doesn't exist elsewhere. SQS for example is kind of like RabbitMQ but not.

In those cases, it's a question of how your application interacts with this service. If it's by way of an external package (say Celery to SQS for example), then using RabbitMQ locally and SQS in production is probably fine because it's Celery that's managing the distinction and not you. They've done the work of testing compatibility, so theoretically you don't have to.

If however your application is the kind of thing that interacts with this service on a low level, opening a direct connection and speaking its protocol yourself, that's probably not a good idea.

That leaves the third option, which isn't great, but I've done it and it's not so bad: use the cloud service in development. Normally this is done by having separate services spun up per user or even with a role account. When your app writes to an S3 bucket locally, it's actually writing to a real bucket called companyname-username-projectbucket. With tools like Terraform, the fiddly process of setting all this up can be drastically simplified, so it's not so bad -- just make sure that the developers are aware of the fact that their actions can incur costs is all.

If none of the above are suitable, then it's probably time to stub out the service and then rely more heavily on a QA or staging environment that's better reflective of production.