Vercel CLI Deployment still accessing local environment variables - deployment

I've been having some issues with Vercel with regards to how it handles the environment variables. On my local machine, I have a .env.local file with some environment variables, along with a similar but slightly different set of environment variables in the Vercel UI.
 
Using the Vercel CLI, I first pull the environment variables from Vercel with vercel pull --environment=preview, build with vercel build, and then deploy with vercel --prebuilt.
 
For some reason, the deployed site still has access to some of the environment variables that were available locally but not available on the UI. Based on this discussion, it looks like Vercel shouldn't be reading the .env files for deployment, so I'm not sure what is happening. I've also tried adding .env.local to the .vercelignore but to no avail.
 
What is vercel build and vercel deploy doing under the hood that's causing this?

Related

How can I stop Vercel preview deployments from appearing on pull requests?

I use Vercel to deploy a Next.js app and I use Vercel for GitHub for CI/CD. Vercel automatically deploys code pushed to my master branch to production, and I would like to keep this functionality. However, Vercel also creates preview deployments for each push, and when I create a pull request, this deployment shows up under 'Checks.' Is there a way to stop this from happening? I don't have an issue with Vercel creating a preview deployment for each push I make, but I would like for Vercel's deployment not to appear under the 'Checks' section of each pull request.
You can use the "Ignore Build Step": https://vercel.com/support/articles/how-do-i-use-the-ignored-build-step-field-on-vercel
You can tell Vercel only to build master (or main depending on your git configuration), and all other branches will be ignored.
EDIT: Thanks to #Dani Akash for the suggestion below
Adding the following command in the ignored build step box of /settings/git page of your project to disable running the builds for non-production environments. Effectively disabling deploy previews
[ "$VERCEL_ENV" != production ]

Maintaining DJANGO_SETTINGS_MODULE between local and production environments

Running into an issue when we deployed to production, had to update manage.py to set os.environ.setdefault("DJANGO_SETTINGS_MODULE", "config.settings.local") to config.settings.production. Of course this broke local settings when we pulled back to our dev branch.
We're running our containers via the docker-compose local.yml commands recommended in the documentation.
Am I missing something? Is this by design?
This environment variable should be set via a .env file, the production one is located under .envs/.production/.django, and is not in source control (for security reasons). So yes, it is by design.
Depending on how you start your server, this file might be missing and the environment will end up unset.

Deploy my React project from Github to Netlify

Basically I have a .env file in the project, however it will be ignored when I commit by git regarding to .gitignore, which also makes it kind of disappear when Netlify deploys this project from GitHub. Then I have to manually set my environment variables on Netlify.
Are there any other ways to do this, so I don't have manually set the environment variables in Netlify and it will read my .env file?
Netlify supports environment variables, not through .env though. You'll need to configure these either through your dashboard or or in the netlify configuration file.
File
In the Netlify configuration file. File-based configuration allows you
to set different environment variables for different deploy contexts.
Variable values set in the configuration file will override values set
in the UI.
Dashboard
In your site dashboard under Settings > Build & deploy > Environment >
Environment variables. Variable values set under site settings will
override the team-level settings.

How to handle multiple environments with Google Cloud Build and Kubernetes

I'successfully set up a CICD pipeline following this tutorial.
It shows clearly how to make Google Cloud Build and Kubernetes work with one environment: production.
For simplicity, this tutorial uses a single environment —production—
in the env repository, but you can extend it to deploy to multiple
environments if needed.
Right, but some details are missing: is there one kubernetes.yaml file by environment? What about kubernetes namespaces?...
More precisely, what would be the way to handle multiple environments (staging...)?
There could be a bizillion ways of doing environments , but what I understand from this line:
env repository: contains the manifests for the Kubernetes Deployment
That the default master/production branch maps to the production environment , then you can create for example testing , and staging branches , where you test and stage your things , and later on port the change to master branch.
Infact if you keep reading that document , it will tell you something:
The env repository can have several branches that each map to a
specific environment (you only use production in this tutorial) and
reference a specific container image, whereas the app repository does
not.
One more thing , if you have access to gitlab and kubernetes , you can implement it without google GKE and clud build.

How to get bamboo use different config file on deployment depending on environment

I have different config files for each different deployment environments I have. Dev, QA and live are those environments.
How do i get bamboo to use the right config file for each environment when deploying?
So when deploying the dev environment bamboo use the dev config file and change name on it and put it on the right place.
I assume that artifacts can fix this? But how?
I solved it. I simply used artifacts and pointed directly to the file. Then in deploy i made a ps script for deploying the right artifact to the right deployment environment.
I also made the file changing depending on environment so i don't need separately config files.
Just hit me up if you are having the same problem, Atlassian documentation on this is terrible.