multi-env-deploy VS distroless

I have used CodePipeline/CodeBuild, CodeDeploy, and CodeCommit quite a bit. You can see an example of it all working together with Terraform here: https://github.com/cogini/multi-env-deploy

Parameter Store is a good place to store things. ECS can read from it and set variables. This is a complete example of using Terraform to manage infrastructure with EC2 or ECS: https://github.com/cogini/multi-env-deploy Here is an app that runs in ECS: https://github.com/cogini/phoenix_container_example This task file sets env vars based on parameter store: https://github.com/cogini/phoenix_container_example/blob/master/ecs/taskdef.json

AWS has a fine stack for deploying "cloud native" apps on top of EC2 instances.

Build a base AMI using Packer and launch it to an Auto Scaling Group behind a load balancer. Deploy code to the ASG using CodeDeploy. Use RDS for the database.

This is a good match for languages that have good concurrency like Elixir. They benefit from deploying to big machines that have a lot of CPU cores, and keeping a common in-memory cache on the EC2 instance is more efficient than using an external cache like Elasticache. It also works well for resource-hungry systems with poor concurrency like Ruby on Rails. Putting these kinds of apps into big containers is just a waste of money.

Here is a complete example of that architecture using Terraform: https://github.com/cogini/multi-env-deploy

Similarly, bare metal can be really cost-effective. For $115/month, I can get a dedicated server with 24 VCPU cores (2x Intel Hexa-Core Xeon E5-2620 CPU), 64 GB RAM, 4x8 TB SATA, 30 TB traffic (see https://www.leaseweb.com/dedicated-servers#NL). That would be an order of magnitude more expensive on AWS with containers.

Here is how I did it with Terraform: https://github.com/cogini/multi-env-deploy/blob/master/terraform/modules/iam-codepipeline-app/main.tf

The AWS components are managed via Terraform: https://github.com/cogini/multi-env-deploy

A fully featured infrastructure using terraform with terragrunt can be found in this repo: https://github.com/cogini/multi-env-deploy/tree/master/terraform

You might like this full-featured example of using Terraform to set up the infrastructure for an application using EC2 instances in an autoscaling group or ECS containers. https://github.com/cogini/multi-env-deploy

Here is a set of hand-coded modules I wrote that handle deploying real world complex apps to AWS: https://github.com/cogini/multi-env-deploy

lots of questions here regarding what this product is. I guess i can provide some information for the context, from a perspective of an outside contributor.

Chainguard Images is a set of hardened container images.

They were built by the original team that brought you Google's Distroless (https://github.com/GoogleContainerTools/distroless)

However, there were few problems with Distroless:

1. distroless were based on Debian - which in turn, limited to Debian's release cadence for fixing CVE.

2. distroless is using bazelbuild, which is not exactly easy to contrib, customize, etc...

3. distroless images are hard to extend.

Chainguard built a new "undistro" OS for container workload, named Wolfi, using their OSS projects like melange (for packaging pkgs) and apko (for building images).

The idea is (from my understanding) is that

1. You don't have to rely on upstream to cut a release. Chainguard will be doing that, with lots of automation & guardrails in placed. This allow them to fix vulnerabilties extremely fast.

> If you have one image based on Ubuntu in your stack, you may as well base them all on Ubuntu, because you only need to download (and store!) the common base image once

This is only true if your infrastructure is static. If your infrastructure is highly elastic, image size has an impact on your time to scale up.

Of course, there are better choices than Alpine to optimize image size. Distroless (https://github.com/GoogleContainerTools/distroless) is a good example.

The same as our code dependencies, container updates can include security patches and bug fixes and improvements. However, they can also include breaking changes and it is crucial you test them thoroughly before putting them into production. Wherever possible, I recommend using the distroless base image which will drastically reduce both your image size, your risk vector, and therefore your maintenance version going forward.

# Use a large Node.js base image to build the application and name it "build" FROM node:18-alpine as build WORKDIR /app # Copy the package.json and package-lock.json files into the working directory before copying the rest of the files # This will cache the dependencies and speed up subsequent builds if the dependencies don't change COPY package*.json /app # You might want to use yarn or pnpm instead RUN npm install COPY . /app RUN npm run build # Instead of using a node:18-alpine image, we are using a distroless image. These are provided by google: https://github.com/GoogleContainerTools/distroless FROM gcr.io/distroless/nodejs:18 as prod WORKDIR /app # Copy the built application from the "build" image into the "prod" image COPY --from=build /app/.output /app/.output # Since this image only contains node.js, we do not need to specify the node command and simply pass the path to the index.mjs file! CMD ["/app/.output/server/index.mjs"]

Lots of examples without the entire OS as other comments mention, an example would be Googles distroless[0]

[0]: https://github.com/GoogleContainerTools/distroless

Docker doesn't do this all the time. Distroless Docker containers are relatively common. https://github.com/GoogleContainerTools/distroless

Deployment: https://github.com/GoogleContainerTools/distroless

Or use distroless image as it includes one, among others. https://github.com/GoogleContainerTools/distroless/blob/main/base/README.md