deploy-cloudrun VS Packer

Examples for products in this category are: Google Cloud Run, AWS App Runner, Azure Container Apps. Each has different scalability, cost, and integration trade-offs.

Cloud Run is a managed platform that enables you to run container based workloads on top of Google infrastructure. Cloud Run automates many of the above steps and allows you to focus on developing and deploying updates to your application.

Serverless computing was also introduced, where the developers focus on their code instead of server configuration.Google offers serverless technologies that include Cloud Functions and Cloud Run.Cloud Functions manages event-driven code and offers a pay-as-you-go service, while Cloud Run allows clients to deploy their containerized microservice applications in a managed environment.

The quickest way is to deploy to Cloud Run. The service will use Dockerfile to build the production image. You can even omit the GOOGLE_APPLICATION_CREDENTIALS env var as these are in GCP’s projects by default.

In our company we use Google Cloud Run to deploy web applications, and every app is built into a docker image. For now we use the default memory limit by Cloud Run which is 256 MB per container. Recently we started to notice that the part of applications go beyond this limit, causing a container to restart and in some cases even resulting to downtime of a service.

It's perhaps a little fiddlier than other options, but you can probably host it on Google Cloud Run and it would fall within the free tier.

You can see more here on how to use the google cloud run github actions.

I wonder what the aversion is to using a plain old server / vps. It's really not that difficult to deploy nowadays [0][1][2][3] and I'd rather get an $8 bill every month as insurance than ever worry about shit like OP just went through. It'll probably be more performant anyway due to cold starts and "edge" still having to hit us-east-1 for data.. cache your static files with Cloud Flare/Front. People are always surprised by how much traffic a single VPS can take[4] and believe it all has to be serverless to be web scale. I believe HN still runs on a single core or something.

There's a ton of places to get cloud credits as well, too many to link, so just Bing™ it

[0] https://docs.aws.amazon.com/cdk/api/v2/docs/aws-cdk-lib.aws_...

[1] https://aws.amazon.com/apprunner/

[2] https://cloud.google.com/run

[3] https://render.com/

[4] https://news.ycombinator.com/item?id=34676186

Google Cloud Run

The missing piece of puzzle is the AMI "golden image" that will be used to start the instances in autoscaling group. The AMI has to have NGINX and PHP installed with the list of required modules enabled. The great tool to brew one is hashicorp packer.

To manage a VM, you can use something as simple as just manual actions over SSH, or can use tools like Ansible, Hashicorp's Packer and Terraform or other automations. For an app where there is minimal load and security/reliability concern, VMs are still a great option that provide a lot of value for the buck

Server templating: Using Packer has never been easier to create reusable server configurations in a platform-independent and documented manner.

I'll give you hard, but rewarding and easy to modify(once you know what you're doing) way. Packer may be a thing you're looking for.

It is straightforward to build them with packer (I have built AMIs for 13.0 and 13.1, but 13.2 should be exactly the same). I've been meaning to write a blog post about it for a while, but have not gotten to it yet... In any case, what I am doing is using the EBS Surrogate Builder to start an instance running the official FreeBSD 13.2 image with an extra volume attached and run a script to create a zpool on the extra volume and bootstrap and configure FreeBSD 13.2-RELEASE on it. After that packer takes care of creating an AMI out of that extra volume, so you can use it... If you have any issues, let me know, and maybe I will finally get to writing that blog post...

HashiCorp Packer is a tool for creating machine images for a variety of platforms, including AWS, Azure, and VMware. It allows you to define machine images as code and supports a wide range of configuration options.

Packer is a tool that can be used to build machine images. Basically, it takes a base image, runs a series of steps to provision that image, and then burns a new image. In my workplace we use it heavily to build AWS AMIs. But it has an ARM plugin that looks to be very very suitable for building customised Raspberry Pi images (my quick read of the doco there says it can go ahead and write the final image to an SD card for you too).

Seems related to https://github.com/hashicorp/packer/issues/12118 But the workaround discribed in the comments doesn’t seems to work anymore

I'd suggest using a tool like Packer to build a gold image based on your base AMI and all your changes. Then you'll have your own AMI you can launch new instances with.