Universal-Kubernetes-Helm-Charts VS Packer

I would point you to what I call the "Universal Helm Charts" and some examples of how to use them.

Shameless Plug: Here's one of my dashboards I made for Ingress-Nginx, which is my recommended border router/gateway into all the services. It adds deep robust metrics and configurability, and if you've got years of experience with Nginx also, it allows you rich complex customization via nginx's configuration structure via kubernetes annotations. Besides that I have open-source helm charts which are easy to use, boilerplates showing how to use them, a volume autoscaler to automatically resize your disks as they get full, and a blog where I share various of my experience which is a companion blog to my upcoming book of the same name. Hope this helps! Feel free to ask if you have any further questions.

You may want to check out some other of my Helm Boilerplates to explain and highlight how using subcharts works. This is a companion repo to my upcoming DevOps + Kubernetes book. You also might like to check out my set of open-source universal helm charts which are published in a helm registry right now that you can leverage and has many industry best-practices built into it, such as anti-affinity rules, pod disruption budgets, horizontal pod autoscaling, ingress, service support, etc.

References: I use docker and Kubernetes daily. I currently manage numerous clusters and maintain pipelines for hundreds of microservices as I type this. I've been converting microservices into Docker images for companies hundreds if not thousands of times by now over the last bunches of years. I am also an avid and passionate open-source evangelist and Kubernetes/DevOps consultant. I author some Kubernetes controllers such as the Volume Autoscaler and have a set of Open Source Helm Charts and I love to contribute code/fixes wherever I run into issues.

If it helps at all I have some universal helm charts that have a template for easily deploying your application as a deployment or statefulset. You will notice I don’t even have a daemonset chart because it doesn’t make sense to. https://github.com/DevOps-Nirvana/Universal-Kubernetes-Helm-Charts

See: Open-Source Universal Helm Charts See: Boilerplates of using Open-Source Helm Charts (as a sub-chart)

Helm charts - https://github.com/DevOps-Nirvana/Universal-Kubernetes-Helm-Charts Example using helm charts as sub charts - https://github.com/DevOps-Nirvana/Helm-Chart-Boilerplates/tree/master/boilerplate-echoserver

A open-source set of Universal Helm Charts with tons of best-practices baked into it such as autoscaling, PDBs, labeling, and an standardized set of "universal" templates that allows you to pivot between templates easily (meaning, you can easily make a deployment into a Statefulset or a Cronjob). Yes, I need to add more documentation, I know. I'm busy :P

Universal Kubernetes Helm Charts

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.

Your assumption sounds correct. It sounds like you shouldn't focus on migrating specific instances, but instead migrating the template image used for autoscaling into GCP. I tend to prefer Packer for this job, or otherwise recreating the golden image directly on GCP.