Kubernetes-Volume-Autoscaler VS sparrowci_web

Additionally if you don't know, Kubernetes freshly setup, especially AWS's EKS is largely useless after you first set it up. You need to then install roughly a dozen other services into it to make it "do all the magic automatically". Services such as aws-ebs-csi-driver, (optional) aws-efs-csi-driver, (optional) aws-fsx-csi-driver, aws-load-balancer-controller, (optional) aws-node-termination-handler, cluster-autoscaler, (optional) external-dns, logs cascading engine (eg: fluentd-elasticsearch / fluent-bit-elasticsearch / datadog), grafana, prometheus, your ingress controller of choice (I prefer and recommend ingress-nginx), and the Kubernetes Volume Autoscaler to auto-scale up EBS volumes. (shameless plug: I wrote the volume-autoscaler)

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.

Do not waste your timesetting up your own Kubernetes cluster; use any cloud provider's fully managed Kubernetes cluster, and then learn how to configure everything on it to do everything you want. Typically, there are anywhere between 10-30 foundational services you'll want to install on it to make everything work. Things such as Cluster-Autoscaler, an ingress controller, a mesh network technology, various CSI volume provisioners, a runner for your chosen CI/CD platform, a disk volume autoscaler (shameless plug I wrote this) etc. Learn to deploy Helm charts on it, and learn to deploy some of your services onto it, exposing them to the internet. Learn to install and use Prometheus and Grafana on it to get in-depth metrics and visualization. Learn how to use Prometheus Alertmanager to trigger alerts to your email, webhooks, slack, etc. There's a lot to learn, and it may feel intimidating, but get the ball rolling and incrementally improve/expand your experience.

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.

Old justifications for this were to resize drives but all major cloud providers support handling the resizing operation for you now. You still need to trigger the resize. But with a controller like the Kubernetes Volume Autoscaler you don’t even need to do that!

An new open-source Kubernetes controller, the Kubernetes Volume Autoscaler, which auto-resizes your Persistent Volumes when they get almost full

Kubernetes Volume Autoscaler - An Kubernetes Controller to automatically scale up volumes (disks). I just recently released an update based on some feedback, adding Prometheus metrics support and fixing a few bugs

Autoscale everything. There’s no over provisioning if it just provisions as needed. HPA and Cluster Autoscaler and for disks I wrote and use the Volume Autoscaler. Nodes disappear as needed and appear as needed. I generally even do spot instances in production. All assuming you are using a cloud provider.

Volume Autoscaler - Automatically scale up your disks size, keeping your costs low and allowing you to grow over time. Also making one less thing your sysops/devops person has to do. (Shameless plug, I wrote this)

I continue to build community around SparrowCI - https://ci.sparrowhub.io - flexible CI system with many languages support. Welcome in! We already have active uses , but we welcome 🤗 more.

With SparrowCI you have a compromise of having yaml based structure and flexibility to use many programming languages for tasks, and tasks act as functions accepting and returning parameters accessible within other tasks. You can check more out at https://ci.sparrowhub.io/

Continue to build super flexible CICD framework - https://ci.sparrowhub.io , recently I’ve added self hosted deployment support that allows people to install the system on their infrastructure. Another interesting feature is gitea integration

Checkout more on https://ci.sparrowhub.io

Keep building my own free CI service extendable by many languages including Python, please check out Python examples here - https://github.com/melezhik/SparrowCI/tree/main/examples/python

Now officially support builds for Alpine Linux, Debian and Arch Linux containers - see examples at https://ci.sparrowhub.io

For example, in SparrowCI pipeline this could be achieved by a simple Bash task:

For more sophisticated scenarios try out .sparkyci.yaml DSL

For more sophisticated scenarios there is .sparkyci.yaml DSL that allows to install none Raku packages, external services and so on, an example is my fork of DBIish::Pool repo - https://github.com/melezhik/DBIish-Pool/blob/main/.sparkyci.yaml