SparrowCI
Kubernetes-Volume-Autoscaler
Our great sponsors
SparrowCI | Kubernetes-Volume-Autoscaler | |
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8 | 16 | |
12 | 245 | |
- | 2.4% | |
7.8 | 7.1 | |
4 months ago | 6 months ago | |
Raku | Python | |
Artistic License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SparrowCI
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Best CI Service for Use with Gitea?
Self-hosted SparrowCI supports GitTea integration - https://github.com/melezhik/SparrowCI/blob/main/reporters/gitea.yaml , now it’s just sending back commit statues ( after CI build finished ) , but let me know if you need anything else. I tested it on my self-hosted installation and it works well.
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Dynamic CI pipelines with SparrowCI - Alexey Melezhik
Hi! Thanks for asking. If you mean SparrowCI pipelines then this is - https://github.com/melezhik/SparrowCI
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Ask HN: Which CI/CD do you use for a monorepo?
You can try out SparrowCI (https://github.com/melezhik/SparrowCI) -it’s simple and could be self-hosted. It builds on docker images, so if you spin up an SparrowCI on arm64 host you should be probably good. It’s not possible to have 3 separate CI pipelines but you can organize repo pipeline in such a way that it’s split by 3 or many tasks to cover different parts of your system.
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Sunday Daily Thread: What's everyone working on this week?
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
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5 min introduction to goyek v2 - a library for creating build automation in Go
This is neat, guys! I've recently created a similar tool - https://github.com/melezhik/SparrowCI/blob/main/go_support.md , but maybe with a bit different approach, however maybe our tools could be integrated somehow ?
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Monthly 'Shameless Self Promotion' thread - 2022/11
That makes SparrowCI extremely flexible CICD system in comparison with existing solutions (GitHub Actions, Ado Pipelines, GitLab, CircleCI ). The service runs for free now. Try it out! Some examples for popular languages (Python/Ruby/Powershell,Bash,GoLang) could be found here - https://github.com/melezhik/SparrowCI/tree/main/examples
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Need feedback on CICD for Ruby
More examples for Ruby could be found here - https://github.com/melezhik/SparrowCI/tree/main/examples/ruby
- Monthly 'Shameless Self Promotion' thread - 2022/10
Kubernetes-Volume-Autoscaler
- Toyota blames factory shutdown in Japan on ‘insufficient disk space’
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[AWS] EKS vs Self managed HA k3s running on 1x2 ec2 machines, for medium production workload
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)
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Monitoring many cluster k8s
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.
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QUESTION: What is the best way to learn kubernetes?
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.
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How do you guys on Mac M1's get around the annoying port forwarding issues with k8s + docker?
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.
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Accessing the Underlying Node
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!
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Monthly 'Shameless Self Promotion' thread - 2023/01
An new open-source Kubernetes controller, the Kubernetes Volume Autoscaler, which auto-resizes your Persistent Volumes when they get almost full
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Monthly 'Shameless Self Promotion' thread - 2022/11
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
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How do you prevent overprovisioning
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.
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What are some must-have, can’t-live-without 3rd party apps/tools you have installed in your k8s clusters?
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)
What are some alternatives?
PoC_CVEs - PoC_CVEs
pvc-autoresizer - Auto-resize PersistentVolumeClaim objects based on Prometheus metrics
kcl - KCL Programming Language (CNCF Sandbox Project). https://kcl-lang.io
Grafana-Dashboards - A variety of open-source Grafana dashboards typically for AWS and Kubernetes
Cromtit - Run Tomtit scenarios as cron jobs and more.
autoscaler - Autoscaling components for Kubernetes
vscode-kcl - VS Code KCL Extension
Helm-Chart-Boilerplates - Example implementations of the universal helm charts
personal-server - Personal server configuration with k3s
sparrowci_web - ci.sparrowhub.io website
korm - KORM, an elegant and lightning-fast ORM for all your concurrent and async needs. Inspired by the highly popular Django Framework, KORM offers similar functionality with the added bonus of performance
win2s3 - Windows to S3 Backup, Restore, Point in Time, and File Permissions