cheatsheets
helm
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cheatsheets | helm | |
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60 | 206 | |
5,596 | 26,045 | |
1.5% | 1.2% | |
7.6 | 8.9 | |
5 days ago | 3 days ago | |
TeX | Go | |
Creative Commons Attribution 4.0 | Apache License 2.0 |
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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.
cheatsheets
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Tools a Data Scientist should know:
If you're an R user, stringr + its cheatsheet gets you very close to remembering what to do without needing to look further!
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JSON to PDF Magic: Harnessing LaTeX and JSON for Effortless Customization and Dynamic PDF Generation
For more information on how to use ggplot2 and create charts consult the ggplot2 official page or the ggplot2 cheat graphic.
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Best packages to learn?
I'd suggest you have a look at cheatsheets (or download them from GitHub) if you want to get to know your way around a package or set if functions, it saves you a lot of time.
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How do I make these shapes (pictured below) in ggplot?
You could use geom_hline and geom_vline, geom_abline, or geom_segment for this. (The ggplot cheat sheet is very useful for answering these kinds of questions, BTW.)
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Why does my scatter plot look like this?
I can't say for sure because I don't know what your ultimate aim is for your visualization. Check out the cheat sheet for ggplot2 here.
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Import from Excel
Finally just do your analysis. You should also should give a try and see the cheat sheet for data importing on the tidyverse package.
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[Request] How to best visualize percentages with R?
That said, when I’m trying to come up with an interesting way to visualize data, I find the ggplot cheat sheet very helpful: https://github.com/rstudio/cheatsheets/raw/main/data-visualization-2.1.pdf
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Need help with variables
Here's a cheat sheet: https://github.com/rstudio/cheatsheets/blob/main/strings.pdf
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Data manipulation in R
The cheat sheet of the stringr package should give you good overview of string manipulation/ regex in R.
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I'm trying to recreate this plot but I keep failing
I would very highly recommend that rather than trying to get started by translating an existing graph, you check out some documentation about ggplot first. If nothing else, the ggplot cheat sheet from RStudio should help explain what the component parts of the code are, and that might help you figure out what you actually want to do.
helm
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Kubernetes CI/CD Pipelines
Applying Kubernetes manifests individually is problematic because files can get overlooked. Packaging your applications as Helm charts lets you version your manifests and easily repeat deployments into different environments. Helm tracks the state of each deployment as a "release" in your cluster.
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deploying a minio service to kubernetes
helm
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How to take down production with a single Helm command
Explanation here: https://github.com/helm/helm/issues/12681#issuecomment-19593...
Looks like it's a bug in Helm, but actually isn't Helm's fault, the issue was introduced by Fedora Linux.
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Building a VoIP Network with Routr on DigitalOcean Kubernetes: Part I
Helm (Get from here https://helm.sh/)
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The 2024 Web Hosting Report
It’s also well understood that having a k8s cluster is not enough to make developers able to host their services - you need a devops team to work with them, using tools like delivery pipelines, Helm, kustomize, infra as code, service mesh, ingress, secrets management, key management - the list goes on! Developer Portals like Backstage, Port and Cortex have started to emerge to help manage some of this complexity.
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Deploying a Web Service on a Cloud VPS Using Kubernetes MicroK8s: A Comprehensive Guide
Kubernetes orchestrates deployments and manages resources through yaml configuration files. While Kubernetes supports a wide array of resources and configurations, our aim in this tutorial is to maintain simplicity. For the sake of clarity and ease of understanding, we will use yaml configurations with hardcoded values. This method simplifies the learning process but isn’t ideal for production environments due to the need for manual updates with each new deployment. Although there are methods to streamline and automate this process, such as using Helm charts or bash scripts, we’ll not delve into those techniques to keep the tutorial manageable and avoid fatigue — you might be quite tired by that point!
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Deploy Kubernetes in Minutes: Effortless Infrastructure Creation and Application Deployment with Cluster.dev and Helm Charts
Helm is a package manager that automates Kubernetes applications' creation, packaging, configuration, and deployment by combining your configuration files into a single reusable package. This eliminates the requirement to create the mentioned Kubernetes resources by ourselves since they have been implemented within the Helm chart. All we need to do is configure it as needed to match our requirements. From the public Helm chart repository, we can get the charts for common software packages like Consul, Jenkins SonarQube, etc. We can also create our own Helm charts for our custom applications so that we don’t need to repeat ourselves and simplify deployments.
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Kubernets Helm Chart
We can search for charts https://helm.sh/ . Charts can be pulled(downloaded) and optionally unpacked(untar).
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Introduction to Helm: Comparison to its less-scary cousin APT
Generally I felt as if I was diving in the deepest of waters without the correct equipement and that was horrifying. Unfortunately to me, I had to dive even deeper before getting equiped with tools like ArgoCD, and k8slens. I had to start working with... HELM.
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🎀 Five tools to make your K8s experience more enjoyable 🎀
Within the architecture of Cyclops, a central component is the Helm engine. Helm is very popular within the Kubernetes community; chances are you have already run into it. The popularity of Helm plays to Cyclops's strength because of its straightforward integration.
What are some alternatives?
tidytuesday - Official repo for the #tidytuesday project
crossplane - The Cloud Native Control Plane
forcats - 🐈🐈🐈🐈: tools for working with categorical variables (factors)
kubespray - Deploy a Production Ready Kubernetes Cluster
mostly-adequate-guide - Mostly adequate guide to FP (in javascript)
Packer - Packer is a tool for creating identical machine images for multiple platforms from a single source configuration.
ggplot2-book - ggplot2: elegant graphics for data analysis
krew - 📦 Find and install kubectl plugins
mech - 🦾 Main repository for the Mech programming language. Start here!
skaffold - Easy and Repeatable Kubernetes Development
ggplot2 - An implementation of the Grammar of Graphics in R
dapr-demo - Distributed application runtime demo with ASP.NET Core, Apache Kafka and Redis on Kubernetes cluster.