berglas
kind
berglas | kind | |
---|---|---|
37 | 183 | |
1,224 | 12,797 | |
0.1% | 1.0% | |
6.9 | 8.9 | |
6 days ago | 5 days ago | |
Go | Go | |
Apache 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.
berglas
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How to deploy a Django app to Google Cloud Run using Terraform
Secret Manager: secure storage for sensitive data e.g passwords.
- How do you handle sensitive variables with a service-worker?
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Increasing Your Cloud Function Development Velocity Using Dynamically Loading Python Classes
Google Secret Manager
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Getting started using Google APIs: API Keys (Part 2)
API keys are easy to "leak" or compromise, so best to not only use the restrictions presented to you when you create them but physically protect them as well. Don't code them in plain-text, don't check them into GitHub, etc. Store them in a secure database or use a service like GCP Secret Manager.
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Need some advice on API key storage
I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights.
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Secure GitHub Actions by pull_request_target
In this post, I described how to build secure GitHub Actions workflows by pull_request_target event instead of pull_request event. Using pull_request_target, you can prevent malicious codes from being executed in CI. And by managing secrets in secrets management services such as AWS Secrets Manager and Google Secret Manager and access them via OIDC, you can restrict the access to secrets securely. To migrate pull_request to pull_request_target, several modifications are needed. And pull_request_target has a drawback that it's difficult to test changes of workflows, so it's good to introduce pull_request_target to repositories that require strong permissions in CI. For example, a Terraform Monorepo tends to require strong permissions for CI, so it's good to introduce pull_request_target to it.
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Need Help with Deploying Directus on Google Cloud Platform (GCP)
If you want to make these secrets more secure and get versioning and access logs for them, you may want to switch to Secret Manager later on. They can still be exposed as environment variables to your code. It's a little more setup work, so start with the simple approach at the top.
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Has anyone been able to implement the OpenAI API with a Firebase Function (which is needed for the env variable API Key)?
https://cloud.google.com/secret-manager https://aws.amazon.com/secrets-manager/
- Securely storing Social Security Numbers with Firebase?
- Dónde van las credenciales cuando voy a subir un código a la nube para correr 24/7?
kind
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Take a look at traefik, even if you don't use containers
Have you tried https://kind.sigs.k8s.io/? If so, how does it compare to k3s for testing?
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How to distribute workloads using Open Cluster Management
To get started, you'll need to install clusteradm and kubectl and start up three Kubernetes clusters. To simplify cluster administration, this article starts up three kind clusters with the following names and purposes:
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15 Options To Build A Kubernetes Playground (with Pros and Cons)
Kind: is a tool for running local Kubernetes clusters using Docker container "nodes." It was primarily designed for testing Kubernetes itself but can also be used for local development or continuous integration.
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Exploring OpenShift with CRC
Fortunately, just as projects like kind and Minikube enable developers to spin up a local Kubernetes environment in no time, CRC, also known as OpenShift Local and a recursive acronym for "CRC - Runs Containers", offers developers a local OpenShift environment by means of a pre-configured VM similar to how Minikube works under the hood.
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K3s Traefik Ingress - configured for your homelab!
I recently purchased a used Lenovo M900 Think Centre (i7 with 32GB RAM) from eBay to expand my mini-homelab, which was just a single Synology DS218+ plugged into my ISP's router (yuck!). Since I've been spending a big chunk of time at work playing around with Kubernetes, I figured that I'd put my skills to the test and run a k3s node on the new server. While I was familiar with k3s before starting this project, I'd never actually run it before, opting for tools like kind (and minikube before that) to run small test clusters for my local development work.
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Mykube - simple cli for single node K8S creatiom
Features compared to https://kind.sigs.k8s.io/
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Hacking in kind (Kubernetes in Docker)
Kind allows you to run a Kubernetes cluster inside Docker. This is incredibly useful for developing Helm charts, Operators, or even just testing out different k8s features in a safe way.
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Choosing the Next Step: Docker Swarm or Kubernetes After Mastering Docker?
Check out KinD
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K3s – Lightweight Kubernetes
If you're just messing around, just use kind (https://kind.sigs.k8s.io) or minikube if you want VMs (https://minikube.sigs.k8s.io). Both work on ARM-based platforms.
You can also use k3s; it's hella easy to get started with and it works great.
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Two approaches to make your APIs more secure
We'll install APIClarity into a Kubernetes cluster to test our API documentation. We're using a Kind cluster for demonstration purposes. Of course, if you have another Kubernetes cluster up and running elsewhere, all steps also work there.
What are some alternatives?
kubernetes-external-secrets - Integrate external secret management systems with Kubernetes
minikube - Run Kubernetes locally
helm-charts
k3d - Little helper to run CNCF's k3s in Docker
kube-secrets-init - Kubernetes mutating webhook for `secrets-init` injection
lima - Linux virtual machines, with a focus on running containers
gitleaks - Protect and discover secrets using Gitleaks 🔑
vcluster - vCluster - Create fully functional virtual Kubernetes clusters - Each vcluster runs inside a namespace of the underlying k8s cluster. It's cheaper than creating separate full-blown clusters and it offers better multi-tenancy and isolation than regular namespaces.
cocert - Split and distribute your private keys securely amongst untrusted network
colima - Container runtimes on macOS (and Linux) with minimal setup
secrets-store-csi-driver-provider-gcp - Google Secret Manager provider for the Secret Store CSI Driver.
nerdctl - contaiNERD CTL - Docker-compatible CLI for containerd, with support for Compose, Rootless, eStargz, OCIcrypt, IPFS, ...