k8s-deployer | Deploy Kubernetes service and store retrieved information | DevOps library

by psyhomb Python Version: v0.1.3 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | k8s-deployer Summary

k8s-deployer is a Python library typically used in Devops, Ansible, Docker applications. k8s-deployer has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitLab, GitHub.

k8s-deployer HTTP API ===. About --- Deploy Kubernetes service and store retrieved information in the Consul K/V store. Installation --- ## Supervisor Install pew (python environment wrapper). Create required project dirs. Create a new virtualenv for k8s-deployer project. Enter virtualenv (previous commad will also enter virtualenv at the end). Copy and modify k8s-deployer configuration file. Copy and modify supervisor configuration file. Add and start service.

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Support

k8s-deployer has a low active ecosystem.

It has 23 star(s) with 4 fork(s). There are 5 watchers for this library.

It had no major release in the last 12 months.

k8s-deployer has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of k8s-deployer is v0.1.3

Quality

k8s-deployer has no bugs reported.

Security

k8s-deployer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

k8s-deployer is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

k8s-deployer releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed k8s-deployer and discovered the below as its top functions. This is intended to give you an instant insight into k8s-deployer implemented functionality, and help decide if they suit your requirements.

Delete an object
Make a request
Validate a JSON object
Scale a Kubernetes cluster
Create an object
Fetch a node from K8s API
Generate a template
Write JSON data to file
Load configuration from a file
Get a value from Consul
Read JSON from file
Delete key value pairs
Create a new key - value pair

Get all kandi verified functions for this library.

k8s-deployer Key Features

No Key Features are available at this moment for k8s-deployer.

k8s-deployer Examples and Code Snippets

No Code Snippets are available at this moment for k8s-deployer.

Community Discussions

Trending Discussions on k8s-deployer

Grant a pod access to create new Namespaces

QUESTION

Grant a pod access to create new Namespaces

Asked 2021-May-14 at 09:56

I'm trying to provision emepheral environments via automation leveraging Kubernetes namespaces. My automation workers deployed in Kubernetes must be able to create Namespaces. So far my experimentation with this led me nowhere. Which binding do I need to attach to the Service Account to allow it to control Namespaces? Or is my approach wrong?

My code so far:

deployment.yaml:

...

ANSWER

Answered 2021-May-14 at 09:56

To give a pod control over something in Kubernetes you need at least four things:

Create or select existing Role/ClusterRole (you picked administer-cluster, which rules are unknown to me).
Create or select existing ServiceAccount (you created k8s-deployer in namespace tooling).
Put the two together with RoleBinding/ClusterRoleBinding.
Assign the ServiceAccount to a pod.

Here's an example that can manage namespaces:

Source https://stackoverflow.com/questions/67532060

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install k8s-deployer

You can download it from GitLab, GitHub.
You can use k8s-deployer like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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