Metadata-Version: 2.1
Name: wielder
Version: 0.2.1
Summary: A reactive debuggable CI-CD & orchestration management tool for local & cloud deployments e.g. kubernetes, airflow & data lakes
Home-page: https://github.com/hamshif/Wielder.git
Author: Hamshif
Author-email: hamshif@gmail.com
License: Apache License Version 2.0
Download-URL: https://github.com/hamshif/Wielder/archive/v0.2.1-beta.tar.gz
Keywords: CI-CD,Kubernetes,Reactive
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Requires-Dist: Cython
Requires-Dist: gitpython
Requires-Dist: pyyaml
Requires-Dist: kubernetes
Requires-Dist: rx
Requires-Dist: jprops
Requires-Dist: pyhocon
Requires-Dist: requests


Wielder
=

<h2> 
One Lib to rule them all,<br>
One Lib to find them,<br>
One Lib to bring them all<br>  
and in the darkness bind them.  
</h2>

Reactive debuggable CI-CD
-

Kubernetes polymorphic plan apply (A reactive debuggable alternative to Helm declarative charts)

Reactive deployments, canaries, updates, scaling and rollbacks.

Wielder wields Git, Docker, Terraform, Kubernetes, Airflow, ETLs & more into reactive debuggable event sequences; 
to guide code from development through testing to production. 

* Functionality:
    * Kubernetes polymorphic plan apply (A reactive debuggable alternative to Helm declarative charts)
    * Packing code to docker containers and repositories (A reactive debuggable alternative to Jenkins, Travis etc..).
    * Weaving Terraform and Kubernetes events into reactive, debuggable elastic scaling mechanisms. 
    * Automation of local development in Intellij and Kubernetes.
    * One stop shop for CLI and configuration, using Hocon a superset of JSON, YAML integration with Terraform.
* Examples:
    * Waiting for Zookeeper to come online before deploying or scaling Kafka nodes.
    * Waiting for Redis sentinels to find a master and come online before deploying another slave.
    * Provisioning additional cluster nodes and volumes with terraform before scaling a Cassandra stateful set.
    * Scheduled provisioning of hadoop clusters -> Running ETL's -> Deprovisioning the clusters
    * Listening to Kubernetes service throughput -> provisioning infrastructure scaling with terraform -> provisioning kubernetes node scaling.
    * Use of the same infrastructure as code to develop locally and on deploy to the cloud.


CI-CD
-

* Functionality:
    * Facilitates creating images tailored to all environments from code base.
        * Local feature branches
        * Cloud feature branches
        * Integration
        * QE
        * Stage
        * Production
        * Pushing images to repository.


Use Instructions
-
To learn how to run read PYTHON.md

