wielder 0.2.7

A reactive debuggable CI-CD & orchestration management tool for local & cloud deployments e.g. kubernetes, airflow & data lakes

Wielder

One Lib to rule them all,
One Lib to find them,
One Lib to bring them all
and in the darkness bind them.

Reactive debuggable CI-CD

Wielder is meant to unify the best technologies for the job. You decide, pick and choose (fastest, cheapest, legacy...). We do this by wrapping the technology in python and then treating it as a black-box with callbacks For example:

• Kubernetes polymorphic plan apply (A reactive debuggable alternative to Helm declarative charts & SDK dependant Go Operators)

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