airship
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shipyard
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A cluster lifecycle orchestrator for Airship.
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This PS  adds default values for chart values and adds python code that
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      drydock_client_connect_timeout: 20
      drydock_client_read_timeout: 300
      promenade_client_connect_timeout: 20
      promenade_client_read_timeout: 300

Also adjusting timeout in shipyard_client requests usinf hardcoded values:

- connection timeout - 5 sec
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README.rst

Shipyard

Shipyard adopts the Falcon web framework and uses Apache Airflow as the backend engine to programmatically author, schedule and monitor workflows.

Find more documentation for Shipyard on Read the Docs.

The current workflow is as follows:

  1. Initial region/site data will be passed to Shipyard from either a human operator or Jenkins
  2. The data (in YAML format) will be sent to Deckhand for validation and storage
  3. Shipyard will make use of the post-processed data from DeckHand to interact with Drydock.
  4. Drydock will interact with Promenade to provision and deploy bare metal nodes using Ubuntu MAAS and a resilient Kubernetes cluster will be created at the end of the process
  5. Once the Kubernetes clusters are up and validated to be working properly, Shipyard will interact with Armada to deploy OpenStack using OpenStack Helm
  6. Once the OpenStack cluster is deployed, Shipyard will trigger a workflow to perform basic sanity health checks on the cluster

Note: This project, along with the tools used within are community-based and open sourced.

Mission

The goal for Shipyard is to provide a customizable framework for operators and developers alike. This framework will enable end-users to orchestrate and deploy a fully functional container-based Cloud.

Getting Started

This project is under development at the moment. We encourage anyone who is interested in Shipyard to review our documentation.

Bugs

If you find a bug, please feel free to create a Storyboard issue.