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Mid.CBF MCS

Documentation on the Developer's portal: ReadTheDoc

Table Of Contents

Introduction

The Mid CBF MCS prototype implements at the moment these TANGO device classes:

  • CbfController: Based on the SKAMaster class. It represents a primary point of contact for CBF Monitor and Control. It implements CBF state and mode indicators and a set of housekeeping commands.

  • CbfSubarray: Based on the SKASubarray class. It implements commands needed for scan configuration.

  • Vcc and Fsp: Based on the SKACapability and CspSubelementObsDevice classes, respectfully. These implement commands and attributes needed for scan configuration.

  • Vcc and Fsp Capabilities: Based on the SKACapability class. These implement state machines to enable/disable certain VCC and FSP functionality for a scan.

    • VccBand1And2, VccBand3, VccBand4, and VccBand5 specify the operative frequency band of a VCC.
    • VccSearchWindow defines a search window for a VCC.
    • FspCorr, FspPss, FspPst, and FspVlbi specify the function mode of an FSP.
    • FspCorrSubarray, FspPssSubarray and FspPssSubarray: Based on the SKASubarray class. It implements commands and attributes needed for scan configuration.

  • TmCspSubarrayLeafNodeTest: Based on the SKABaseDevice class. It simulates a TM CSP Subarray Leaf Node, providing regular updates to parameters during scans using a publish-subscribe mechanism.

To cut down on the number of TANGO device servers, some multi-class servers are implemented to run devices of different classes:

  • VccMulti: Runs a single instance of Vcc, one instance each of the VCC frequency band capabilities, and two instances of VccSearchWindow.
  • FspMulti: Runs a single instance of Fsp, one instance each of the FSP function mode capabilities, and 4 instances each of FspCorrSubarray, FspPssSubarray and FspPssSubarray.

At the moment, the device servers implemented are:

  • 1 instance of CbfController.
  • 3 instance of CbfSubarray.
  • 4 instances of FspMulti.
  • 4 instances of VccMulti.
  • 2 instances of TmCspSubarrayLeafNodeTest.

Getting started

This section follows the instructions on the SKA developer’s portal:

Hardware and OS requirements

The following settings are needed for the virtual machine, running on a Windows 10 host:

  • 4 CPUs
  • 8 GB RAM (ideally more, maximum that VirtualBox recommends)
  • ~40 GB storage

Install a virtual machine

Download and install VirtualBox and the extension pack from: https://www.virtualbox.org/wiki/Downloads

Install Ubuntu

Download an image of Ubuntu 18.04 like the following one:

https://sourceforge.net/projects/osboxes/files/v/vb/55-U-u/18.04/18.04.2/18042.64.7z/download

Steps:

  1. Open up the file downloaded from SourceForge for the Ubuntu image with 7-Zip and extract the “Ubuntu 18.04.2 (64bit).vdi” file into a known directory.

  2. Open up the VirtualBox software and click “new” and run through the setup process, on the Hard Disk option screen choose “use and existing virtual hard disk file” and then choose the VDI file that you extracted in step two.

  3. Run the OS in VirtualBox and login to the Ubuntu OS. The login screen should show the account osboxes.org; this is a default account the virtual machine creates for you and the password is osboxes.org (you can change the name and password in account settings once you are logged in”).

Note : If you set your own password for the virtual machine, change "ansible_become_pass=osboxes.org" to "ansible_become_pass=your_own_password"

Set up development environment

DEPRECATION NOTICE

ansible-playbooks repository no longer supported, however it is still useful to set up a new development environment.

Setting up the Development environment, including Tango environment, is performed using the ansible playbook script. Follow the commands in the yellow box under the 'Creating a Development Environment' section of the https://developer.skatelescope.org/en/latest/getting-started/devenv-setup/tango-devenv-setup.html web page.

sudo apt -y install git
git clone https://gitlab.com/ska-telescope/ansible-playbooks
cd ansible-playbooks
sudo apt-add-repository --yes --update ppa:ansible/ansible && \
    sudo apt -y install ansible
ansible-playbook -i hosts deploy_tangoenv.yml \
    --extra-vars "ansible_become_pass=osboxes.org" \
    -e ansible_python_interpreter=/usr/bin/python
sudo reboot

See that page for a list of the applications installed in this way.

Notes and troubleshooting

Note 1: If you already have an older installation don't forget to first update your local version of the ansible-playbooks repo (pull, checkout or delete and clone again), before running the ansible-playbooks command.

Note 2: You may need to precede the ansible-playbook command (from the commands sequence at the link above) by sudo.

Note 3: Depending on your system, the ansible-playbook command may take more than one hour to complete.

Note 4: If you encounter Python installation problem with the ansible command, try to explicitly specify the python version in the ansible command, for example:

ansible-playbook -i hosts deploy_tangoenv.yml --extra-vars "ansible_become_pass=osboxes.org" -e ansible_python_interpreter=/usr/bin/python3

Note 5: If you experience other issues with the script ask questions in the #team-system-support slack channel.

Set up the Mid CBF MCS Software

The basic requirements are:

  • Python 3.5
  • pip

The following projects are required:

  • ska-mid-cbf-mcs
  • ska-tango-base

To get a local copy of the ska-mid-cbf-mcs project:

git clone https://gitlab.com/ska-telescope/ska-mid-cbf-mcs.git  # clone the MCS 
repository locally

To install ska-tango-base (as a Python package), follow the 'Installation steps' of the README at https://gitlab.com/ska-telescope/ska-tango-base

Note:SKA Tango base classes are needed when using Pogo to automatically generate Python TANGO code. Pogo will ask for the Base class pogo (.xmi) files, which are located in the ska-tango-base folder.

Set up Kubernetes

For installing Kubernetes, Minikube and Helm, follow the instructions at https://developer.skatelescope.org/en/latest/tools/dev-faq.html.

Individual installation instructions

  • Docker Engine
  • minikube, kubectl and Helm
    • Clone the https://gitlab.com/ska-telescope/sdi/ska-cicd-deploy-minikube project and follow the README instructions to install and configure minikube, kubectl and Helm correctly.

Running the Mid CBF MCS

The ska-mid-cbf-mcs Tango device servers are started and run via Kubernetes.

Make sure Kubernetes/minikube and Helm have been installed (and verified) as described in the 'Set up Kubernetes' section.

Note: You may need to change permission to the .minikube and .kube files in your home directory:

sudo chown -R <user_name>:<user_name> ~/.minikube/
sudo chown -R <user_name>:<user_name> ~/.kube/

1. Make sure minikube is up and running

minikube start    # start minikube (local kubernetes node)
minikube status   # check current status of minikube

2. From the root of the project, build the application image.

cd ska-mid-cbf-mcs
eval $(minikube docker-env)  # if building from local source and not artefact repository
make build

make build is required only if a local image needs to be built, for example every time the SW has been updated. For development, in order to get local changes to build, run eval $(minikube docker-env) before make build

3. Install the umbrella chart.

make install-chart        # deploy from Helm charts
make install-chart-only   # deploy from Helm charts without updating dependencies

Note: make watch will list all of the pods' status in every 2 seconds using kubectl; make wait will wait until all jobs are 'Completed' and pods are 'Running'.

4. (Optional) Create python virtual environment to isolate project specific dependencies from your host environment.

virtualenv venv           # create python virtualenv 'venv'
source venv/bin/activate  # activate venv

5. Install linting and testing requirements.

make requirements

6. Run a test.

make test       # functional tests, creates a running deployment
make test-only  # functional tests with an already running deployment
make unit_test  # unit tests, deployment does not need to be running

Note: add -k pytest flags in setup.cfg in the project root to limit which tests are run

6. Tear down the deployment.

make uninstall-chart                  # uninstall deployment from Helm charts
deactivate                            # if in active virtualenv
eval $(minikube docker-env --unset)   # if docker-env variables were set previously
minikube stop                         # stop minikube

Jive and Taranta

Jive

Run make jive with the deployment active to get a command useful for configuring local Jive; this command sets the TANGO_HOST environment variable equal to <minikube-IP-address>:<database-pod-TCP-port>.

make jive   # copy and paste the output
jive&       # run Jive

Taranta

This prototype provides a graphical user interface using Taranta (previously known as WebJive); to set it up:

  • Add the following line to /etc/hosts: 
    192.168.49.2  taranta
    Note: 192.168.49.2 is the minikube IP address, obtainable with the command minikube ip
  • Deploy with make install-chart-with-taranta
  • Navigate to taranta/ska-mid-cbf/taranta/devices in a browser (works best with Google Chrome).

The following credentials can be used to operate the system:

  • Username: user1
  • Password: abc123

The device tree can be viewed and explored. In addition, device attributes can be seen and modified, and device commands can be sent, by creating and saving a new dashboard.

Releasing

For a new release (i.e. prior to merging a branch into master) update the following files by incrementing version/release/tag number fields to conform to the semantic versioning convention:

  • .release: release= and tag=
  • src/ska_mid_cbf_mcs/release.py: version =
  • charts/ska-mid-cbf/Chart.yaml: version: and appVersion:
  • charts/ska-mid-cbf/values.yaml: midcbf:image:tag:
  • charts/ska-mid-cbf-tmleafnode/Chart.yaml: version: and appVersion:
  • charts/ska-mid-cbf-tmleafnode/values.yaml: midcbf:image:tag:
  • charts/mid-cbf-umbrella/Chart.yaml:
    • version: and appVersion:
    • version: under ska-mid-cbf and ska-mid-cbf-tmleafnode

Note: appVersion represents the version of the application running, so it corresponds to the ska-mid-cbf-mcs docker image version.

Once a new release has been merged into master, create a new tag on GitLab and run the manual "publish-chart" stage of the tag pipeline to publish the Helm charts.

Development resources

Other resources

See more tango device guidelines and examples in the ska-tango-examples repository

Useful commands

Kubernetes

For Kubernetes basic kubectl commands see: https://kubernetes.io/docs/reference/kubectl/cheatsheet/

To display components of the MCS Kubernetes system:

kubectl get all -n ska-mid-cbf
kubectl describe <component-name> -n ska-mid-cbf  # info on a particular component

This should list the following running pods:

  • cbfcontroller-controller-0 : The CbfController TANGO device server.
  • cbfsubarrayxx-cbf-subarray-xx-0: xx ranges from 01 to 03. The 3 instances of the CbfSubarray TANGO device server.
  • fspxx-fsp-xx-0: xx ranges from 01 to 04. The 4 instances of the FspMulti TANGO device servers.
  • vccxxx-vcc-xxx-0: xxx ranges from 001 to 004. The 4 instances of the VccMulti TANGO device servers.
  • tmcspsubarrayleafnodetestx-tmx-0: x ranges from 1 to 2. The 2 instances of the TmCspSubarrayLeafNodeTest TANGO device servers.
  • tango-host-databaseds-from-makefile-test-0: The TANGO DB device server.
  • etc.

Docker

Set up Docker run without sudo:

sudo groupadd docker
sudo usermod -aG docker $USER
newgrp docker
docker run hello-world

System info and cleanup:

docker system info
docker system prune
docker images
docker image rm <image-ID(s)>
docker volume ls

To list the running containers issue:

docker ps

To list all created containers (not only running):

docker ps -a

To list all created containers but less verbose, run for example:

docker ps -a --format "table {{.ID}}\t{{.Status}}\t{{.Names}}"

License

See the LICENSE file for details.

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