Celery Commands Etc

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Getting Started with Kubernetes

1. Install Minikube
$ brew update
$ brew install kubectl
$ brew cask install minikube

2. Install xhyve
$ brew install docker-machine-driver-xhyve

3. Set superuser privileges for xhyve (this appears during installation)
$ sudo chown root:wheel /usr/local/opt/docker-machine-driver-xhyve/bin/docker-machine-driver-xhyve
$ sudo chmod u+s /usr/local/opt/docker-machine-driver-xhyve/bin/docker-machine-driver-xhyve

4. Start minikube
$ minikube start --vm-driver=xhyve

5. Test
$ kubectl config current-context
minikube

6. Get cluster nodes info
$ kubectl get nodes
NAME       STATUS    ROLES     AGE       VERSION
minikube   Ready         22m       v1.8.0

7. Stop cluster
$ minikube stop
Stopping local Kubernetes cluster...
Machine stopped.

8. Delete minikube
$ minikube delete
Deleting local Kubernetes cluster...
Machine deleted.

9. Show available kubernetes versions
$ minikube get-k8s-versions
The following Kubernetes versions are available when using the localkube bootstrapper:
 - v1.8.0
 - v1.7.5
 - v1.7.4
...

10. Get v1.8.0
$ minikube start --vm-driver=xhyve --kubernetes-version="v1.8.0"

11. Start dashboard
$ minikube dashboard

Get Custom Settings in Django

1. Insert additional settings this way...

In settings.py, or settings/development.py, can insert whatever data structure...

RESOURCE_CREDENTIALS = {
    'client': {
        'USERNAME': 'root',
        'PASSWORD': 'abc123',
    },
    'server': {
        'USERNAME': 'root',
        'PASSWORD': 'ABC123!',
    }
}


2. Then from the app access it this way...

e.g., in views.py...

from django.conf import settings

RESOURCE_CREDENTIALS = getattr(settings, 'RESOURCE_CREDENTIALS')
USERNAME = RESOURCE_CREDENTIALS["client"]["USERNAME"]
PASSWORD = RESOURCE_CREDENTIALS["client"]["PASSWORD"]

How to Integrate Clarity UI on your Angular App

I heart Clarity UI.

Install
$ yarn add clarity-icons
$ yarn add @webcomponents/custom-elements@1.0.0
$ yarn add clarity-ui
$ yarn add clarity-angular

Use clarity on Angular
$ vi .angular-cli.json
"styles": [
  ...
  "../node_modules/clarity-icons/clarity-icons.min.css",
  "../node_modules/clarity-ui/clarity-ui.min.css"
],
"scripts": [
  ...
  "../node_modules/@webcomponents/custom-elements/custom-elements.min.js",
  "../node_modules/clarity-icons/clarity-icons.min.js"
],

$ vi app.module.ts
import { ClarityModule } from "clarity-angular";
imports: [
  ...
  ClarityModule.forRoot(),
  ...
],

Angular Development Production Settings

This came from this post

Angular apps created using angular-cli will have src/environments directory.

1. Add another file in there called environment.staging.ts with the following entry...
export const environment = {
  production: false,
  envName: 'staging'
};

2. Modify .angular.cli.json
"environments": {
        "dev": "environments/environment.ts",
        "prod": "environments/environment.prod.ts",
        "staging": "environments/environment.staging.ts"
      }

3. Now when creating a build or serving the app..
$ ng build -prod
$ ng build -staging
$ ng serve -prod
$ ng serve -staging

4. To use...
import { environment } from './environment';
export class MyappAppComponent {  
  title = 'myapp works!';
  environmentName = environment.envName;
}

VS Code Cheat Sheet

Full list of shortcuts

1. Detach file to another window
⌘K, O

2. Format file
⇧ + Opt + F

3. Preview side-by-side
⌘K, V 

4. Screen shot
⇧⌘3 - whole screen
⇧⌘4 - selection

Celery Tasks Parallel and Chained Execution Workflow

In celery, it is very easy to chain and parallelize execution of tasks, e.g. to satisfy this example workflow...

      _____
     |task1|      1. exec task1
    /      \
 __/__    __\__
|task2|  |task3|  2. parallel task1 & task2
   \        /
    \ _____/
     |task4|      3. exec task4 when both task1 & task2 are done

from celery import chain, group, chord
from orchestrator.tasks.host_tasks import acquire_hosts, prepare_hosts, return_hosts
from orchestrator.tasks.job_tasks import start_job, stop_job
from orchestrator.tasks.vcenter_tasks import acquire_vcenter, return_vcenter


def start_performance_run_workflow(job_id):
    print('Starting performance run workflows for job %s' % job_id)
    # The effect of this chain, is that only the first one is routed
    # to the "regular.priority" queue
    # subsequent tasks are routed to "celery" default queue
    workflow = chain(
        acquire_hosts.si(job_id),
        chord(
            (prepare_hosts.si(job_id), acquire_vcenter.si(job_id)),
            start_job.si(job_id)
        )
    ).apply_async(queue="regular.priority")