Kibana Spaces & ML API Notes

gistfile1.txt

username = ''
password = ''
create_url = "/api/spaces/space"
URL= ':5601'
def requester(**kwargs): 
        headers = {
                "Content-Type": "application/json",
                "kbn-xsrf": "True",
        } if not "files" in kwargs else {
                "kbn-xsrf": "True",
        }
        auth = (username, password) if (username and password) else None
        return requests.request(headers=headers, auth=auth, verify=False, **kwargs)

url = URL + create_url
# Get All Spaces
response = requester(url=url, method="get")
response.json()

# Create Space
def create_space(url, data):
    response = requester(url=url, method="post", data=json.dumps(data))
    return response

url = URL + create_url
data = {"id": "test2",
  "name": "TEST2",
  "initials": "LL",
  "color": "#6092C0",
  "disabledFeatures": ["enterpriseSearch",
   "logs",
   "infrastructure",
   "apm",
   "uptime",
   "observabilityCases",
   "siem"]}
resp = create_space(url, data)
resp.text

# Update Space
def update_space(url, data):
    response = requester(url=url, method="put", data=json.dumps(data))
    return response

update_url = '/test2'
url = URL + create_url + update_url
data = {"id": "test2",
  "name": "AA",
  "initials": "AA",
  "color": "#6092C0",
  "disabledFeatures": ["enterpriseSearch",
   "logs",
   "infrastructure",
   "apm",
   "uptime",
   "observabilityCases",
   "siem"]}
resp = update_space(url, data)
resp.text

# Update Default Space
def update_space(url, data):
    response = requester(url=url, method="put", data=json.dumps(data))
    return response

update_url = '/default'
url = URL + create_url + update_url
data = {'id': 'default',
  'name': 'Default',
  "initials": "RR",
  'description': 'This is your default space!',
  'color': '#00bfb3',
  'disabledFeatures': ["enterpriseSearch"]}
resp = update_space(url, data)
resp.text

# Bulk Import ML Jobs
import json
def load_ml_jobs(url, data):
    response = requester(url=url, method="post", data=json.dumps(data))
    return response
with open('anomaly_detection_jobs.json', 'r') as dfile:
    data = json.load(dfile)

ml_url = '/api/ml/jobs/bulk_create'
url = URL + ml_url
resp = load_ml_jobs(url, data)
resp.text

# Open and Start ML Job
def start_ml_job(url, data):
    response = requester(url=url, method="post", data=json.dumps(data))
    return response

ml_open_job = '/api/ml/anomaly_detectors/netatmo/_open'
url = URL + ml_open_job
resp = start_ml_job(url, {})
print(resp.text)
ml_start_job = '/api/ml/datafeeds/datafeed-netatmo/_start'
url = URL + ml_start_job
resp = start_ml_job(url, {})
resp.text