Skip to main content

Minimal client library for Argus webservice REST API

Project description

This is a minimal and thin layer of Python client code on top of the Argus webservices REST API. Most of the library API is 1:1 with that of REST API so it serves to be more of a convenience than an abstraction. This means you still need to be familiar with the underlying REST API to be effective. For more information on the REST API and data model, refer to the Argus - User Guide. Special thanks to Demian Brecht for giving a lot of feedback early and helping to shape the API and the project.

You can also browse the Python API documentation online at: https://salesforce.github.io/python-argusclient/

A quick primer to using argusclient

Below you will find functional and self-explanatory code that shows how to do the following:

  • Import the relevant pieces from argusclient

  • Create the main entry point and establish login session

  • Query for existing namespaces

  • Create a new namespace

  • Collect metrics and annotations

  • Post metrics and annotations

  • Query for existing dashboards

  • Update or Create dashboard

  • Query for existing alerts

  • Delete alert

  • Create an alert along with a trigger and a notification

In addition, also look at the bundled example named splunk_to_argus.py that shows how to extract metrics from Splunk and push them to Argus.

Some package imports and initializations that we use later

import sys, os, time, calendar, getpass, logging, random
import lxml.etree

from argusclient import *
from argusclient.dashboardtags import DASHBOARD, CHART, TITLE, METRIC, FLAGS

logging.basicConfig()
logging.root.setLevel(logging.INFO)
logging.getLogger("requests").setLevel(logging.WARN)

endpoint = "http://localhost:8080/argusws"
user = "hdara"
password = None

tags = { "host": "hdara-wsl" }
fields = { "user": user }
curtm = long(calendar.timegm(time.gmtime()))*1000
ns_name = "hdara-ns"
ns_access_addl_users = ("hdara",)
dashboard_name = "hdara.test.dashboard"
alert_name = "hdara.test.alert"
scope_name = "hdara"
metric_name = "test"
ans = []

Login to the service and establish session

argus = ArgusServiceClient(user,
                           password or getpass.getpass("SSO password for %s: " % user),
                           endpoint=endpoint)
logging.info("Logging in")
argus.login()

Check if a namespace exists and create one if missing

logging.info("Looking up existing namespace with name: %s", ns_name)
nss = dict((ns.qualifier, ns) for ns in argus.namespaces.values())
ns = nss.get(ns_name)
if not ns:
    logging.info("Creating new namespace with name: %s", ns_name)
    ns = argus.namespaces.add(Namespace(ns_name))

Generate some random metrics against hdara-ns:hdara:test and mark the start and end with annotations.

logging.info("Generating some metric and annotation data for the dashboard")
m = Metric(scope_name, metric_name, tags=tags, namespace=ns_name)
for t in xrange(10, 0, -1):
    # Warden requires 1 minute gap between successive data points.
    ts = curtm-t*60*1000
    m.datapoints[ts] = random.randint(50, 100)
    if not ans or t == 1:
        ans.append(Annotation("script", "hdara", "test", ts, ts, "generated", tags=tags, fields=dict(event=ans and "start" or "end", **fields)))

Send metrics and annotations to Argus

logging.info("Adding metrics data to Argus")
am_resp = argus.metrics.add([m]);
if am_resp.error_count():
    logging.error("Errors reported in metric data: errorCount: %s errorMessages: %s", am_resp.error_count(), am_resp.error_messages())
logging.info("Adding annotation data to Argus")
an_resp = argus.annotations.add(ans)
if an_resp.error_count():
    logging.error("Errors reported in annotation data: errorCount: %s errorMessages: %s", an_resp.error_count(), an_resp.error_messages())

Generate dashboard content

mquery = str(MetricQuery(scope_name, metric_name, "sum", tags=tags, stTimeSpec="-1d", enTimeSpec="-0d", namespace=ns_name))
aquery = str(AnnotationQuery(scope_name, metric_name, "generated", tags=tags, stTimeSpec="-1d", enTimeSpec="-0d"))
content = lxml.etree.tostring(DASHBOARD(
    CHART(
        TITLE("hdara.test"),
        METRIC(mquery, name="hdara.test.metric"),
        FLAGS(aquery, name="hdara.test.annotation"),
        name="Chart"
        )
), method="html")
dashbobj.content = content

Update or Create dashboard

logging.info("Looking up existing dashboard with name: %s", dashboard_name)
dashbobj = argus.dashboards.get_user_dashboard(user, dashboard_name, shared=False)
if not dashbobj:
    logging.info("Creating new dashboard with name: %s", dashboard_name)
    dashbobj = Dashboard(dashboard_name, content, shared=True, description="A new dashboard")
    dashbobj = argus.dashboards.add(dashbobj)
else:
    logging.info("Updating dashboard with name: %s id %s", dashboard_name, dashbobj.argus_id)
    dashbobj.content = content
    argus.dashboards.update(dashbobj.argus_id, dashbobj)
logging.info("Dashboard url: %s", os.path.join(os.path.dirname(endpoint), "argus/#/dashboards", str(dashbobj.argus_id)).replace("-ws", "-ui"))

Look for an existing alert and delete it so that we can recreate it

logging.info("Looking up existing alert with name: %s owned by user: %s", alert_name, user)
alertobj = argus.alerts.get_user_alert(user, alert_name, shared=False)
if alertobj:
    logging.info("Deleting existing alert with name: %s id: %s", alert_name, alertobj.argus_id)
    argus.alerts.delete(alertobj.argus_id)

Finally, create alert with a trigger and a notification

logging.info("Creating new alert with alert name: %s", alert_name)
alertobj = argus.alerts.add(Alert(alert_name, mquery, "* */1 * * *",
                                  trigger=Trigger("hdara.test.trigger", Trigger.GREATER_THAN, 100000, 600000),
                                  notification=Notification("hdara.test.notification", Notification.EMAIL, subscriptions=["hdara@salesforce.com"]),
                                  shared=True))

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

argusclient-1.0.tar.gz (19.5 kB view details)

Uploaded Source

Built Distribution

argusclient-1.0-py3-none-any.whl (19.4 kB view details)

Uploaded Python 3

File details

Details for the file argusclient-1.0.tar.gz.

File metadata

  • Download URL: argusclient-1.0.tar.gz
  • Upload date:
  • Size: 19.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.23.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.7.3

File hashes

Hashes for argusclient-1.0.tar.gz
Algorithm Hash digest
SHA256 91a1346a5b0a3be2e9f26337215114fc025b6b00adf78f36bad32b0e02802a31
MD5 9ea3bf115ee69719aef2a44ddd51f375
BLAKE2b-256 a7b1d745d0e955584df84bdbaff2935d1a8de950f4319ebb4f784157d56dbee0

See more details on using hashes here.

File details

Details for the file argusclient-1.0-py3-none-any.whl.

File metadata

  • Download URL: argusclient-1.0-py3-none-any.whl
  • Upload date:
  • Size: 19.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.23.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.56.0 CPython/3.7.3

File hashes

Hashes for argusclient-1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b064ab7d98482f3ad7508eec5932b3345d4b9bc7999e558db1362ed5310f7e99
MD5 f8bcebe4ebd95ea0ebf2aa9f6574fbb8
BLAKE2b-256 8ad4c6f4e63f810c9c6180e8a0926e1898a320bc98e16123f2c5704754fb0efc

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page