We churn out charts for board meetings to show the health of our system (uptime, etc.). Historically, we did that once per quarter, manually. Recently, I endeavored to create a live dashboard for the same information, starting with production incidents over time. We use PagerDuty to alert on-call staff. Each incident is stored in PagerDuty, which is queryable via the PagerDuty API. From there, it is easy enough to transform that JSON into a matplotlib chart using pandas:
First, we grab the data:
from datetime import datetime, timedelta
import requests
%matplotlib inline
api_url = "https://api.pagerduty.com/incidents"
headers = {
'Accept': 'application/vnd.pagerduty+json;version=2',
'Authorization': 'Token token=YOUR_TOKEN'
}
today = datetime.today()
until = today.replace(day=1)
def get_month(since, until):
current_date = since
total_incidents = 0
while current_date < until:
next_date = current_date + timedelta(days=7)
if (next_date > until):
next_date = until
url = api_url + "?since={}&until={}&time_zone=UTC&limit=100".format(current_date.date(), next_date.date())
response = requests.get(url, headers=headers)
incidents = response.json()['incidents']
total_incidents = total_incidents + len(incidents)
current_date = next_date
return total_incidents
# Lookback over twelve months
incidents_per_month = {}
for delta in range(1,12):
since = (until - timedelta(days=1)).replace(day=1)
num_incidents = get_month(since, until)
incidents_per_month[str(since.date())] = num_incidents
print "{} - {} [{}]".format(since.date(), until.date(), num_incidents)
until = sinceAt this point,
incidents_per_month = { 2018-07-01": 13, "2018-08-01":5 ... }From there, it is just a matter of plotting the values using pandas:
import pandas as pd import numpy as np import matplotlib import seaborn as sns data = pd.DataFrame(incidents_per_month.items(), columns=['Month', 'Incidents']) data = data.sort_values(by=["Month"], ascending=True) data.plot(kind='bar', x='Month', y='Incidents', color="lightblue")
And voila, there you have it:
| Published on Java Code Geeks with permission by Brian ONeill, partner at our JCG program. See the original article here: Charting PagerDuty Incidents over Time (using pandas) Opinions expressed by Java Code Geeks contributors are their own. |
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Brian ONeillOctober 7th, 2018Last Updated: October 5th, 2018
Brian ONeillOctober 7th, 2018Last Updated: October 5th, 2018
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