Connect Pagerduty to Redshift
Send Pagerduty users, incidents, incident logs and 3 more data types to Redshift on a schedule. Refresh as often as every 15 minutes.
Redshift
schema pagerduty
usersincidentsincident_logsteamsservices- 1 more data type
How to connect Pagerduty and Redshift
4 steps. You can preview the Pagerduty data in Coupler.io before anything reaches Redshift.
Step 1 of 4
Connect Pagerduty
Enter your Pagerduty API key. You only do this once per account.
Step 2 of 4
Choose what to export
Pick the Pagerduty data you want in Redshift.
Step 3 of 4
Connect Redshift
Enter your Redshift connection details, then the schema and table for the Pagerduty data.
Show 3 more fields Show fewer fields
Step 4 of 4
Choose a write mode and schedule
Every run either replaces or appends the data in Redshift. Run it as often as every 15 minutes.
Each run drops and recreates users with fresh Pagerduty data.
Coupler.io made it easy to create dashboards and reports from different data sources. The sync is reliable and the user experience is amazing.
Take your data analytics to the next level
Sign Up with Google
Sign Up with MICROSOFT
SIGN UP WITH EMAIL
By signing up to Coupler.io, you agree to our Privacy Policy and Terms of Use.
Build your Pagerduty integrations with these destinations
Get the most of Pagerduty to Redshift integration
Gather data
Understand data
Automate data
Act on data
6 data types, including Users, Incidents, Incident logs, Teams and Services.
With your Pagerduty API key, entered once when you add the connection.
Yes, if the database user has CREATE privileges. Coupler.io creates the pagerduty schema and the users table on the first run.
With Replace, Coupler.io recreates users, so new Pagerduty columns appear automatically. With Append, the table keeps its schema, so add the column yourself or switch to Replace.
On a schedule you choose, from monthly down to every 15 minutes, depending on your Coupler.io plan.
Yes. Add more sources to the same data flow, for example 100ms or Amazon Seller Central, and join or append them before the data reaches Redshift.
