PagerDuty Data Integration with Redshift

With Portable, integrate PagerDuty data with your Redshift warehouse in minutes. Access your digital business operations platform data from Redshift without having to manage cumbersome ETL scripts.

The Two Paths to Connect PagerDuty to Amazon Redshift

There are two ways to sync data from PagerDuty into your data warehouse for analytics.

Method 1: Manually Developing a Custom Data Pipeline Yourself

Write code from scratch or use an open-source framework to build an integration between PagerDuty and Redshift.

Method 2: Automating the ETL Process with a No-Code Solution

Leverage a pre-built connector from a cloud-hosted solution like Portable.

How to Create Value with PagerDuty Data

Teams connect PagerDuty to their data warehouse to build dashboards and generate value for their business. Let’s dig into the capabilities PagerDuty exposes via their API, outline insights you can build with the data, and summarize the most common analytics environments that teams are using to process their PagerDuty data.

Extract: What Data Can You Extract from the PagerDuty API?

PagerDuty is a digital business operations platform used for resolving incidents.

To help clients power downstream analytics, PagerDuty offers an application programming interface (API) for clients to extract data on business entities. Here are a few example entities you can extract from the API:

  • Incident Creation
  • Global Event Rules
  • Audit Records Event API Endpoints:
  • Send a Change Event
  • Send an Alert Event
  • Send a v1 Event

You can visit the PagerDuty API Documentation to explore the entire catalog of available API resources and the complete schema definition for each.

As you think about the data you will need for analytics, don’t forget that Portable offers no-code integrations to other similar applications.

Regardless of the SaaS solution you use, it’s important to find a digital business operations platform with robust data available for analytics.

Load: Which Destinations Are Best for Your PagerDuty ETL Pipeline?

To turn raw data from PagerDuty into dashboards, most companies centralize information into a data warehouse or data lake. For Portable clients, the most common ETL pipelines are:

  1. PagerDuty to Snowflake Integration
  2. PagerDuty to Google BigQuery Integration
  3. PagerDuty to Amazon Redshift Integration
  4. PagerDuty to PostgreSQL Integration
Common Data Warehouses
Common Data Warehouses

Once you have a destination to load the data, it’s common to combine PagerDuty data with information from other enterprise applications like Jira, Mailchimp, HubSpot, Zendesk, and Klaviyo.

From there, you can build cross-functional dashboards in a visualization tool like Power BI, Tableau, Looker, or Retool.

Develop: Which Dashboards Should You Build with PagerDuty Data?

Now that you have identified the data you want to extract, the next step is to plan out the dashboards you can build with the data.

As a process, you want to consume raw data, overlay SQL logic, and build a dashboard to either 1) increase revenue or 2) decrease costs.

Replicating PagerDuty data into your cloud data warehouse can unlock a wide array of opportunities to power analytics, automate workflows, and develop products. The use cases are endless.

Now that we have a clear sense of the insights we can create, let’s compare the process of developing a custom PagerDuty integration with the benefits of using a no-code ETL solution like Portable.

Method 1: Building a Custom PagerDuty ETL Pipeline

To build your own PagerDuty integration, there are three steps:

  1. Navigate the PagerDuty API documentation
  2. Make your first API request
  3. Turn an API request into a complete data pipeline

Let’s walk through the process in more detail.

How to Interpret PagerDuty’s API Documentation

When reading API documentation, there are a handful of key concepts to consider.


There are many common authentication mechanisms. OAuth 2.0 (Auth Code and Client Credentials), API Keys, JWT Tokens, Personal Access Tokens, Basic Authentication, etc. For PagerDuty, it’s important to identify the authentication mechanism and how best to incorporate the necessary credentials into your API requests.

All REST API calls require authentication. In order to make successful requests to the REST API, you must provide a valid form of authorization.


It’s important to identify the PagerDuty API endpoints you want to use for analytics. Most APIs offer a combination of GET, POST, PUT, and DELETE request methods; however, for analytics, GET requests are typically the most useful. At times, POST requests can be used to extract data as well.

For PagerDuty, the abilities endpoint is a great place to get started.

Request Parameters

For each API endpoint you would like to use for analytics, you need to understand the method (GET, POST, PUT, or DELETE) and the URL, but there are other considerations to take into account as well. You should look out for pagination mechanics, query parameters, and parameters that are added to the request path.

When you retrieve a collection over the API, the results are returned in portions, also known as pages. Currently, most endpoints use classic pagination. However, a growing list of endpoints support cursor-based pagination. Many index endpoints employ the classic pagination approach. Initially, only a certain number of results will be returned at a time. The default is 25. You can override this by passing a limit parameter to set the maximum number of results, but cannot exceed 100. Specifying a number for offset sets the starting point for the result set, allowing you to fetch subsequent resources that are not in the initial set of results.

PagerDuty uses limit and offset parameters for pagination.

How Do You Call the PagerDuty API? (Tutorial)

  1. Follow the instructions above to read the PagerDuty API documentation
  2. Identify and collect your credentials for authentication
  3. Pick the API resource you want to pull data from
  4. Configure the necessary parameters, method, and URL to make your first request (e.g. with curl or Postman)
  5. Add your credentials and make your first API call . Here is an example request using curl (without real credentials):
curl --request GET     
--header 'Accept: application/vnd.pagerduty+json;version=2'     
--header 'Authorization: Token token=y_NbAkKc66ryYTWUXYEu'     
--header 'Content-Type: application/json'

How Do You Maintain a Custom PagerDuty to Redshift ETL Pipeline?

Making a call to the PagerDuty API is just the beginning of maintaining a complete custom ETL pipeline.

Here is a getting-started guide to building a production-grade pipeline for PagerDuty:

  • For each API endpoint, define schemas (which fields exist and the type for each)
  • Process the API response and parse the data (typically parsing JSON or XML)
  • Handle and replicate nested objects and custom fields
  • Identify which PagerDuty fields are primary keys and which keys are required vs. optional
  • Version control your changes in a git-based workflow (using GitHub, GitLab, etc.)
  • Handle code dependencies in your toolchain and the upgrades that come with each
  • Monitor the health of the upstream API, and —when things go wrong— troubleshoot via the status page, reach out to support, and open tickets
  • Handle error codes (HTTP error codes like 400s, 500s, etc.)
  • Manage and respect rate limits imposed by the server

We won’t go into detail on all of the items above, but rate limits are a great example of the complexity found in a production-grade data pipeline.

PagerDuty rate limits the Events v2 API, to of approximately 120 calls/minute per integration key. The limit is calculated over a 60 second window looking back from the current time.

Rate limits on the REST API is 900 events/min across an entire organization.

If you don’t respect rate limits, and if you can’t handle server responses (like 429 errors with a Retry-After header), your pipeline can break, and analytics can become out-of-date.

What Are the Drawbacks of Building the PagerDuty ETL Pipeline Yourself?

You can probably tell at this point that there is a lot of work that goes into building and maintaining an ETL pipeline from PagerDuty to your data warehouse.

If you want less development work, faster insights, and no ongoing responsibilities, you should consider a cloud-hosted ETL solution.

Let’s walk through the setup process for a no-code ETL solution and its benefits.

Method 2: Using a No-Code PagerDuty ETL Solution

No-code ETL solutions are simple. Vendors specialize in building and maintaining data pipelines on your behalf. Instead of starting from scratch for each integration. Companies like Portable create connector templates that can be leveraged by hundreds or thousands of clients.

Step-By-Step Tutorial for Configuring Your PagerDuty ETL Pipeline

Off-the-shelf ETL tools offer a no-code setup process. Here are the instructions to connect PagerDuty to your cloud data warehouse with Portable.

  1. Create an account (no credit card required)
  2. Add a source —search for and select PagerDuty
  3. Authenticate with PagerDuty using the instructions in the Portable console
  4. Select Redshift and authenticate
  5. Set up a flow connecting PagerDuty to your analytics environment
  6. Run your flow to replicate data from PagerDuty to your warehouse
  7. Use the dropdown to set your data flow to run on a cadence

What Are the Benefits of Using Portable for PagerDuty ETL?

No-Code Simplicity

Start moving PagerDuty data in minutes. Save yourself the headaches of reading API documentation, writing code, and worrying about maintenance. Leave the hassle to us.

Easy to Understand Pricing

With predictable, fixed-cost pricing per data flow, you know exactly how much your PagerDuty integration will cost every month.

Fast Development Speeds

Access lightning-fast connector development. Portable can build new integrations on-demand in hours or days.

Hands-On Support

APIs change. Schemas evolve. PagerDuty will have maintenance issues and errors. With Portable, we will do everything in our power to make your life easier.

Unlimited Data Volumes

You can move as much data from PagerDuty to Amazon Redshift as you want without worrying about usage credits or overages. Instead of analyzing your ETL costs, you should be analyzing your data.

Free to Get Started

Sign up and get started for free. You don’t need a credit card to manually trigger a data sync, so you can try all of our connectors before paying a dime.

Stop waiting for your data.Start using Portable today.

Pioneer insights and streamline operations with data from all your business applications.

Get Started