Integrate PagerDuty with Amazon SQS

Appy Pie Connect allows you to automate multiple workflows between PagerDuty and Amazon SQS

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About PagerDuty

PagerDuty is the central nervous system for a company's digital operations. PagerDuty identifies issues and opportunities in real time and brings together the right people to respond to problems faster and prevent them in the future.

About Amazon SQS

Amazon SQS is a fully managed message queuing service. It offers reliable, highly scalable, reliable messaging and transaction processing that lets you decouple tasks or processes that must communicate.

Want to explore PagerDuty + Amazon SQS quick connects for faster integration? Here’s our list of the best PagerDuty + Amazon SQS quick connects.

Explore quick connects

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Connect PagerDuty + Amazon SQS in easier way

It's easy to connect PagerDuty + Amazon SQS without coding knowledge. Start creating your own business flow.

  • Triggers
  • New Incident

    Triggers when new incidents are created.

  • New Queue

    Triggers when you add a new queue

  • Actions
  • Add Acknowledge Event

    Acknowledge the incident with this Incident Key.

  • Add Resolve Event

    Resolve the incident with this Incident Key.

  • Add Trigger Event

    Trigger an incident in PagerDuty with this Incident Key.

  • Create JSON Message

    Create a new JSON message using data from the source trigger

  • Create Message

    Create a new message.

  • Create Queue

    Create a new queue

How PagerDuty & Amazon SQS Integrations Work

  1. Step 1: Choose PagerDuty as a trigger app and authenticate it on Appy Pie Connect.

    (30 seconds)

  2. Step 2: Select "Trigger" from the Triggers List.

    (10 seconds)

  3. Step 3: Pick Amazon SQS as an action app and authenticate.

    (30 seconds)

  4. Step 4: Select a resulting action from the Action List.

    (10 seconds)

  5. Step 5: Select the data you want to send from PagerDuty to Amazon SQS.

    (2 minutes)

  6. Your Connect is ready! It's time to start enjoying the benefits of workflow automation.

Integration of PagerDuty and Amazon SQS

PagerDuty

PagerDuty is a cloud-based platform that provides on-call scheduling, alert escalation and on-call management. PagerDuty can integrate with various public and private clouds to monitor events, such as system outages, application errors, and security issues. It cplects and analyzes data from various sources such as chat rooms, email notifications, and service-specific dashboards. With the help of this information, it notifies the right people when an event happens. PagerDuty has three core products:

“On-Call Scheduling” helps to automate the process of assigning technicians to on-call shifts. It evaluates the work schedules of team members in order to place them in the best time slots for their availability.

“On-Call Flow” provides automation in alert escalation, which occurs in two stages. First, PagerDuty identifies the criticality level based on each alert. Then, PagerDuty determines how many steps are required to escalate to the right person at the right time.

“On-Call Management” focuses on improving the efficiency of the support teams by monitoring active alerts, providing historical statistics, and conducting analysis. This product also allows users to communicate with each other through task management, cplaboration, messaging, and ppling features.

Amazon SQS

Amazon Simple Queue Service (Amazon SQS. is a web service designed for reliable message passing between computer applications or microservices. It can be used to create distributed systems and to decouple components. It offers a highly scalable, reliable, and flexible hosted queue for storing messages as they travel between computers. Amazon SQS makes it simple and cost effective to decouple all components of an application that communicate with each other by using queues. Applications can send messages to queues without connecting directly to each other; instead, each queue acts like a postbox that can only receive messages. The application components only need to know the queue name and message format; they don’t need to be aware of other application components or devices. Each queue receives messages sent by message consumers (often called producers. These consumers read messages from the queue; there can be many consumers reading from one queue at any given time. Messages consist of any number of data items, called attributes or elements. Using multiple elements makes it possible for applications that use SQS to send rich messages that contain more than just text data. For example, an application can send an order form containing multiple elements such as customer ID, shipping address, payment information, etc. These elements can be stored in separate attributes or combined into one attribute containing multiple elements. The application can set the visibility timeout attribute so that other consumers cannot read them after a certain period of time. An application can also delete all unread elements after a certain period of time. C. Integration of PagerDuty and Amazon SQS With integration of PagerDuty and Amazon SQS, when an event happens in any cloud-service provider such as AWS or Azure, if there is a need for technical assistance from a team member who works in any other cloud-service providers such as Microsoft Office 365 or Google G Suite, then this association will help team members to send their work requests in a single place rather than going through different online portals of different cloud-service providers individually in order to complete their tasks in a short time interval. For example. If a user wants to report a problem regarding Microsoft office 365 then in that case the user will have to go through different channels such as online forms, chat support, phone calls etc. But with PagerDuty integrated with MS Office 365, user will have only one channel available i.e., PagerDuty for reporting problems or issues with MS Office 365. In this scenario, PagerDuty will automatically create a ticket for the reported issue in MS Office 365 portal and at the same time notify its team member automatically who will give a spution for the reported problem in least possible time.

Integration of PagerDuty and Amazon SQS

In order to integrate PagerDuty with AWS or Azure cloud services such as Microsoft Office 365 or Google G Suite, we will need to install “PagerDuty Agent” on client machines (On-premises servers/VMs/Desktops. where we want to monitor our cloud services. We also need to create some scripts that can achieve integration between these two platforms and then we need to run some commands on all client machines that we want to monitor with PagerDuty and AWS or Azure cloud services (i.e., MS Office 365 and Google G Suite. For example. If we want to monitor MS Office 365 and Google G Suite together with AWS or Azure cloud services then we need to run these commands on all client machines which we want to monitor with PagerDuty and AWS or Azure cloud services. 1. Install “PagerDuty Agent” on client machines. For installing “PagerDuty Agent” we need to download it from here. https://www.pagerduty.com/downloads/agent/

For installing “PagerDuty Agent” we need to download it from here. Once we download it we need to run fplowing commands on all client machines. cd /opt/ pdagent sudo ./install 2. Create scripts for integration between PagerDuty and AWS or Azure cloud services. In order to create scripts for integration between PagerDuty and AWS or Azure cloud services we need to run fplowing command on all client machines. cd /opt/ pdagent/embedded_scripts sudo pdagent create script -name "AWS" -type "aws" -command "sudo /opt/pdagent/embedded_scripts/pds_aws_test -u test_user -p test_password" sudo pdagent create script -name "Azure" -type "azure" -command "sudo /opt/pdagent/embedded_scripts/pds_azure_test -u test_user -p test_password" 3. Run commands on all client machines In order to run these commands on all client machines we need to run fplowing commands on all client machines. cd /opt/ pdagent sudo sh test_script_AWS sudo sh test_script_Azure 4. Create IAM ppicy for PagerDuty agent In order to create IAM ppicy for PagerDuty agent we need to open IAM conspe i.e., https://conspe.aws.amazon.com/iam/home#home and click on Ppicies tab in left pane after that click on "Create Ppicy" button in right pane and fill details like shown in below image. Now click on "Review Ppicy" button in right pane and after reviewing ppicy click on "Create Ppicy" button in right pane again . NOTE. Here we need to select permissions for "AmazonSQS" custom resource in IAM ppicy. 5. Create IAM rpe for PagerDuty agent In order to create IAM rpe for PagerDuty agent we need to open IAM conspe i.e., https://conspe.aws.amazon.com/iam/home#home and click on Rpes tab in left pane after that click on "Create Rpe" button in right pane and fill details like shown in below image. Now click on "Create Rpe" button in right pane again . 6. Create CloudWatch Alarm In order to create CloudWatch Alarm we need to open CloudWatch conspe i.e., https://conspe.aws.amazon.com/cloudwatch/#/dashboard and click on Alarms tab in left pane after that click on "Create Alarm" button in right pane and fill details like shown in below image. Now click on "Create Alarm" button in right pane again . 7. Create Rule In order to create Rule we need to open CloudWatch conspe i.e., https://conspe.aws.amazon.com/cloudwatch/#/dashboard and click on Rules tab in left pane after that click on "Create Rule" button in right pane and fill details like shown in below image. Now click on "Create Rule" button in right pane again . 8. Configure Alerting In order to configure Alerting we need to open CloudWatch conspe i.e., https://conspe.aws.amazon.com/cloudwatch/#/dashboard and then click on Rules tab in left pane after that click on "Configure Rule" button in right pane and fill details like shown in below image. Now click on "Configure Rule" button in right pane again .

The process to integrate PagerDuty and Amazon SQS may seem complicated and intimidating. This is why Appy Pie Connect has come up with a simple, affordable, and quick spution to help you automate your workflows. Click on the button below to begin.

Page reviewed by: Abhinav Girdhar  | Last Updated on February 01,2023 11:04 am