Enhancing Incident Management with PagerDuty Advance and Amazon Q Index

Unlocking Operational Efficiency through AI Integration

A Collaborative Approach to Modern Incident Resolution

Navigating the Complexities of Data Ecosystems for Improved Insights

Understanding the Components: PagerDuty Advance and Amazon Q Index

Benefits for Enterprises: Streamlining Incident Response and Data Access

Solution Overview: Seamless Integration for Actionable Insights

Step-by-Step Implementation: Adding PagerDuty Advance as a Data Accessor

Clean-Up Process: Maintaining Your Environment

Conclusion: Transforming Incident Management with Intelligent Solutions

About the Authors: Insights from Industry Experts

Enhancing Incident Management with PagerDuty Advance and Amazon Q Business

This blog post is co-written with Jacky Leybman from PagerDuty.

As organizations scale their digital operations, they encounter unprecedented challenges in managing and capitalizing on their expansive data ecosystems. Chief among these challenges are data accessibility and quality. The intricacies of modern IT operations demand robust solutions capable of seamlessly integrating, processing, and delivering actionable insights.

In this post, we delve into how organizations can bolster their incident management capabilities by integrating PagerDuty Advance, an innovative suite of agentic and generative AI features, with Amazon Q Business. We will guide you through configuring PagerDuty Advance as a data accessor for Amazon Q indexes, allowing you to search and retrieve vital enterprise knowledge across multiple systems during incident responses. We also outline the key benefits of this integration—including improved search functionalities across connected platforms and enhanced data processing for expedited incident resolution—all while ensuring robust security measures are in place.

Understanding the Components

PagerDuty, a leading digital operations management platform, is designed to help organizations preemptively and effectively address business-impacting incidents. Utilizing sophisticated machine learning and AI, PagerDuty automates response workflows and provides real-time insights into operational health. As a pioneer in incident management, PagerDuty is the first platform to integrate with Amazon Q Business, providing an enterprise-grade solution for operational intelligence that synthesizes data across multiple Software as a Service (SaaS) applications, breaking down silos that often impede the efficacy of AI in driving operational resilience.

Amazon Q index enables independent software vendors (ISVs) to seamlessly connect their generative AI applications with enterprise data and metadata, fostering a unified search experience while maintaining stringent security and data ownership controls. The synergy between Amazon Q index and PagerDuty Advance creates a holistic solution that revolutionizes the approach to operational data management, facilitating numerous use cases that elevate incident management and efficiency across enterprises.

The integration merges refined data indexing from Amazon Q with real-time incident data from PagerDuty, fostering a comprehensive view of operational intelligence. Leveraging the Amazon Q Data Accessor, PagerDuty Advance can securely analyze data from over 100 different SaaS applications, transforming formerly siloed data into actionable insights critical for incident prevention and resolution.

The following video showcases this solution in action as an agent utilizes PagerDuty Advance to identify the cause of an incident and request troubleshooting insights.

Benefits for Enterprises

Enterprises routinely grapple with incident resolution, often squandering valuable time searching across multiple systems for answers. Consider a scenario where your team receives a critical alert—through the integration of PagerDuty Advance and Amazon Q index, your team can quickly access relevant runbooks or identify pertinent GitHub commits that may have triggered the issue.

This seamless integration transforms incident management. Here are some key benefits:

• Improved Search Capabilities: Amazon Q index enhances the generative AI question-and-answer experience by supplying semantically relevant enterprise content across connected systems. This results in actionable, contextually appropriate outcomes, significantly reducing search time for information across platforms like Confluence and GitHub.

• Enhanced Data Processing: The integration continuously ingests and analyzes operational data, automatically correlating incidents and discerning patterns across various systems. By intelligently parsing documents and code repositories, the system generates automatic links between incidents and relevant documentation while delivering a unified view of operational data.

• Cost Optimization: Organizations can realize significant cost savings by reducing mean time to resolution (MTTR) and optimizing resource allocation. With immediate access to runbooks and historical resolution data, teams can resolve incidents faster, improving operational efficiency and ROI on technology investments.

• Security Benefits: Security is a cornerstone of this integrated solution. Amazon Q index employs robust identity-aware access controls, ensuring enterprise index data is securely housed within the organization. With the specialized Search Relevant Content API, the system retrieves only contextually relevant content after authenticating users’ permissions, thereby providing a secure and compliant environment for managing sensitive operational data.

Jacky Leybman, Principal Product Manager on PagerDuty, encapsulates this development well:

“Our PagerDuty customers have asked for a one-stop shop for identifying critical issues and driving resolution. The integration of Amazon Q index with PagerDuty Advance represents a significant milestone, delivering comprehensive insights, including runbooks and historical information, to help swiftly resolve issues—resulting in up to 30% faster MTTR on average.”

Solution Overview

The Amazon Q Business data accessor is a secure component bridging enterprise applications with the Amazon Q index, facilitating PagerDuty Advance’s access to essential enterprise data. When users engage with PagerDuty Advance through communication platforms like Slack or Microsoft Teams, the orchestrator processes queries against both the PagerDuty knowledge base and the Amazon Q index, fetching data from various enterprise systems, including Slack and Salesforce, via built-in connectors.

With generative AI, PagerDuty Advance delivers contextual, actionable insights directly within communication tools, enabling teams to quickly access critical information—enhancing response efficiency and minimizing resolution times.

Prerequisites

To enable the Amazon Q index integration within PagerDuty Advance, ensure the following components and requirements are in place:

• Amazon Q Business set up with AWS IAM Identity Center for user authentication
• Access to PagerDuty Advance
• A valid AWS account with adequate service access

Steps to Add PagerDuty Advance as a Data Accessor

1. In the Amazon Q Business console, navigate to Data accessors.
2. Click on Add data accessor.
3. Select PagerDuty Advance as your data accessor.
4. Assign a name to your data accessor.
5. Configure access levels for data sources.
6. Specify user or group access permissions.

Following these steps ensures granular control over accessibility and organizational access.

Configuring Amazon Q for PagerDuty Advance

Once PagerDuty is set as a data accessor, enable Amazon Q Business assistance on PagerDuty Advance:

1. Navigate to Account Settings on your PagerDuty page, then choose PagerDuty Advance.
2. Toggle “Enable Amazon Q Business.”
3. Edit configuration values with the previously copied data accessor information.

Your setup is complete! You can now engage with the communication tool where PagerDuty Advance is available to begin querying data.

Clean Up

When finished with this solution, ensure to clean up created resources:

1. Disable Amazon Q Business in PagerDuty Advance.
2. Delete the PagerDuty data accessor from the AWS console.
3. Remove the Amazon Q Business application created as a prerequisite.

This process ensures all related resources are removed, eliminating unnecessary costs.

Conclusion

The integration of PagerDuty Advance and Amazon Q index furnishes businesses with an improved mechanism for managing day-to-day operations. This powerful combination allows for the secure retrieval of relevant information previously scattered across various systems while retaining data ownership. As a result, organizations can achieve quicker problem-solving and enhanced collaboration.

In this post, we illuminated how enterprises can leverage the integration between PagerDuty Advance and Amazon Q Business to streamline their incident management workflows, unlocking invaluable operational insights. Ready to elevate your operational intelligence? Discover the potential of your enterprise today with the Amazon Q Business console and the PagerDuty Advance documentation.

About the Authors

Jacky Leybman is a Principal Product Manager at PagerDuty, pioneering the development of PagerDuty Advance and AI Agents. With over 19 years in technology and product management, Jacky specializes in leading cross-functional teams to create innovative digital products.

Takeshi Kobayashi serves as a Senior AI/ML Solutions Architect within the Amazon Q Business team, dedicating his expertise to developing advanced AI/ML solutions for enterprise customers.

Daniel Lopes is a Solutions Architect at AWS, specializing in leveraging AWS services to help ISVs realize their product visions. Outside of work, Daniel is an avid mentor to his kids in gaming and pop culture.

Elevate your incident management and operational efficiency today!