Alert fatigue has become one of the biggest challenges for modern observability teams. As environments grow in complexity and alert volumes climb, teams are forced into a constant cycle of prioritization that makes it difficult to ensure critical issues don’t slip through the cracks. Tools like PagerDuty play an essential role in incident management and response, but they don’t provide insight into which alerts actually need attention. This lack of clarity exacerbates alert fatigue and contributes to engineer burnout over time.
Edge Delta’s AI Teammates are purpose-built to address alert fatigue and keep you focused on the issues that matter. These role-aware, out-of-the-box AI agents autonomously analyze alerts, surface legitimate signals from noise, correlate relevant telemetry data, and identify root causes. This enables on-call engineers to make informed decisions faster without getting bogged down in manual triage.
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With Edge Delta’s out-of-the-box AI agent for SRE, teams get clearer context on the alerts that matter and more confidence in the overall health and performance of their apps.
Learn MoreIn this post, we’ll demonstrate how to connect AI Teammates with PagerDuty in a few short steps, and walk through an example scenario that shows how this agentic observability team cuts through alert noise while automating incident response.
Easily Connect Your PagerDuty Environment with AI Teammates
Edge Delta’s PagerDuty Connector enables AI Teammates to ingest PagerDuty tickets in just a few minutes. Once connected, every critical PagerDuty alert automatically triggers AI Teammates to analyze relevant telemetry data, correlate events across services, and build a diagnostic timeline to guide you during your on-call shift.
To set this up, you’ll first need to navigate to the Connectors page in your Edge Delta account and click “Add Connector.” From there, select the PagerDuty connector, click the “Connect” button, and follow the OAuth flow to link your PagerDuty instance. Save the newly created webhook URL and token — you’ll need these to configure the webhook in PagerDuty:
In your PagerDuty account, navigate to Integrations → Webhooks from the main nav and create a new webhook instance. Paste the webhook URL from Edge Delta, and add the authentication token as a custom header with the following parameters:
Name: Authorization
Value: Bearer <your-webhook-token>
Finally, click “Add Webhook” to finish the setup. Once complete, your AI Teammates will be ready to start running autonomous alert response workflows. For additional configuration options and custom header setup, check out our PagerDuty integration documentation.
Automate Incident Response with AI Teammates
With the PagerDuty Connector now active, every new incident that triggers a PagerDuty alert will automatically notify your AI Teammates to begin an investigation. To demonstrate, let’s walk through a real-world example, where a P1 alert fires for a fraud-scorer service experiencing sustained p99 latency above 2 seconds:
Once the ticket is created, the OnCall AI super-agent instantly starts a new thread, tags the SRE Teammate, and initiates triage. After reviewing the impacted services, OnCall AI upgrades the severity to a P0 to more accurately reflect incident impact, while the SRE Teammate begins querying relevant telemetry data, building a timeline of events, and correlating failures across the environment:
During the investigation, the SRE Teammate identifies the root cause: node-level memory pressure causing the fraud-scorer service to degrade. The nodes hit 95% memory utilization due to other services repeatedly crashing and restarting from memory leaks. This memory pressure caused the fraud-scorer’s ML model performance to collapse, spiking latency from 40ms to 2.8+ seconds:
From here, the SRE Teammate provides actionable remediation steps: immediately increase memory allocation for the fraud-scorer service to restore functionality, then investigate the crash loops in payment-processor and session-cache to fix the underlying memory leaks that are causing the node-level pressure.
Faced with a P0 incident impacting multiple services, AI Teammates autonomously correlated logs, checked Kubernetes events, queried node metrics, and built a historical timeline — completing in minutes what would’ve been an extensive manual investigation. The SRE Teammate fully investigated the incident with clear root cause analysis and actionable next steps, allowing the on-call engineer to jump straight into remediation instead of starting from scratch.
Conclusion
Edge Delta’s AI Teammates transform how human teams handle incidents by automatically triaging PagerDuty alerts the moment they fire. These out-of-the-box AI agents immediately analyze alert context, correlate it with data from across your environment, and build a diagnostic timeline to help on-call engineers spend less time chasing false positives and focus on remediation. Whether it’s memory leaks, cascading failures, or silent degradations like the fraud-scorer incident above, AI Teammates know what to look for, how to connect the dots across services, and how to provide actionable remediation steps that accelerate resolution.
To learn more about how AI Teammates can reduce mean time to resolution and eliminate alert fatigue by automating incident triage, sign up for a free trial or book a live demo with a technical member of our team.
