Connectors / Integration
Integrate AWS CloudWatch with PagerDuty to Automate Incident Response
Turn CloudWatch alarms into PagerDuty incidents instantly, so your on-call team is always the first to know.
AWS CloudWatch + PagerDuty integration
AWS CloudWatch and PagerDuty do two different jobs that only work when they're connected. CloudWatch watches your AWS infrastructure continuously, tracking metrics, logs, and alarms across EC2, Lambda, RDS, and dozens of other services. PagerDuty makes sure the right engineers are notified and moving the moment something breaks. Without a connection between them, there's a gap between detection and response where incidents go unnoticed and resolution time climbs. Connecting these platforms through tray.ai closes that gap — an automated pipeline from anomaly to alert to fix.
CloudWatch alarms firing in isolation create noise without action. Engineers miss threshold breaches, teams rely on manual checks to translate infrastructure warnings into support tickets, and MTTR suffers. Connecting AWS CloudWatch to PagerDuty through tray.ai lets operations teams automatically create, route, and escalate incidents based on real-time AWS signals. You get full control over which alarms trigger which PagerDuty services and escalation policies. High-severity production outages wake the right on-call engineer within seconds, while low-priority warnings are logged without unnecessary interruptions. Faster incident response, less alert fatigue, and your AWS environment actually talking to your incident management workflows.
Automate & integrate AWS CloudWatch + PagerDuty
Automating AWS CloudWatch and PagerDuty business processes or integrating data is made easy with Tray.ai.
Use case
CloudWatch Alarm to PagerDuty Incident Creation
When a CloudWatch alarm transitions to ALARM state — whether from high CPU utilization, memory pressure, or network anomalies — tray.ai opens a new PagerDuty incident and routes it to the appropriate service and escalation policy. The incident is populated with alarm metadata including the affected resource, metric value, and breached threshold, giving on-call engineers immediate context without needing to log into the AWS console.
- No manual effort to translate CloudWatch alarms into PagerDuty incidents
- On-call engineers are notified within seconds of threshold breaches
- Incidents include AWS context for faster triage and diagnosis
Use case
Auto-Resolve PagerDuty Incidents When CloudWatch Returns to OK
When a CloudWatch alarm recovers and transitions back to OK state, tray.ai automatically resolves the corresponding PagerDuty incident. Stale alerts stop cluttering dashboards and keeping engineers unnecessarily on edge. PagerDuty always reflects the true health of your AWS infrastructure in real time.
- Eliminates stale incidents that distract on-call teams
- Keeps PagerDuty dashboards accurate
- Reduces unnecessary escalations and on-call fatigue
Use case
Severity-Based Incident Routing from CloudWatch Metrics
A Lambda timeout deserves a different response than a full RDS database failure. With tray.ai, you can define conditional logic that maps CloudWatch alarm severity, namespace, or resource type to specific PagerDuty services, urgency levels, and escalation policies. Critical P1 incidents immediately page senior engineers while informational warnings are quietly logged for review.
- Right-sized responses for alarms of different severity levels
- Reduces alert noise by routing low-priority alarms to non-urgent channels
- Improves on-call experience with context-aware escalation policies
Use case
CloudWatch Log Insights Anomaly Alerting via PagerDuty
CloudWatch Log Insights can surface error spikes, unusual patterns, and application-level failures buried in log streams. By connecting with PagerDuty through tray.ai, teams can trigger incidents when log-based metric filters breach thresholds — a sudden surge in 5xx errors or repeated authentication failures, for example — so application-layer issues get the same incident management treatment as infrastructure alarms.
- Extends incident coverage from infrastructure to application-level log anomalies
- Enables log-driven alerting without building custom notification pipelines
- Catches error patterns early before they become customer-facing outages
Use case
Scheduled AWS Health and Budget Alarm Summaries to PagerDuty
Beyond real-time alerting, tray.ai can run scheduled workflows that query CloudWatch for metric trends, billing anomalies, or AWS Health events and push summarized reports as low-urgency PagerDuty incidents or status updates. Operations teams get visibility into slow-burning issues — gradually increasing error rates, cost overruns — before they hit critical thresholds.
- Surfaces gradual degradation before it becomes a crisis
- Keeps teams informed about AWS cost and health without manual reporting
- Reduces surprise incidents through trend-aware monitoring
Use case
Multi-Region CloudWatch Alarm Aggregation into Unified PagerDuty Incidents
Organizations running workloads across multiple AWS regions often end up with the same underlying issue triggering dozens of redundant alarms. tray.ai can aggregate correlated CloudWatch alarms from multiple regions into a single, deduplicated PagerDuty incident, cutting the noise and helping on-call engineers find the root cause without sifting through hundreds of duplicate notifications.
- Dramatically reduces incident noise from correlated multi-region alarms
- Engineers see one consolidated incident rather than dozens of duplicates
- Accelerates root cause identification by surfacing the full blast radius
Challenges Tray.ai solves
Common obstacles when integrating AWS CloudWatch and PagerDuty — and how Tray.ai handles them.
Challenge
Alarm State Transitions Generating Duplicate or Redundant Incidents
CloudWatch alarms frequently flap between ALARM and OK states during intermittent issues, flooding PagerDuty with duplicate incident create and resolve events that exhaust on-call engineers and erode trust in the alerting system.
How Tray.ai helps
tray.ai workflows implement deduplication logic using PagerDuty's dedup_key field and state-tracking within the workflow itself, so a flapping alarm maps to a single incident lifecycle rather than generating a flood of redundant notifications.
Challenge
Mapping AWS Resource Context to Actionable PagerDuty Incidents
Raw CloudWatch alarm payloads contain AWS-specific identifiers like ARNs, metric namespaces, and dimension keys that mean something to AWS engineers but leave on-call responders without the plain-language context they need to act quickly.
How Tray.ai helps
tray.ai's data transformation tools let teams parse and enrich CloudWatch payloads — translating resource ARNs into human-readable names, appending runbook links, and formatting metric data into clear incident summaries — before anything reaches PagerDuty.
Challenge
Routing Alarms from Multiple AWS Accounts and Regions
Enterprises running across multiple AWS accounts and regions face a real headache consolidating CloudWatch alarms from fragmented infrastructure into a coherent PagerDuty incident structure without building and maintaining custom routing logic in every account.
How Tray.ai helps
tray.ai acts as a centralized integration layer that receives alarm events from all AWS accounts and regions via a shared SNS endpoint, applies unified routing logic, and maps alarms to the correct PagerDuty services and teams — no per-account Lambda functions required.
Templates
Pre-built workflows for AWS CloudWatch and PagerDuty you can deploy in minutes.
CloudWatch Alarm → PagerDuty Incident (Real-Time)
AWS CloudWatch Automatically creates a PagerDuty incident whenever a CloudWatch alarm transitions to ALARM state, populating it with the alarm name, affected AWS resource ARN, breached metric value, and a direct link to the CloudWatch console. Resolves the incident automatically when the alarm returns to OK.
Severity-Tiered CloudWatch to PagerDuty Routing
AWS CloudWatch Evaluates incoming CloudWatch alarms against a configurable severity matrix and routes them to the appropriate PagerDuty service and urgency level. Critical production alarms trigger high-urgency incidents with immediate escalation, while non-critical alarms create low-urgency incidents without waking on-call staff.
CloudWatch Log Metric Filter Breach to PagerDuty Alert
AWS CloudWatch Monitors CloudWatch log metric filters for application-level anomalies such as error rate spikes or failed authentication events. When a log-based metric breaches a defined threshold, tray.ai triggers a PagerDuty incident with log query context, so application teams can investigate faster.
Multi-Region Alarm Deduplication and PagerDuty Consolidation
AWS CloudWatch Aggregates CloudWatch alarm events from multiple AWS regions, detects correlated alarms representing the same underlying issue, and creates a single consolidated PagerDuty incident rather than flooding on-call engineers with duplicate notifications. Subsequent correlated alarms are appended as notes on the existing incident.
Post-Incident CloudWatch Metric Report Attachment
AWS CloudWatch When a PagerDuty incident is resolved, automatically queries CloudWatch for metric statistics covering the incident window and attaches a formatted summary — including peak values, anomaly timestamps, and affected resource identifiers — directly to the PagerDuty incident as a post-mortem data artifact.
Daily CloudWatch Anomaly Digest to PagerDuty Open Incidents
AWS CloudWatch Runs on a daily schedule to query CloudWatch Anomaly Detector findings and AWS Health events, then creates low-urgency PagerDuty incidents for any new anomalies found. Teams get visibility into gradual degradation without relying solely on threshold-based alarms.
How Tray.ai makes this work
AWS CloudWatch + PagerDuty runs on the full Tray.ai platform
Intelligent iPaaS
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Learn more →Agent Builder
Build AI agents that read, write, and take action in AWS CloudWatch and PagerDuty — with guardrails, audit, and human-in-the-loop.
Learn more →Agent Gateway for MCP
Expose AWS CloudWatch + PagerDuty actions as governed MCP tools — observable, rate-limited, authenticated.
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