Enhance PagerDuty AIOps with Autonomous Root Cause Analysis
While PagerDuty AIOps reduces alert noise and automates triage, Hawkeye AI SRE for PagerDuty delivers autonomous incident investigation and root cause analysis the instant critical alerts fire. Hawkeye empowers incident response and SRE teams to accelerate resolution across multiple enterprise tools while seamlessly integrating with your existing PagerDuty incident management workflows.
Why SRE Teams Choose Neubird for PagerDuty Enhancement:
- Enterprise-Wide Automation: Unlocks AI incident resolution workflows across OpenTelemetry, DataDog, ServiceNow, Amazon CloudWatch, Microsoft Azure Monitor and other observability tools for comprehensive incident response beyond alert correlation.
- Significant MTTR Reduction: Converts PagerDuty incident alerts into actionable root cause analysis with up to a 90% decrease in Mean Time to Resolution through autonomous investigation.
- SRE Burnout Alleviation: Eliminates time-consuming manual investigation with agentic AI workflows, empowering your SREs to focus on prevention and strategic improvements rather than firefighting.
- Incident Response Enhancement: Extends PagerDuty’s intelligent triage with deep technical investigation, providing the “why” behind incidents, not just the “what.”
How Neubird Enhances Your PagerDuty Environment
- Intelligent Session Management: Hawkeye monitors PagerDuty incidents with configurable priority filtering (High, High & Medium, or All) and automatically creates AI investigation sessions with full incident context.
- Cross-Service Investigation: Correlates PagerDuty service data with observability signals from connected tools to identify dependencies and cascade effects across your infrastructure.
- Automated Response Optimization: Tracks automation effectiveness, playbook triggers, and incidents resolved without human intervention to continuously improve your incident response workflows.
PagerDuty AIOps + Hawkeye AI SRE Use Cases
- Autonomous Investigation: Hawkeye automatically creates investigation sessions from PagerDuty high-priority incidents, providing instant AI analysis and context gathering across your observability stack.
- On-Call Enhancement: Enrich on-call engineer handoffs with pre-analyzed incident context from Azure, AWS or ServiceNow and DataDog to help SREs diagnosing the issue and accelerate response times.
- Alert Intelligence: Beyond PagerDuty’s noise reduction, Hawkeye analyzes recurring escalations and non-actionable alerts to optimize your alerting rules and improve signal quality.
- Post-Incident Analysis: Automatically generate comprehensive postmortem data from PagerDuty incidents with full investigation timeline, policy recommendations, and action item tracking for continuous improvement.
Integration Help
Need help to set up the connection? Follow our detailed PagerDuty integration setup guide.
Frequently Asked Questions
What is PagerDuty AIOps?
PagerDuty AIOps uses machine learning to reduce alert noise by 87%, automate manual incident response work, and provide intelligent triage through correlation tools and event-driven automation.
What is the difference between PagerDuty AIOps and Hawkeye by NeuBird?
PagerDuty AIOps focuses on alert noise reduction and incident triage within the PagerDuty platform. Hawkeye by NeuBird is an agentic AI SRE platform that extends PagerDuty’s capabilities by providing autonomous root cause investigation across your entire observability and infrastructure stack.
How does Hawkeye AI reduce Mean Time to Resolution (MTTR)?
Hawkeye receives PagerDuty incident alerts and immediately begins autonomous investigation across your observability tools (DataDog, AWS, Azure) to identify root causes. This eliminates the time engineers spend gathering context and investigating, often cutting MTTR by up to 90%.
How does Hawkeye integrate with PagerDuty incidents?
Hawkeye connects via PagerDuty API with configurable incident priority filtering. When incidents match your criteria, Hawkeye automatically creates investigation sessions that analyze the incident context, pull relevant telemetry data, and provide AI-driven insights to accelerate resolution.
Can Hawkeye and PagerDuty AIOps be used together?
Yes, Hawkeye and PagerDuty AIOps work together seamlessly. While PagerDuty AIOps handles alert correlation and noise reduction, Hawkeye provides the deep technical investigation and root cause analysis that your on-call engineers need for rapid incident resolution.
Can Hawkeye help optimize our PagerDuty alerting rules?
Yes, Hawkeye analyzes escalation patterns, non-actionable alerts, and manual escalation frequency to identify opportunities for alerting rule optimization and noise reduction beyond what PagerDuty AIOps provides.
How does Hawkeye ensure security with PagerDuty incident data?
Hawkeye has achieved SOC 2 Type II compliance and uses secure, read-only access to your observability data. All incident investigation data remains within your infrastructure boundaries, with role-based access control and enterprise-grade security protocols protecting sensitive information.
Resources
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IT operations are evolving beyond traditional alert automation with intelligent analysis that correlates data, identifies root causes, and provides actionable insights before engineers even step in. By reducing MTTR and minimizing alert fatigue, teams can shift their focus from constant firefighting to strategic improvements.
Transforming Datadog and PagerDuty Integration and Workflows with GenAI: Every Minute Counts in Incident Response
SRE teams waste valuable time gathering context before resolving incidents. Hawkeye streamlines this process by automatically analyzing data across Datadog, PagerDuty, and other observability tools, delivering instant insights. This shift reduces MTTR, prevents burnout, and lets engineers focus on strategic improvements.
Image Pull Errors: How Hawkeye Streamlines Container Deployment Troubleshooting
AI-powered teammates are transforming IT operations by automating investigations, accelerating decision-making, and reducing manual effort. By analyzing AWS, Kubernetes, and CI/CD telemetry, they pinpoint deployment issues in minutes, ensuring faster and more reliable rollouts. This shift allows SRE teams to focus on innovation rather than firefighting.
CPU Spikes Demystified: How Hawkeye Masters Resource Analysis
SRE teams are redefining CPU utilization management with AI, moving beyond manual data correlation. Hawkeye analyzes observability data streams in parallel, swiftly identifying root causes and cascading effects.
