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PagerDuty has announced a product collaboration with Amazon DevOps Guru, an operational insight service powered by machine learning (ML) from Amazon Web Services (AWS).
PagerDuty is one of four Amazon DevOpsGuru Launch Partners, further extending its longstanding relationship with AWS. Through this new integration, PagerDuty will automatically ingest observability data from Amazon DevOps Guru.
PagerDuty consolidates these digital health signals and alerts, and uses AIOps to contextualize and filter out the noise so teams can remediate issues in real-time, and customers can ensure critical business services get delivered.
As digital transformation accelerates, cloud computing adoption continues to increase; IDC predicts total worldwide spending on cloud services will surpass $1.0 trillion by 2024.
This shift leaves many organizations with a complex mix of hybrid-cloud and on-premises environments. As such, observability is becoming a business requirement for digital services built on any infrastructure.
Amazon DevOps Guru is a powerful yet simple to use native observability service. Tightly paired via the new integration with Amazon DevOps Guru, PagerDuty provides actionable insights and resolution, contextualized through ML algorithms, to the correct stakeholders.
The PagerDuty platform for real-time operations was built to ingest digital signals from across the entire enterprise ecosystem, and then arm the right responders with the right insights and tools to resolve issues in real-time. PagerDuty allows operations teams to improve the optics into their AWS environment and AWS-based applications.
Leveraging Amazon DevOps Guru’s ML-enabled application health information, PagerDuty provides even more real-time signal-to-resolution capabilities to our shared customers.
Through PagerDuty’s ingestion of Amazon Simple Notification Service (Amazon SNS) notifications on Amazon DevOps Guru, customers can seamlessly identify and action operational issues more quickly, before they become customer-impacting outages.
“This integration is a sign of where the industry is headed as the demand for deep observability grows,” said Jonathan Rende, Senior Vice President of Product at PagerDuty.
“For cloud native companies, PagerDuty’s combination with Amazon DevOps Guru means powerful, simple, no-configuration visibility and machine learning that ensures application uptime and instant incident response.
“For non-cloud native companies, it enables PagerDuty to further unify digital operations across complex, hybrid, and non-cloud-based applications as they migrate onto the cloud, with less complexity, less technology, and much faster ROI.”
Users can benefit from better automation and a more complete picture of their environment. Health signals from Amazon DevOps Guru coupled with those from other observability tools, help PagerDuty’s AIOps noise reduction algorithms and automation capabilities to be more effective.
The integration can also ensure cloud migration success by empowering teams to take real-time action on incidents that take place across your hybrid infrastructure. And, for teams who are “all in” on AWS, Amazon DevOps Guru’s out of the box app monitoring feeds can be ingested and made actionable by PagerDuty with almost no configuration needed. As a result, real-time incident response functionality is automatically added to customers’ app development lifecycle.
PagerDuty is also adding support for two other AWS services, focused on supporting cloud migration and removing noise from hybrid infrastructures. These build on the monitoring, security, and management and automation integrations already available through the platform. The new integrations for AWS include:
- PagerDuty for AWS Control Tower: Gives organizations the power of service ownership by applying guardrails that will either auto-remediate compliance issues or escalate to the right person to handle it.
- PagerDuty for AWS Outposts: Extends the AWS infrastructure to virtually any datacenter, allowing organizations to manage incidents in real-time for AWS infrastructure used in a private datacenter, co-location space, or on-premises facility.
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