Amazon Web Services (AWS), an Amazon.com company, announced Amazon DevOps Guru, a fully-managed operations service that uses machine learning to make it easier for developers to improve application availability by automatically detecting operational issues and recommending specific actions for remediation.
Amazon DevOps Guru applies machine learning informed by years of Amazon.com and AWS operational excellence to automatically collect and analyze data like application metrics, logs, events, and traces for identifying behaviors that deviate from normal operating patterns (e.g. under-provisioned compute capacity, database I/O over-utilization, memory leaks, etc.). When Amazon DevOps Guru identifies anomalous application behavior (e.g. increased latency, error rates, resource constraints, etc.) that could cause potential outages or service disruptions, it alerts developers with issue details (e.g. resources involved, issue timeline, related events, etc.) via Amazon Simple Notification Service (SNS) and partner integrations like Atlassian Opsgenie and PagerDuty to help them quickly understand the potential impact and likely causes of the issue with specific recommendations for remediation.
Developers can use remediation suggestions from Amazon DevOps Guru to reduce time to resolution when issues arise and improve application availability and reliability with no manual setup or machine learning expertise required. There are no upfront costs or commitments with Amazon DevOps Guru, and customers pay only for the data Amazon DevOps Guru analyzes.
Amazon DevOps Guru’s machine learning models leverage over 20 years of operational expertise in building, scaling, and maintaining highly available applications for Amazon.com. This gives Amazon DevOps Guru the ability to automatically detect operational issues (e.g. missing or misconfigured alarms, early warning of resource exhaustion, config changes that could lead to outages, etc.), provide context on resources involved and related events, and recommend remediation actions – with no machine learning experience required.
With just a few clicks in the Amazon DevOps Guru console, historical application and infrastructure metrics like latency, error rates, and request rates for all resources are automatically ingested and analyzed to establish normal operating bounds, and Amazon DevOps Guru then uses a pre-trained machine learning model to identify deviations from the established baseline.
When Amazon DevOps Guru analyzes system and application data to automatically detect anomalies, it also groups this data into operational insights that include anomalous metrics, visualizations of application behavior over time, and recommendations on actions for remediation.
Amazon DevOps Guru also correlates and groups related application and infrastructure metrics (e.g. web application latency spikes, running out of disk space, bad code deployments, memory leaks etc.) to reduce redundant alarms and help focus users on high-severity issues. Customers can see configuration change histories and deployment events, along with system and user activity, to generate a prioritized list of likely causes for an operational issue in the Amazon DevOps Guru console.
To help customers resolve issues quickly, Amazon DevOps Guru provides intelligent recommendations with remediation steps and integrates with AWS Systems Manager for runbook and collaboration tooling, giving customers the ability to more effectively maintain applications and manage infrastructure for their deployments.
Together with Amazon CodeGuru – a developer tool powered by machine learning that provides intelligent recommendations for improving code quality and identifying an application’s most expensive lines of code – Amazon DevOps Guru provides customers the automated benefits of machine learning for their operational data so that developers can more easily improve application availability and reliability.
“Customers have asked us to continue adding services around areas where we can apply our own expertise on how to improve application availability and learn from the years of operational experience that we have acquired running Amazon.com,” said Swami Sivasubramanian, VP, Amazon Machine Learning, Amazon Web Services, Inc. “With Amazon DevOps Guru, we have taken our experience and built specialized machine learning models that help customers detect, troubleshoot, and prevent operational issues while providing intelligent recommendations when issues do arise. This enables teams to immediately benefit from operational best practices Amazon has learned from running Amazon.com, saving customers the time and effort that would otherwise be spent configuring and managing multiple monitoring systems.”
With a few clicks in the AWS Management Console, customers can enable Amazon DevOps Guru to begin analyzing account and application activity within minutes to provide operational insights. Amazon DevOps Guru gives customers a single-console experience to visualize their operational data by summarizing relevant data across multiple sources (e.g. AWS CloudTrail, Amazon CloudWatch, AWS Config, AWS CloudFormation, AWS X-Ray) and reduces the need to switch between multiple tools. Customers can also view correlated operational events and contextual data for operational insights within the Amazon DevOps Guru console and receive alerts via Amazon SNS.
Additionally, Amazon DevOps Guru supports API endpoints through the AWS SDK, making it easy for partners and customers to integrate Amazon DevOps Guru into their existing solutions for ticketing, paging, and automatic notification of engineers for high-severity issues.
PagerDuty and Atlassian are among the partners that have integrated Amazon DevOps Guru into their operations monitoring and incident management platforms, and customers who use their solutions can now benefit from operational insights provided by Amazon DevOps Guru.
Amazon DevOps Guru is available in preview today in US East (N. Virginia), US East (Ohio), and US West (Oregon), Asia Pacific (Singapore), and Europe (Ireland) with availability in additional regions in the coming months.
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