Disruptions to the digital experience can negatively impact customer satisfaction and business performance across all industries. Application failures, slow loading times, and unavailability of services can lead to user frustration, decreased engagement, and lost revenue. The risk and impact of an outage increases during peak usage periods, which vary by industry, from e-commerce sales events to quarter-ends and major product launches. According to New Relic’s Observability Forecast for 2024, businesses face a median annual downtime of 77 hours due to high-impact outages. These outages can cost up to $1.9 million per hour.
New Relic addresses these challenges by creating the New Relic AI custom plugin for Amazon Q Business. This custom plugin creates an integrated solution that combines New Relic AI’s observability insights and recommendations with Amazon Q Business’s acquisition, extension, and generation (RAG) capabilities, providing a natural language interface to get started. Masu.
Custom plugins streamline incident response, enhance decision-making, and reduce the cognitive load of managing multiple tools and complex datasets. This enables team members to interpret observability data and act quickly, improving system reliability and customer experience. Using AI and New Relic’s comprehensive observability data, businesses can prevent problems, minimize incidents, reduce downtime, and maintain high-quality digital experiences. .
In this post, we will explain the use case, how this custom plugin works, how to enable it, and how it can help improve your customers’ digital experience.
Challenge: Resolve application issues before they impact customers
New Relic’s 2024 observability forecast highlights three key operational challenges:
- Switching tools and contexts – Engineers use multiple monitoring tools, support desks, and documentation systems. 45% of support engineers, application engineers, and SREs use an average of five different monitoring tools. This fragmentation can result in a lack of SLAs and SLOs, disruption during critical incidents, and increased negative financial impact. Switching tools slows down decision-making during outages and e-commerce disruptions.
- Accessibility to knowledge – Knowledge such as operating procedures and post-incident reports is scattered and difficult to access, hindering effective incident response. This can lead to slower escalation, uncertain decision making, longer interruptions, and increased operational costs due to the involvement of extra engineers.
- Complexity of data interpretation – Team members can struggle to interpret monitoring and observability data due to complex applications with numerous services and cloud infrastructure entities, and unclear relationships between symptoms and problems. This complexity hinders quick and accurate data analysis and informed decision-making during critical incidents.
Custom plugins for Amazon Q Business address these challenges using an integrated natural language interface to gain critical insights. Use AI to investigate findings, turn them into clear recommendations, and provide quick access to indexed runbooks and post-incident reports. This custom plugin streamlines incident response, enhances decision-making, and reduces the effort of managing multiple tools and complex datasets.
Solution overview
New Relic custom plugins for Amazon Q Business streamline your workflow by centralizing important information and actions in one interface. This allows you to directly inquire about a specific service, host, or system component. For example, you can investigate sudden spikes in web service response times or slow databases. NR AI responds by analyzing current performance data and comparing it to historical trends and best practices. It then provides detailed insights and actionable recommendations based on the latest production information.
The following diagram shows the workflow.
When a user asks a question in the Amazon Q interface, such as “What’s the problem with the checkout process?”, Amazon Q queries the RAGs that were ingested with the customer’s runbooks. Runbooks are troubleshooting guides maintained by operations teams to minimize application disruption. Amazon Q obtains contextual information, such as the specific service name and infrastructure information related to your checkout service, and communicates with New Relic AI using a custom plugin. New Relic AI began an in-depth analysis of monitoring data after issues with our checkout service arose.
New Relic AI performs comprehensive analysis of your checkout service. Inspect key indicators such as service performance metrics, error rates, error patterns and anomalies, security alerts, and overall system status and health. The analysis results in a summarized alert intelligence report that identifies and explains the root cause of issues with your checkout service. This report provides clear, actionable recommendations and includes insights into real-time application performance. It also provides a direct link to the detailed New Relic interface. Users can access this comprehensive overview without leaving the Amazon Q interface.
Custom plugins surface information and insights directly within the Amazon Q Business interface, eliminating the need to switch between the New Relic and Amazon Q interfaces and enabling faster problem resolution.
Potential impact
The New Relic Intelligent Observability platform provides comprehensive incident response and application and infrastructure performance monitoring capabilities for SREs, application engineers, support engineers, and DevOps professionals. Organizations using New Relic see significant operational improvements with 65% fewer incidents, 10x more deployments, and 50% faster release times while maintaining 99.99% uptime. I am reporting. When you combine New Relic insights with Amazon Q Business, you can further reduce incidents, deploy high-quality code more often, and create more reliable experiences for your customers.
- Detect and resolve incidents faster – Reduce undetected incidents and resolve issues faster with this custom plugin. Incidents often occur when teams miss early warning signs or are unable to connect symptoms to underlying issues, leading to long service disruptions. New Relic collects and generates data that can identify these warning signs, but teams working in another tool may not have access to these important insights. For example, support specialists may not have direct access to monitoring dashboards, making it difficult to identify emerging issues. Custom plugins integrate these monitoring insights to help you more effectively identify and understand related issues.
- Simplify incident management – Custom plugins improve the efficiency of support engineers and incident responders by streamlining their workflows. Custom plugins let you manage incidents without having to switch between New Relic AI and Amazon Q at critical moments. The unified interface eliminates context switching and allows both technical and non-technical users to quickly access important monitoring data within the Amazon Q interface. This comprehensive approach speeds troubleshooting, minimizes downtime, and improves overall system reliability.
- Build trust across your team – Custom plugins allow team members to access application and infrastructure performance monitoring insights beyond traditional observability users. Transform complex production telemetry data into clear, actionable insights for product managers, customer service specialists, and executives. By providing a unified interface for querying and resolving issues, you empower your entire team, regardless of technical expertise, to maintain and improve your digital services. For example, when a customer service specialist receives a user complaint, they can quickly investigate application performance issues without having to navigate complex monitoring tools or interpret alert conditions. This unified view enables everyone supporting enterprise software to understand and act on insights into application health and performance. The result is a more collaborative approach across multiple enterprise teams, resulting in more reliable system maintenance and a better customer experience.
conclusion
New Relic AI custom plugins represent a step forward in digital experience management. The solution enables teams to deliver great digital experiences by addressing key challenges such as tool fragmentation, knowledge accessibility, and data complexity. This collaboration between AWS and New Relic opens possibilities for building a more robust digital infrastructure, driving innovation in customer-facing technology, and setting new benchmarks in proactive IT problem resolution.
To learn more about improving operational efficiency with AI-powered observability, visit the Amazon Q Business User Guide and explore the capabilities of New Relic AI. To get started, sign up for free Amazon Q training from AWS Training and Certification.
About New Relic
New Relic is the leading cloud-based observability platform that helps businesses optimize the performance and reliability of their digital systems. New Relic processes 3 EB of data per year. Over 5 billion data points are ingested and 2.4 trillion queries are performed every minute across 75,000 active customers. The platform handles over 333 billion web requests every day. The median platform response time is 60ms.
About the author
meena menon I’m a Senior Customer Solutions Manager at AWS.
sean falconer I’m a Senior Solutions Architect at AWS.
Nava Ajay Kansu Kota I am a Senior Partner Solutions Architect at AWS. He is currently part of the Amazon Partner Network (APN) team that works closely with ISV storage partners. Prior to joining AWS, his experience included running storage, backup, and hybrid cloud teams, where his responsibilities included creating managed service offerings in these areas.
david girling He is a senior AI/ML solutions architect with over 20 years of experience designing, leading, and developing enterprise systems. David is part of a team of experts focused on helping customers learn, innovate, and leverage these highly featured services with data for use cases.
camden suita He is the head of AI and ML innovation at New Relic, specializing in developing complex AI systems, agent frameworks, and generative user experiences for complex data acquisition, analysis, and action.
