AWS re:Invent 2025 - The Future of Intelligent Observability (AIM217)

The Future of Intelligent Observability

Observability Trends and Challenges

• Observability has evolved from simple dashboards to a need for more intelligent insights and actions
• Key trends and challenges include:
  • Aligning observability data and metrics with business goals and outcomes, not just technical metrics
  • Handling the increasing complexity of modern, cloud-based applications and microservices
  • Dealing with the "non-deterministic" nature of AI-powered systems and how to observe their behavior
  • Bridging the gap between technical teams (developers, platform engineers) and business stakeholders

The Vision for Intelligent Observability

• New Relic's vision is to become a "system of intelligence for the AI age" - moving beyond dashboards to proactive insights and automated actions
• Key elements of this vision include:
  • Automatically identifying and resolving issues before they impact the business
  • Providing developers with insights and optimizations to improve application performance and reliability
  • Aligning observability data with business metrics and KPIs to drive better alignment between tech and business

Intelligent Observability in Action

• The demo showcased an "intelligent agent" within New Relic that can:
  • Detect emerging performance issues and take corrective actions
  • Identify root causes and create remediation tickets
  • Optimize application performance and cost
  • Analyze security vulnerabilities and flag them for remediation
  • Run simulations to predict and prevent future issues

Integrating Observability with AWS

• New Relic announced new integrations with AWS services, including:
  • Two-way integrations with AWS DevOps Tooling to enable bi-directional data sharing and actions
  • Integrating New Relic AI with Amazon Business Index to correlate observability data with business metrics
  • Automated discovery and onboarding of cloud environments into New Relic
  • Security integrations to identify and remediate vulnerabilities

Key Challenges and Advice

• Overcoming the "alert fatigue" problem by implementing smarter, self-tuning alert systems
• Ensuring observability data is properly collected, integrated, and prepared for AI/ML analysis
• Fostering stronger relationships and alignment between technical and business teams
• Starting with what data you have today, rather than waiting for "perfect" observability
• Continuously improving observability processes through retrospectives and learnings

Conclusion

The future of observability is moving towards more intelligent, automated systems that can proactively identify and resolve issues, while also aligning observability data and insights with broader business goals and outcomes. By addressing key challenges around alert management, data integration, and cross-functional alignment, organizations can unlock the full potential of observability to drive better application performance, reliability, and business impact.