AI agents, cloud-native applications, and complex multi-tiered architectures are becoming more common, and enterprises require innovative solutions to help them manage and optimize their IT environments. Next-gen observability can be critical in ensuring business resilience in a rapidly evolving digital landscape. A recent CUBE Conversation with Alois Reitbauer, chief technology strategist at Dynatrace, and Eve Psalti, senior director of AI at Microsoft, discusses how their collaboration addresses these demands and enables greater business resilience.
The Dynatrace-Microsoft Partnership: A Unified Approach to Observability
Alois Reitbauer highlighted the longstanding partnership between Dynatrace and Microsoft, which was designed to serve mutual customers who are heavily invested in cloud and AI technologies. Dynatrace’s observability and security solutions cover both traditional and AI workloads, while the collaboration with Microsoft Azure allows these features to be seamlessly integrated into the cloud environment. This setup means enhanced visibility, automated issue resolution, and a streamlined experience for joint customers, creating a consistent and efficient way to manage cloud-based resources while reducing downtime and maintaining optimal performance.
The Role of Observability in AI Ecosystems
From Microsoft’s perspective, Psalti emphasizes that observability is essential within the AI ecosystem. Observability enables businesses to monitor AI model behavior, data patterns, and anomalies, providing a deep level of insight that supports the robustness and reliability of applications. As Psalti notes, “You can’t manage what you can’t see,” stressing that observability offers crucial visibility into shifts in AI model performance. This visibility is especially important for preventing failures and optimizing resource usage in real time, giving enterprises actionable insights that enable them to adjust quickly and efficiently.
Reitbauer explains how the adoption of cloud and AI technologies is reshaping the enterprise landscape. Today’s organizations are not just digital—they are digital-first, automating processes that were once manual. As a result, applications now operate in environments where multiple services interact, each reliant on a network of APIs and integrations. Managing this complexity requires more than just observability; it calls for AI-enhanced observability to support IT teams in maintaining, optimizing, and troubleshooting applications at scale.
Automation becomes essential, as traditional, manual approaches to managing these complex environments are no longer viable, especially with the added complexity of generative AI. AI observability offers a proactive solution by identifying and addressing issues before they impact end users, allowing companies to leverage the quality of their digital services as a key differentiator.
Managing Complex Application Architectures in a Multi-Tiered World
The shift from three-tiered to multi-tiered applications, often involving microservices and layered AI components, adds new challenges for businesses. Understanding application behavior and root causes becomes more difficult as complexity increases. Psalti recognized the rapid evolution of AI and explained how Microsoft is committed to providing organizations with various AI models to meet their diverse needs across industries, including healthcare, finance, retail, and manufacturing. With a strong focus on responsible AI, Microsoft ensures its models are high-performing, transparent, and free from bias.
Reitbauer elaborated on how Dynatrace uses AI within its platform to enhance customer experience. The company’s Hypermodal AI, also known as Davis, combines predictive and causal AI techniques to deliver a comprehensive observability solution. Predictive AI anticipates potential issues before they impact the user, while causal AI identifies the root causes of problems, enabling IT teams to resolve issues efficiently. This combination allows Dynatrace to provide customers with real-time insights, from deployment configurations to performance adjustments, fostering a proactive approach to problem-solving.
Generative AI: A New Dimension in Observability
With the integration of generative AI, Dynatrace’s observability platform goes beyond simply identifying issues. It can make real-time recommendations for issue resolution, enabling businesses to address problems proactively and at scale without extensive manual intervention. Reitbauer explained that Dynatrace uses generative AI to automate workflows, substantially boosting productivity and scalability for enterprises.
This approach aligns well with Microsoft’s focus on offering customers flexibility, whether through API integrations, ready-to-use models, or custom applications. Microsoft collaborates with industry leaders like OpenAI and Mistral to provide a wide array of AI models that cater to industry-specific requirements. The collaboration with Dynatrace further supports this approach, equipping customers with the tools to diagnose performance issues, monitor application reliability, and enhance security.
The Importance of Governance in AI-Driven Observability
As the conversation shifts to the importance of governance, Psalti emphasized the need for clear AI governance frameworks to drive responsible experimentation and align observability solutions with business objectives. Through their partnership, Microsoft and Dynatrace combine Azure’s cloud capabilities with Dynatrace’s observability insights, offering customers a reliable and secure way to optimize performance. This collaboration supports enterprises in balancing innovation with compliance, making it easier to implement observability solutions that are aligned with both operational and regulatory requirements.
How AI-Driven Observability Enhances Cloud Environments
Reitbauer outlined how AI-driven observability enhances cloud experiences by allowing companies to pinpoint the causes of unexpected behavior or performance issues and quickly address them. This capability is particularly beneficial for Site Reliability Engineering (SRE) and DevOps teams, who can offload much data analysis and troubleshooting to automated observability tools. This automation enables these teams to focus on strategic innovation tasks, delivering superior customer experiences at scale.
Our Perspective
AI-driven observability is no longer optional but a necessity for enterprises navigating the complex landscape of digital transformation. By offering real-time insights, automating critical processes, and fostering innovation, observability empowers businesses to build resilient, scalable, and customer-centric systems. The collaboration between Dynatrace and Microsoft demonstrates the transformative potential of combining robust observability with cutting-edge AI and cloud technologies. Organizations that embrace these capabilities will be better equipped to drive innovation, improve operational efficiency, and maintain a competitive edge in the rapidly evolving digital world.
For more information on these solutions please visit the Dynatrace website and Microsoft website
For more articles on this partnership from theCUBE Research.
