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Dynamic Environments and Tool Overload Drive Observability Challenges
Dedicated Teams, AI Integration, and Platform Alignment Are Key to Building Stro…
Aligning Architectures, Teams, and Hybrid Cloud Monitoring Is Crucial for Advanc…
Organizations Work to Build Confidence and Business Outcomes With AI in Observab…
Teams Increasingly Use Advanced Observability to Manage AI Models
Organizations Tackle Costs and Complexity With AI-driven Observability Solutions
Conclusion
Research Methodology
Respondent Demographics
Research Report: Transforming Observability and Monitoring Through AI
Research Report
Apr 09, 2025
by
Torsten Volk, Emily Marsh, Enterprise Strategy Group Research
AI increasingly enables organizations to understand their limitations and then optimally allocate their technology spending, maximizing efficiency and driving superior business outcomes. Organizations that harness AI-driven observability, visibility, and monitoring platforms can receive data-driven, actionable insights that transform the economics of application development and platform engineering.
But technology leaders and platform teams are faced with a key challenge: identifying and deploying AI-driven observability tools that fit their environment, expertise, and culture. Only then can they seamlessly enhance system reliability and performance through transparent and actionable insights. Organizations must prioritize explainability for stakeholders to understand the reasoning behind AI decisions to foster trust and refine AI’s decision-making processes and criteria.
To gain further insight into these trends, Enterprise Strategy Group surveyed 377 application developers and IT professionals at organizations in North America (U.S. and Canada) involved with observability and monitoring technology and processes at their organization.
Page Count: 24
Table of Contents
Executive Summary
Report Conclusions
Introduction
Research Objectives
Research Findings
Dynamic Environments and Tool Overload Drive Observability Challenges
Dedicated Teams, AI Integration, and Platform Alignment Are Key to Building Strong Observability
Aligning Architectures, Teams, and Hybrid Cloud Monitoring Is Crucial for Advanced Observability
Organizations Work to Build Confidence and Business Outcomes With AI in Observability
Teams Increasingly Use Advanced Observability to Manage AI Models
Organizations Tackle Costs and Complexity With AI-driven Observability Solutions
