AI in Action Observability: To run your IT environment on insights, not instincts
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Jul 15, 2025 Vikram Murali, VP of Software Development for IBM Automation, sheds light on the transformative power of continuous observability in IT. He explains how it turns reactive measures into proactive strategies, enhancing operational resilience. The conversation covers the critical differences between effective and ineffective observability tools, the integration of AI in enhancing service reliability, and the challenges of data collection. Vikram emphasizes the importance of automation in optimizing cloud resources, ensuring businesses run seamlessly and efficiently.
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Evolution of Observability
- Observability evolved from basic monitoring to understanding system behavior and proactive action.
- It requires automation to translate insights into actions that prevent costly system disruptions.
Gen AI Powers Observability
- The vast data from logs, metrics, and traces is too large for traditional methods.
- Gen AI is essential to analyze this data quickly and efficiently, improving observability.
Managing Idle GPUs Efficiently
- Observability helps track expensive GPU usage for Gen AI workloads to avoid idle resources.
- Automated actions can reassign idle hardware to teams, optimizing infrastructure use and reducing costs.