Elevator Pitch
AI-powered anomaly detection is revolutionizing SRE, but coding complexity prevents many teams from adopting it. What if you could train and deploy AI models without writing code? In this talk, I’ll show how Azure ML’s No-Code AutoML enables SREs to implement AI-driven monitoring effortlessly
Description
No-Code Anomaly Detection for SREs: AI-Driven Monitoring with Azure Machine Learning AI-powered anomaly detection is a game-changer for Site Reliability Engineers (SREs), enabling real-time incident prevention and cloud cost optimization. However, implementing AI models traditionally requires coding expertise and deep ML knowledge—a barrier for many teams.
What if you could build AI-powered monitoring without writing a single line of code? In this talk, we’ll explore how Azure Machine Learning’s No-Code AutoML allows SREs and DevOps engineers to:
- Train and deploy anomaly detection models—without coding.
- Detect system failures in real-time and prevent outages with AI-powered insights.
- Integrate AI alerts seamlessly with Azure Monitor, Log Analytics, and Kusto (ADX).
- Fine-tune models to minimize false positives and enhance reliability.
Who Should Attend? - SREs, DevOps, and Cloud Engineers looking to leverage AI-driven monitoring. - Azure users interested in using AI for observability. - Teams seeking No-Code AI solutions to optimize cloud reliability.
Key Takeaways: - Learn how to train AI models without a single line of code. - Understand real-world SRE use cases for AI-driven observability. - Best practices for AI-powered incident prevention.
Join me to unlock the power of AI-driven monitoring—without ML expertise!
Notes
Why Me? - Microsoft Certified AI Expert – I hold Azure AI Engineer Associate, Data Scientist Associate, and AI Fundamentals certifications, demonstrating my deep expertise in AI/ML. - Hands-on Experience – I have built anomaly detection solutions using Azure Machine Learning and integrated AI-driven monitoring into cloud observability systems. - SRE and Cloud Expertise – With extensive experience in Azure Monitor, Log Analytics, Kusto (ADX), and cloud cost optimization, I understand how AI can enhance reliability engineering and incident response. - Proven Research & Thought Leadership – I have published multiple peer-reviewed papers on AI-driven cloud optimization and have presented at international conferences.
Backup Plan: If live access isn’t available, I can provide a pre-recorded walkthrough and screenshots of the process.
Why This Talk Matters for SREday 2025? - Directly Relevant to SREs & DevOps – AI-powered monitoring and anomaly detection are critical for proactive incident management and reliability. - Empowers Engineers with No ML Background – Many SREs lack ML expertise, and this talk removes that barrier. - Can also be presented as a shorter lightning talk (15 minutes) with a focus on key takeaways and a quick demo.