Monitor, Scale and Backup Your AI App

本课程是 Build AI Apps Like a Pro: No-Code Tools for Beginners 专项课程的一部分

位教师：LearningMate

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3个模块

深入了解一个主题并学习基础知识。

中级等级

推荐体验

3 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Effectively monitor, scale, and back up AI applications to ensure optimal performance and meet service level agreements (SLAs).

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授课语言：英语（English）

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该课程共有3个模块

Monitor, Scale and Backup Your AI App is an intermediate course for developers, system administrators, and AI practitioners responsible for the operational health of AI applications. In today's world, deploying an AI model is just the beginning; ensuring it runs reliably under pressure is what defines success. This course provides the essential skills to guarantee your AI services are performant, resilient, and always available.

You will learn to transform raw data into actionable insights by applying platform analytics to build real-time performance dashboards and configure intelligent alerts, using examples from Azure AI Foundry. Next, you'll dive into resource management, analyzing system metrics to make data-driven scaling decisions that meet strict latency requirements, inspired by practices at Datadog. Finally, you will master business continuity by evaluating and implementing robust backup and restore procedures that align with critical RPO/RTO targets and SLAs, drawing on expert strategies from CAST AI. Through hands-on exercises and a final project, you will build a complete operational toolkit to ensure your AI applications achieve maximum uptime and peak performance.

This module focuses on establishing a foundation for operational excellence by teaching learners how to monitor AI applications proactively. You will learn to identify key performance indicators and use platform analytics to set up real-time dashboards and automated alerts. This ensures that potential issues are caught and addressed before they impact users, drawing on real-world practices like those used with Azure AI Foundry.

涵盖的内容

2个视频1篇阅读材料1个作业

In this module, learners will discover how to ensure their AI applications can handle fluctuating demand. You will learn to analyze performance metrics to make intelligent scaling decisions, balancing cost and responsiveness. The module covers different scaling strategies and how to apply them to meet latency requirements and service level agreements, using the Azure AI Search and Datadog integration as a guiding example.

涵盖的内容

2个视频1篇阅读材料2个作业

This final module addresses the critical need for disaster recovery and data protection. Learners will learn to evaluate and design backup and restore procedures that align with business requirements like Recovery Point Objectives (RPO) and Recovery Time Objectives (RTO). The module emphasizes the importance of regular testing and validation to ensure compliance and minimize downtime, incorporating insights from the CAST AI and Corptec case studies.