{"id":3225,"date":"2024-08-23T11:29:52","date_gmt":"2024-08-23T18:29:52","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/semantic-kernel\/?p=3225"},"modified":"2025-02-10T10:19:11","modified_gmt":"2025-02-10T18:19:11","slug":"step-by-step-guide-to-building-a-powerful-ai-monitoring-dashboard-with-semantic-kernel-and-azure-monitor","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/agent-framework\/step-by-step-guide-to-building-a-powerful-ai-monitoring-dashboard-with-semantic-kernel-and-azure-monitor\/","title":{"rendered":"Step-by-Step Guide to Building a Powerful AI Monitoring Dashboard with Semantic Kernel and Azure Monitor"},"content":{"rendered":"

Today we’re featuring a guest author, Akshay Kokane, who’s a Software Engineer at Microsoft within the Azure CxP team. He’s written an article we’re sharing below, focused on a Step-by-Step Guide to Building a Powerful AI Monitoring Dashboard with Semantic Kernel and Azure Monitor: Master TokenUsage Metrics and Custom Metrics using SK Filters<\/a>. We’ll turn it over to Akshay to share more!<\/p>\n

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Semantic Kernel is one of the best AI Framework for enterprise application. It provides cool and useful out of box features. In this blog we will look into how you can integrate Semantic Kernel with Azure Monitors, to meter your Token Usage. Semantic Kernel provides default metrics to meter the token usage.<\/p>\n

Additionally, we will explore Filters in Semantic Kernel and how they can be used to emit custom metrics.<\/p>\n

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Let\u2019s understand first what are types to tokens.<\/p>\n

Types of Token Usages<\/h1>\n