Monika Mundra
Cloud Architect, Building the Future on the Cloud
Atlanta, Georgia, United States
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With 15+ years of experience managing and delivering software projects, I have worn many hats - including Program Manager, Project Manager, Lead Scrum Master, DevOps Manager, and hands-on SharePoint and Angular Developer. My core strength lies in applying Agile and SAFe methodologies to deliver high-quality outcomes within tight timelines and budgets. Beyond delivery, I bring experience in pre-sales activities such as crafting client proposals for service offerings and initiating new client relationships. I pride myself on strong communication and stakeholder collaboration, consistently driving IT projects to success and exceeding client expectations. Whether leading teams or engaging clients, I focus on turning complex, high-pressure programs into predictable, repeatable delivery.
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From Logs to Clarity: Operationalizing AI Agent Observability on Azure AI Foundry
Moving AI agents from pilot demos to enterprise production requires a fundamental shift in operational monitoring. Unlike traditional deterministic applications, AI agents are non-linear, stateful, and autonomous—frequently calling external tools, branching on intermediate reasoning, and coordinating across multi-agent workflows. Standard log metrics simply fall short.
In this session, explore how Azure AI Foundry bridges this gap by unifying agent execution with enterprise-grade observability via OpenTelemetry and Azure Monitor Application Insights. We will break down the spectrum of tracing approaches—from no-code out-of-the-box visibility with Microsoft Agent Framework, to low-code tracing with Semantic Kernel, LangChain, and LangGraph, to pro-code custom instrumentation with OpenAI Agent SDK. You’ll leave with actionable architecture patterns to achieve end-to-end visibility into token usage, tool invocations, decision trees, and multi-agent interactions in production.
Low Code API Management in Azure : Leveraging Complex Scenarios
This session, "Low-Code API Management in Azure: Leveraging Complex Scenarios," provides an in-depth exploration of Azure's Low-Code API Management capabilities, focusing on efficient management of intricate API scenarios. Attendees will learn how to streamline multi-api integration, implement custom security policies, leverage advanced analytics and logging, and integrate CI/CD pipelines. Through actionable examples and case studies, developers will gain expertise in designing and implementing scalable Low-Code API Management solutions in Azure, ensuring secure, reliable, and high-performance APIs. Key takeaways include mastering complex scenario handling, simplifying API development and deployment, and applying best practices for API security, analytics, and development.
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive : Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability Deep Dive :Correlating logs across azure monitor, app insights and distributed service
Observability for AI Applications on Azure
How to monitor prompts, token usage, latency, failures, and application performance using Azure Monitor, Application Insights, and Log Analytics.
Cost Control in the Age of Agentic AI: APIM Policies for Token Economy
Agentic AI broke your cost model. A single autonomous agent can burn more tokens in an afternoon than an entire department did last quarter — and by the time it shows up on the invoice, the money is gone. Traditional API governance was never designed for consumption that's non-deterministic, streaming, and priced per token.
This session shows how to turn Azure API Management into a real cost-control plane for AI workloads: enforcing token budgets, attributing spend to actual consumers, and building the telemetry that makes chargeback possible. Everything demonstrated comes from production deployments, including the parts that broke.
Monika Mundra
Cloud Architect, Building the Future on the Cloud
Atlanta, Georgia, United States
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