Name: IN-PERSON: AI, Observability, and Data Streaming
Start: 2025-09-02T17:00:00-04:00
End: 2025-09-02T19:00:00-04:00

**IMPORTANT PLEASE RSVP @ [https://lu.ma/gicotw9t?tk=tOFvg2](https://lu.ma/gicotw9t?tk=tOFvg2)**

​**Session 1: Accelerating AI-Powered Applications to Production: Building IDPs to Amplify Developer Velocity**
​AI-empowered developers are shipping applications faster than ever but infrastructure is still the bottleneck. While developers can now generate entire application features in minutes using AI tools, provisioning the cloud infrastructure to run those applications often takes days or weeks. How can platform teams build Internal Developer Platforms (IDPs) that match the velocity of AI-powered development?
​In this talk, I'll share how to design IDPs specifically optimized for AI-empowered application developers who need to move from idea to production at unprecedented speed. We'll explore how the five essential IDP components: abstractions, blueprints, workflows, security guardrails, and self-service all must evolve to support the new reality of AI-accelerated development cycles.
​**Speaker: Adam Bell, Community Engineer at Pulumi**

​**Session 2: Beyond the Black Box: Gaining Observability into AI-Powered Applications with Amazon Bedrock**
​Amazon Bedrock and Amazon Nova model enables you to build AI powered applications and when they are running in production, this can encounter errors or even simply a better visibility into how the model is performing is important. In this session, we will look at why monitoring is the key for AI applications and when using Bedrock with applications, how AI monitoring gives you insights not only about errors but also AI model performance.
​**Speaker: Jones Zachariah Noel N, Sr Developer Relations Engineer at New Relic**

​**Session 3: Build a real-time semantic search platform using principals for AI/ML with Stream Processing**
This talk explores how to build a real-time semantic search platform by combining AI/ML techniques with stream processing frameworks. It demonstrates how to extract meaningful insights from continuous data flows to deliver intelligent, low-latency search experiences.

​**Speaker: Zach Hamilton, Staff Solutions Engineer at Confluent**

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DISCLAIMER
No catering for those under age of 21.
If you want to speak at or host a meetup, please email community@confluent.io

Alice Richardson

Apache Kafka® ATL

Confluent

Technology

Software Development

Open Source

Apache Kafka

Hadoop

Apache Spark

Big Data

Jarek Jarcec Cecho

Matt Jackson

Ravi Mudigonda

Raheem Daya

Ketan Dave

Darryl Jordan

Spencer Hayes

IN-PERSON: AI, Observability, and Data Streaming 

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IN-PERSON: AI, Observability, and Data Streaming

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