| A Low Code Structured Approach to Deploying Apache Beam ML Workloads on Kubernetes using BeamStack | Charles Adetiloye & Nate Salawe |  |
| A New Local Runner Appears: Deep dive on Prism | Robert Burke |  |
| Accelerating CDC Data Ingestion with Apache Beam: A Qlik-to-BigQuery Journey | Bipin Upadhyaya |  |
| At Least Once Streaming vs Exactly Once: Cost saving vs data accuracy | Ihaffa Murtopo |  |
| Avoid HTTP Request Duplicates with SCIO, a custom AsyncHttpParDoFn and State & Timers | Alberto López Serna |  |
| Beam for Large-Scale, Accelerated ML Inference at Google | Uday Kalra |  |
| Beam SDKs Don't Have to Look the Same | Robert Burke |  |
| Beam YAML and Protobuf | Ferran Fernandez & Austin Bennett |  |
| Beam YAML: Advanced topics | Jeff Kinard |  |
| BeamStack: An open source Framework for running Machine Learning Pipelines with Apache Beam | Olufunbi Babalola |  |
| Breaking the Language Barrier: Easy Cross-Language with Generated Python Wrappers | Ahmed Abualsaud |  |
| Cost Effective Solutions for Beam pipelines in Dataflow | Sharan Teja Malyala |  |
| Cost Optimization of Dataflow Pipelines | Sergei Lilichenko |  |
| Data Lineage in Beam | Rohit Sinha |  |
| Dataflow CI/CD | Surjit Singh |  |
| Dataflow Streaming: The evolution of real-time data processing | Tom Stepp |  |
| Drools ParDo and SCIO: a goodbye microservices tale | Alberto López Serna |  |
| How Beam ML Optimizes Serving Large Models | Danny McCormick |  |
| How we Migrated our JSON DB to a Relational DB using Apache Beam / Dataflow | Lakshmanan Arumugam |  |
| Implementing a Beam SDK: A Deep Dive into the Swift SDK | Byron Ellis |  |
| Improving Stability for Running Python SDK with Flink Runner | Lydian Lee |  |
| Innovating the Data & AI Platform | Yasmeen Ahmad |  |
| Introducing Ordered List States | Shunping Huang |  |
| Introduction to Beam YAML | Jeff Kinard |  |
| Lessons Learned from MLOps for GenAI at Google Scale | Prakash Chockalingam |  |
| Multi-Modal LLM Data Processing with Apache Beam | Konstantin Buschmeier, Jasper Van den Bossche & Iris Luden |  |
| Ordered processing in Apache Beam | Sergei Lilichenko |  |
| Processing Data from a Web API: A step by step guide | Damon Douglas |  |
| Project Shield: How we use Beam to defend democracy and free expression, and how we got started! | Marc Howard |  |
| RAG Data Ingestion and Enrichment Pipeline using Redis and OpenSearch Vector Database in Apache Beam | Ayush Pandey |  |
| RAG Data Ingestion Using Apache Beam | Jasper Van den Bossche & Konstantin Buschmeier |  |
| Real-Time Fraud Prevention with Apache Beam | Hai Sadon |  |
| Realtime Forecasting using Beam | Ravi Magham |  |
| Reuniting the Two Distant Cousins: Calling a Beam Pipeline from an Airflow Job | Sadeeq Akintola |  |
| Scaling Autonomous Driving with Apache Beam | Sayat Satybaldiyev & Arwin Tio |  |
| Streaming Processing for RAG Architectures | Pablo Rodriguez Defino & Namita Sharma |  |
| The SolaceIO connector: how was it made and why | Matt Mays |  |
| Throttling Detection and Reactive Worker Downscaling | Yi Hu |  |
| Transitioning Uber Michelangelo's Batch Prediction from Apache Spark to Ray | Baojun Liu |  |
| Troubleshooting Beam/Dataflow ML Pipelines Related Common Issues | Rajkumar Gupta |  |
| Troubleshooting Python pipelines with process monitoring tools. | Valentyn Tymofieiev |  |
| Usage Billing with BEAM @ LinkedIn | Narayanan Venkiteswaran & Jinjing Bi |  |
| Using Dead Letter Queues with Beam | John Casey |  |
| Using LLMs with Beam and RunInference | Jack McCluskey & Reza Rokni |  |
| using pub/subIO writeMessageDynamic() function in a Python pipeline to use dynamic topic destination | Olu Akinlaja |  |
| Workshop: Multiple Input, Multiple output, Multi-Modal Inference: Streaming ML with Dataflow | Wei Hsia |  |