Tracks
| Tracks | Track Chairs |
|---|---|
| Agentic coding | tison, Xuanwo |
| AI Infra | Jerry Tan, junping Du |
| Community | Yin Xu, Richard Lin |
| Data + AI | Juan Pan, Sheng Wu, Jeff Feng |
| Data Lake & Data Warehouse | Lidong Dai, Shaofeng Shi, Zongtang Hu, Jean-Baptiste Onofré, Huaxin Gao |
| Data Storage & Computing | Gang Li,Nicholas Jiang |
| DataOps | William Guo, Lifeng Nie |
| General | Willem Jiang |
| Incubator | Calvin Kirs, Justin Mclean |
| IoT and IIoT | Jialin Qiao, Pengcheng Zheng |
| Keynote | Willem Jiang, Nadia Jiang |
| Lightning Talk | Gang Li,Nicholas Jiang |
| DataOps | Richard Lin |
| Messaging | Jia Zha, Qingshan Lin, Zongtang Hu |
| Microservice | Jun Liu |
| Observability | Huxing Zhang, Sheng Wu |
| OLAP & Data Analysis | Mingyu Chen, Zhijing Lu, Dianjin Wang |
| Rust | tison, Handong Zhang |
| Streaming | Yu Li, Xin Wang |
| Web Application & Framework | Huxing Zhang, Han Li |
Track Details
Agentic coding
Track Chairs : tison, Xuanwo
Agentic coding is moving from demos into production. Across Apache projects, maintainers are asking: How can we integrate LLM-powered agents into our development workflows without compromising code quality, reviewability, or the ASF’s community-driven principles? From code generation and test writing to refactoring, debugging, code review assistance, and release automation, projects across the foundation are experimenting with agents across the entire software lifecycle. These early efforts reveal not only new possibilities but also real friction points.
This track focuses on hands‑on experiences from ASF contributors who are building, integrating, or evaluating code agents. We want to hear what actually works when agents participate in discussions, propose patches, or help with large‑scale maintenance. What breaks, what becomes easier, and what repeatable patterns are emerging? We’re looking for talks that share practical lessons to help the community turn agents from flashy helpers into dependable collaborators.
AI Infra
Track Chairs : Jerry Tan, junping Du
The AI Sub-forum is a professional exchange platform focusing on the integration of artificial intelligence (AI) technology and Apache open-source projects. This sub-forum aims to bring together developers, researchers, and industry users from around the world to explore the application and development of AI technology in the open-source ecosystem, showcase cutting-edge technologies, share practical experience, and promote the implementation of open-source AI solutions across various industries. Topics suitable for this sub-forum include:
- AI-related projects under the Apache Foundation (e.g., focusing on open-source AI frameworks and foundational libraries such as Apache TVM, Mahout, Singa, SystemML, etc.).
- Optimization of individual Apache projects in AI scenarios (e.g., projects like Spark MLlib, Flink ML).
- AI solutions in industrial scenarios based on combinations of multiple Apache projects (e.g., methods for building AI businesses by certain enterprises using a combination of Apache projects).
Community
Track Chairs : Yin Xu, Richard Lin
Why ASF believe in “Community over Code”? There is more to open source than just code contribution.
The Community track covers topics such as community governance model, growing open source project communities, diversity & inclusion, measuring community health, community management tools and data, project roadmaps, case studies, and any other topic around sustaining open source and open source communities.
We welcome you to share your community story with a broader audience.
Data + AI
Track Chairs : Juan Pan, Sheng Wu, Jeff Feng
In the era of Generative AI and Autonomous Agents, data is no longer just a static asset—it is the dynamic fuel for intelligence. The Data + AI track explores the profound convergence where Apache’s battle-tested data infrastructure meets cutting-edge AI capabilities.
We focus on two critical evolutionary paths:
- Infrastructure for AI: How Apache projects are evolving to support the massive scale required by LLMs—covering vector retrieval, real-time RAG pipelines, and unstructured data governance.
- AI-Evolved Data Systems: How AI agents and models are redefining data engineering itself—from autonomous query optimization and self-healing pipelines to AI-native features within established projects.
This track is designed for engineers and architects who move beyond the hype. Join us to dissect concrete architectures, production-grade agentic workflows, and the future of open standards in building reliable, governed, and scalable intelligent systems.
Data Lake & Data Warehouse
Track Chairs : Lidong Dai, Shaofeng Shi, Zongtang Hu, Jean-Baptiste Onofré, Huaxin Gao
Data Lake and Data Warehouse are important solutions for storing and managing data, and they play a crucial role in data management, data analysis, and decision-making. In ASF, there are various projects about Data Lake and Data Warehouse, for example: Apache Hive, Apache Hudi, Apache Iceberg, Apache Paimon, Apache Cassandra, Apache HBase, Apache Cloudberry (Incubating) etc. In this topic, you will get the latest status of data lake and warehouse, best practices the companies use them in the production, and the roadmap of these projects.
Data Storage & Computing
Track Chairs : Gang Li,Nicholas Jiang
Big data is an important branch of computer science,Researches and innovations in the big data storage and computing have never stopped. Big Data is leading and changing various industries and is inseparable from our lives.
Big Data is also a very important part of ASF. ASF has so many big data storage and computing projects, such as Apache Hadoop, Apache Spark, Apache HBase, Apache Ozone, Apache CarbonData, Apache Cassandra, Apache ZooKeeper, Apache Celeborn etc. In this topic, you will learn the cutting-edge trends of these technologies and the practical experience, principles, architecture analysis and other exciting content from first-line users.
DataOps
Track Chairs : William Guo, Lifeng Nie
Featuring some of the most innovative and cutting-edge projects in the Apache ecosystem. This track brings together leading experts and contributors from Apache DolphinScheduler, Apache Airflow, Apache SeaTunnel, Apache Flume, Apache Sqoop, Apache Griffin, Apache Atlas and other DataOps-related projects to explore the latest advances in data operations, automation, and orchestration. Whether you’re a seasoned data professional or just getting started in the field, this track offers something for everyone, with sessions covering topics such as data pipelines, ETL, orchestration, data quality, metadata, and more. Join us at ApacheCon for an exciting and informative deep dive into the world of DataOps.
General
Track Chairs : Willem Jiang
The General track of Community Over Code.
Incubator
Track Chairs : Calvin Kirs, Justin Mclean
The Apache Incubator offers valuable services to projects, referred to as “podlings,” seeking entry into the Apache Software Foundation (ASF). This conference track aims to provide insights and guidance on the incubator journey, enabling attendees to gain a deeper understanding of Apache’s governance and operational practices.
Participants will learn about the process of entering the incubator and progressing towards becoming a Top-Level Project (TLP). Additionally, this track will explore strategies for building an active and diverse open-source community, while ensuring compliance with Apache’s regulations.
IoT and IIoT
Track Chairs : Jialin Qiao, Pengcheng Zheng
IoT and IIoT focuses on how Apache projects empower connected devices, industrial systems, and AI-driven intelligence at the edge. The focus is on real architectures, cross-project integrations, and production experiences across the IoT stack.
Topics include: (1) Embedded platforms and edge AI: real-time OS, device management, and edge-to-cloud synchronization with ML inference for IoT devices. (2) Data infrastructure and time-series intelligence: time-series databases, stream processing, data pipelines, industrial analytics, and emerging time-series foundation models for forecasting, anomaly detection, and predictive maintenance.
We welcome talks from engineers and architects sharing concrete designs, implementation tips, and real-world deployment stories, including large-scale device fleet management, reliable data pipelines for ML, cross-project integration patterns, and building end-to-end intelligent IoT systems using Apache technologies.
Keynote
Track Chairs : Willem Jiang, Nadia Jiang
Keynote track is the main track. we invite many famous people in open source community, they will share their visions and insights about open source.
Lightning Talk
Track Chairs : Richard Lin
Get ready for an exciting lightning talk session! In this fast-paced and dynamic segment, dozens of speakers will take the stage, each delivering inspiring ideas and stories in just 5 minutes. It’s a fantastic opportunity to experience diverse thoughts, perspectives, and innovations. Don’t miss this chance to get inspired and engaged through a rapid succession of impactful presentations!
DataOps
Track Chairs : William Guo, Lifeng Nie
Featuring some of the most innovative and cutting-edge projects in the Apache ecosystem. This track brings together leading experts and contributors from Apache DolphinScheduler, Apache Airflow, Apache SeaTunnel, Apache Flume, Apache Sqoop, Apache Griffin, Apache Atlas and other DataOps-related projects to explore the latest advances in data operations, automation, and orchestration. Whether you’re a seasoned data professional or just getting started in the field, this track offers something for everyone, with sessions covering topics such as data pipelines, ETL, orchestration, data qulity, metadata, and more. Join us at ApacheCon for an exciting and informative deep dive into the world of DataOps.
Messaging
Track Chairs : Jia Zha, Qingshan Lin, Zongtang Hu
With the large-scale landing of serverless, IoT and real-time data technology, event-driven architecture and event streaming technology have been more widely applied, making message queue become more and more important infrastructure. Today, a number of excellent messaging projects have emerged in the Apache ecosystem, including Apache Pulsar, Apache Kafka, Apache RocketMQ, Apache ActiveMQ, Apache Inlong, etc, facing new technological trends, each messaging project is also continuing to evolve.
In this topic, you will learn how different messaging systems make the best technical evolution direction based on their own architectural characteristics, including storage and computing separation, serverless, messaging-streaming integration,and so on. You can also learn how major manufacturers choose the right messaging technology based on their own industry characteristics and business scenarios, and obtain the best practices of messaging technology.
Microservice
Track Chairs : Jun Liu
Whether in the era of Cloud Native or AI-led transformation today, microservices remain the cornerstone of underlying systems, helping us build resilient and scalable distributed systems. Join us as we uncover:
- High-Performance RPC Frameworks – Learn how projects like Apache Dubbo, Apache Thrift, and Apache bRPC are redefining service-to-service communication with speed, efficiency, and interoperability.
- AI-Driven Microservices – Discover how AI and ML are revolutionizing service orchestration, anomaly detection, and autonomous scaling in microservice ecosystems.
- The Next-Gen Service Mesh – Beyond traditional sidecars, we explore the rise of Proxyless Service Mesh and how it transforms observability, security, and traffic management in cloud-native environments.
- Cloud-Native Microservices – From Kubernetes to serverless, we discuss how cloud-native principles optimize microservice architectures for scalability, resilience, and automation.
Observability
Track Chairs : Huxing Zhang, Sheng Wu
As an essential technical capability in the cloud-native era, observability—the ability to analyze and interpret a system’s operational state—has gained increasing importance. Especially in today’s widespread adoption of distributed environments, observability platforms serve as the cornerstone for ensuring software system stability.
OLAP & Data Analysis
Track Chairs : Mingyu Chen, Zhijing Lu, Dianjin Wang
With the advent of the big data era, the application of data analysis and OLAP technology in enterprises is becoming more and more widespread. In order to promote communication and sharing in this field in the industry, we have set up the OLAP and Data Analysis Track. We hope to invite experts and scholars in the industry to share their research results, practical experience, and latest developments in data analysis and OLAP technology. In ASF, there are various projects about OLAP and data analysis, for example: Apache Doris, Apache Druid, Apache Kylin, Apache Pinot, Apache Impala, Apache Calcite, Apache Cloudberry (Incubating), etc.
The topic can cover research progress, application cases, best practices, performance optimization, and other aspects of data analysis and OLAP technology. We believe it will greatly bring great benefits to the attendees.
Rust
Track Chairs : tison, Handong Zhang
The Rust ecosystem is flourishing. Many ASF projects now offer Rust SDKs, and several new ASF projects are primarily written in Rust, such as Apache OpenDAL and Apache Teaclave, among others.
The Rust Track aims to share the evolution of Rust projects and integrations within the ASF and broader open-source ecosystem. It will demonstrate how ASF projects provide excellent Rust implementations and illustrate how the incubator helps Rust projects develop healthy communities under the guidance of The Apache Way.
Streaming
Track Chairs : Yu Li, Xin Wang
Streaming data processing is a big deal in big data these days, businesses crave ever-more timely insights into their data, and what was once a ‘batch’ mindset is quickly being replaced with stream processing. More and more companies, small and large, are rethinking their architecture with real-time context at the forefront, and starting to build their streaming platforms with powerful open source engines such as Apache Flink, Apache Spark, Apache Kafka, Apache Pulsar, Apache Storm, Apache StreamPark, Apache Paimon etc.
In this topic, you will not only learn about the practical experience of first-line users in applying these Apache projects to their in-production environment, but also the latest developments in the ecology of these Apache projects, and visions on where streaming technology is heading in the future.
Web Application & Framework
Track Chairs: Huxing Zhang, Han Li
With the growing demands of modern web applications, building efficient, scalable, and secure web systems has become a core objective of technological development. Within the Apache ecosystem, numerous outstanding projects have emerged, ranging from classic web servers (such as Tomcat, HTTP Server) to essential development tools (like Apache Commons, FreeMarker, Echarts), as well as frameworks specializing in enterprise-level integration and security (e.g., Camel, Shiro). These projects play critical roles in modern web architectures.
Here, you will gain in-depth insights into the latest developments of these projects, learn best practices for production environments, and explore their future directions.