![[Distributed Tracing - NYC] Tracing a Kafka Pipeline Mahmoud Saada Agolo @UberEngineering](https://i.ytimg.com/vi/ZpUMpaWj0i8/maxresdefault.jpg)
Uploaded October 2018 | Updated September 2026, 2 weeks ago
In this August 2018 Distributed Tracing - NYC presentation, Agolo SRE Mahmoud Saada discusses techniques and tips for debugging Kafka pipelines.
In this August 2018 Distributed Tracing - NYC presentation, Agolo SRE Mahmoud Saada discusses techniques and tips for debugging Kafka pipelines.
![[Distributed Tracing - NYC] Tracing a Kafka Pipeline Mahmoud Saada Agolo](https://i.ytimg.com/vi/ZpUMpaWj0i8/mqdefault.jpg "[Distributed Tracing - NYC] Tracing a Kafka Pipeline Mahmoud Saada Agolo
In this August 2018 Distributed Tracing - NYC presentation, Agolo SRE Mahmoud Saada discusses techniques and tips for debugging Kafka pipelines.")
![[Uber Open Summit 2018] Tiling the Earth with Hexagons](https://i.ytimg.com/vi/_-265mfMzl4/mqdefault.jpg "[Uber Open Summit 2018] Tiling the Earth with Hexagons
In order to build a better version of real-time surge pricing, Uber decided to get rid of its geofences and create an algorithm that uses a global, dynamically aggregating hexagon grid. In this talk during Uber Open Summit 2018, product manager Cameron Blume tells the story of why Uber created this global hexagon grid and how the grid works.
Learn more about Uber Open Source: https://uber.github.io/")
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During an October 2018 Distributed Tracing NYC meetup, open source engineer Austin Parker shares some practical lessons for working with spans based on his experience building monitoring and instrumentation at LightStep.")
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During an August 15, 2018 React Native meetup, Uber engineer Arun Nagarajan explains how the Uber Eats engineering team uses React Native to create both mobile and web apps for the platforms three-sided marketplace.")
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In this talk delivered during an Uber Seattle Engineering Meetup in September 2019, Sijie Guo from Apache Pulsar community provided an overview of Apache Pulsar and how it fully leverages Apache Flink unified computation runtime for elastic data processing. Guo also shares the latest integrations between Apache Pulsar and Apache Flink, especially around effectively-once processing and schema integration.")
![[MoneyCon 2019] Controlling Our Own Destiny: Payments as a Service(s) at Airbnb](https://i.ytimg.com/vi/_jxADGmbBgE/mqdefault.jpg "[MoneyCon 2019] Controlling Our Own Destiny: Payments as a Service(s) at Airbnb
The domain of Payments, Finance, and more generally FinTech, is a fast-growing industry that reached record global investment of $111.8B in 2018. The underlying technology that powers this incredible growth is also evolving rapidly. Hosted by Uber, MoneyCon 2019 brought together engineers from leading tech companies to present on the latest topics in payments engineering.
Airbnb Payments has a distributed, service-oriented system for order management and payment processing, and consistency is a challenge in distributed systems. In this talk during MoneyCon 2019, Airbnbs Sophie Behr and John Chew discuss their companys transition to that service-oriented architecture and how they leveraged idempotency to make their systems robust and (eventually) consistent.")
![[XGBoost Meetup] Machine Learning with Large-scale Telematics Data Wayne Zhang & Gorkem Ozkaya](https://i.ytimg.com/vi/_s8ZPVNKsGk/mqdefault.jpg "[XGBoost Meetup] Machine Learning with Large-scale Telematics Data Wayne Zhang & Gorkem Ozkaya
During a January 2019 XGBoost Meetup hosted at Ubers SF office, Uber software engineers Wayne Zhang and Gorkem Ozkaya discuss how we transform telematics datasets into a structured form using a combination of feature engineering, deep learning, and XGBoost.")
![[Uber Marketplace] Marketplace Matching Eoin OMahony](https://i.ytimg.com/vi/a4NuzcYA3pc/mqdefault.jpg "[Uber Marketplace] Marketplace Matching Eoin OMahony
During a May 2018 meetup, data science manager Eoin OMahony discusses how Uber builds technologies to optimize matching on out platform, thereby creating an elastic and efficient network.")
![[Uber Open Source] Engineering an H3-based Geospatial Data Platform at Uber](https://i.ytimg.com/vi/aCj-YVZ0mlE/mqdefault.jpg "[Uber Open Source] Engineering an H3-based Geospatial Data Platform at Uber
During a May 2019 meetup in San Francisco, Uber engineer, Ankit Mehta explains how our Marketplace Intelligence team is building an efficient and scalable H3-based geospatial data platform to facilitate improved user experiences across our products.")
![[Uber Open Summit 2018] Pyro: Deep Probabilistic Programming](https://i.ytimg.com/vi/aLFJ5ERxt2c/mqdefault.jpg "[Uber Open Summit 2018] Pyro: Deep Probabilistic Programming
Pyro is a deep probabilistic programming language built on PyTorch, a GPU-accelerated deep learning framework. Developed at Uber AI Labs by Noah Goodman and team, Pyro is used as a platform for research in modern Bayesian machine learning, where deep neural networks can be used both in models and in inference. To scale to large datasets and high-dimensional models, Pyro uses stochastic variational inference algorithms and probability distributions built on top of PyTorch. The Pyro team works closely with the PyTorch team and many open source collaborators to create a rich, stable toolset for probabilistic machine learning research. During this Uber Open Summit 2018 tech talk, AI Labs JP Chen and Fritz Obermeyer discuss how to use this tool and contribute to Pyros growing open source AI ecosystem.
Learn more about Uber Open Source: https://uber.github.io/")
![[Visualization Nights] Real-time Mapping with Vision Tory Smith (Mapbox)](https://i.ytimg.com/vi/aeFLvwu6wLw/mqdefault.jpg "[Visualization Nights] Real-time Mapping with Vision Tory Smith (Mapbox)
Two of the more salient trends in mapping over the past decade, especially when it comes to connected and automated vehicles, are precision and freshness. During a March 2019 Uber meetup, Mapboxs Tory Smith discusses how his team is building a location platform that enables the creation of living HD maps.")
