• Distributed Databases: Deep Dives and DIYs

    Uber Engineering NYC welcomes the tech community to join us for an evening of refreshments, fun conversation and deep dive presentations on modern distributed databases. We're joined by our friends at CockroachDB, represented by their co-founder Peter Mattis who will kick off the evening with a presentation on parallel commits in CockroachDB. He will be followed by Uber engineer Richard Artoul, who will provide a practical and accessible introduction to the fundamentals of distributed databases. Thanks to our host, Uber Eng NYC, there'll be plenty of opportunity for Q&A, networking, and pizza so come mix with the wonderful NYC tech crowd at Uber's Midtown office. *Schedule* 5:30PM - Doors Open 6:00PM - Introduction by Simon Robb 6:10PM - Parallel Commits by Peter Mattis 6:40PM - Q&A 7:00PM - A DIY Distributed Database in a Weekend by Richard Artoul 7:30PM - Q&A 7:45PM - Networking 8:30PM - Event Ends Parallel Commits - Peter Mattis, CockroachDB In this talk, Peter will discuss the need for parallel commits, explore how the protocol works and explain the benefits it provides. He will conclude his presentation by relating the protocol back to some foundational theory in CS. A DIY Distributed Database in a Weekend - Richard Artoul, M3DB M3DB is Uber's open-source, distributed TSDB designed for massive write throughput. Richard Artoul from the M3DB team will present his talk, "A DIY Distributed Database in a Weekend," which explains how he was able to build a horizontally-scalable high-throughput TSDB in a weekend with the help of FoundationDB. This presentation explores many of the important concepts underpinning M3DB's architecture, and is an excellent primer for getting started building your own databases. *About the speakers* Peter is the co-founder of Cockroach Labs where he works on a bit of everything, from low-level optimization of code to refining the overall design. He has worked on distributed systems for most of his career, designing and implementing the original Gmail backend search and storage system at Google and designing and implementing Colossus, the successor to Google's original distributed file system. In his university days he was one of the original authors of the GIMP and is still amazed when people tell him they use it frequently. Richard Artoul is a software engineer in the Core Storage organization at Uber and the tech lead on the M3DB project, Uber's open-source distributed time series database.

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  • Tales of Instrumentation

    Uber

    *** RSVP HERE: https://www.meetup.com/Distributed-Tracing-NYC/events/264063629/ *** After a bit of a break, our Distributed Tracing - NYC meetup is back at the Uber NYC office! Refreshments will be available at 6:20 p.m. and the talks will begin at 7:00 p.m. Anyone involved in distributed tracing knows that the journey starts with getting high quality instrumentation into your applications. So join us for some Tales of Instrumentation. Agenda: 6:30: Networking 7:00: Talk 1 - Instrumentation: breadcrumbs for a dark path in the future 7:45: Talk 2 - Introduction to OpenTelemetry 8:30: Networking 9:00: Lights out ** Instrumentation: breadcrumbs for a dark path in the future ** Presenter: José Carlos Chávez (https://github.com/jcchavezs) In observability, instrumentation is the task of adding signal emitters in our code for further analysis or debugging. Instrumenting a service is the first step towards understanding a system state while operating it but in practice it really depends on how much the libraries one consume can be instrumented. In this talk we will explore the importance of instrumentable code, patterns for writing instrumentable libraries, means for instrumentation, trade offs and lessons learned on the topic. José Carlos Chávez is a Software Engineer at Expedia, a Zipkin team member and a Mathematics student at the University of Barcelona. He enjoys working with APIs and distributed systems, and is the author of official libraries for Zipkin and OpenTracing. When not working with code, you can find him sipping on craft beers. ** Introduction to OpenTelemetry ** Presenter: Austin Parker (https://github.com/austinlparker) You may have heard of OpenTelemetry, the next major release of OpenTracing and OpenCensus, but you may wonder what it actually is, and how it's going to impact you. In this talk, you'll learn about what led to this project, how it builds on existing open source observability frameworks, and how you can join the community and get involved with the next generation of open source observability. Austin Parker is an Open Source Engineer at LightStep and a maintainer on the OpenTelemetry and OpenTracing projects. Additionally, he's the co-host and producer of On-Call Me Maybe, the world's best-named podcast about building and operating reliable software. You can find him on Twitter @austinlparker A big thanks to the event's host, Uber (https://eng.uber.com), and sponsor, Lightstep (https://lightstep.com)! ** Call for speakers ** If you have learnings and insights you'd like to share, we'd love to hear from you. Let us know if you're interested in speaking at an upcoming event!

  • Platform Governance and the Future of Work

    Speaker, Arun Sundararajan, is the Harold Price Professor of Entrepreneurship and Technology at NYU Stern School of Business. As the lines between traditional industrial-age corporations, platforms and governments are blurred by advances in digital technology and the increasing centrality of algorithms in business and society, I discuss six critical governance choices (neutrality, compliance oversight, transparency, fairness, due process and IP) that platforms like Uber, Facebook and Amazon must make, and how to manage the evolving relationship between individuals and institutions in a way that catalyzes micro-entrepreneurship and lowers inequality. Arun’s best-selling book, “The Sharing Economy,” published by the MIT Press, was the winner of a 2017 Axiom Best Business Books Award, and has been translated into five languages. Arun’s work studies how digital technologies transform business, government and civil society. His recent focus has been on the sharing economy, the future of work, platform governance, the business of artificial intelligence, the digital transformation of retail, and digital trust. Arun is a member of the World Economic Forum’s Global Future Council on Technology, Values and Policy. He helps tech companies figure out strategy and regulation, and non-tech companies with forecasting and addressing changes induced by digital technologies Agenda: 5:00PM - Doors Open / Network & Mingle 6:00PM - Platform Governance and the Future of Work (Arun) 6:40PM - Q&A with Arun and Marc Donner (Director of Global Tech Sites, Uber) 7:00PM - Doors Close

  • Open Source Meetup -Uber x Jet x Spotify

    Please RSVP here: https://uberxjetoss.splashthat.com/ Join us for a series of lightning talks on open source software in the enterprise. There'll be food, drinks, and plenty of opportunities for networking. This event is hosted by Uber Technologies in partnership with Jet.com and Spotify. Uber helps millions of people move towards opportunity every day in over 600 cities around the world. Jet.com is the place to shop curated brands and city essentials online. If you would like to attend the event please rsvp at : https://uberxjetoss.splashthat.com/ Learn more about Uber Open Source: www.opensource.uber.com

  • Distributed Tracing with Jaeger & Building Golang Microservices with FX @Uber

    * RSVP here - https://www.meetup.com/Microservices-NYC/events/260829807/ * 6:00pm - Doors Open, Food and Drinks, Networking 6:15pm - Tech Talk One: "How Uber Uses Jaeger for Distributed Tracing" * Abstract: Distributed tracing has become a must-have tool for any organization that operates systems with many microservices. However, from our experience at Uber, we found that the classic use case of using tracing for latency analysis is not the only use for distributed tracing. Instead, we found the greatest value of tracing is in getting a handle on the complexity of an architecture composed of thousands of microservices. In this talk, we demonstrate the utility of tracing by walking through different applications of tracing at Uber. * Speakers: Prithvi Raj https://www.linkedin.com/in/vprithviraj/ is an engineer on the Jaeger team at Uber & Yuri Shkuro https://www.linkedin.com/in/yurishkuro/ is a software engineer at Uber, working on distributed tracing, observability, reliability, and performance problems; author of the book "Mastering Distributed Tracing"; creator of Jaeger, Uber's open source distributed tracing system (a CNCF project); coauthor of the OpenTracing standard (also a CNCF project); invited expert in W3C Distributed Tracing Working Group. 7:15pm - Tech Talk Two: "Fx: A Dependency Injection based Application Framework for Golang" * Abstract: Golang is the primary choice for developing back-end services at Uber. To provide faster development, reusability, and extensibility, we have developed the Fx framework which provides a dependency injection framework for microservices and yarpc - a message passing framework for Golang. Both of these frameworks are open source and currently powering 1000+ Go microservices at Uber. During this talk, we will walk through developing a backend service in Golang using Fx+yarpc and demonstrate how to use Fx for dependency injection, application lifecycle management, and outbound calls over multiple encoding and transport protocols. * Speaker: Keshav Nandan https://www.linkedin.com/in/keshav-nandan-58871b26/ is a software engineer at Uber, working on backend systems and data pipelines which power marketplace metrics for Uber Eats. He has experience developing back-end services in Golang using the Fx+yarpc framework and absolutely loves it. 8:00pm - Wrap Up and Networking

  • Visualization Nights: An Urban Planning Workshop with Uber Movement & Kepler.gl

    Uber Movement has recently released a new dataset, segment-level speeds, which has wide applicability towards urban and transportation planning. Combined with the capabilities of Kepler.gl and other datasets, the possibilities for data-driven planning are enormous. Join us for a hands-on workshop where we explore these opportunities as part of the Visualization team’s ongoing Visualization Nights series! Please bring your laptop! Agenda 5:30PM - Doors Open 6:10PM - Introduction 6:30PM - Tutorial #1 6:45PM - Tutorial #2 7:10PM - Showcase + Q&A 7:40PM - Networking 8:30PM - Event Ends Introduction The Uber Visualization team will give a quick introduction to the new Uber Movement Street Speeds product and a brief overview of Kepler.gl. Tutorial #1 We will start with a basic tutorial where we walk through how to download the Street Speeds dataset and visualize it in Kepler.gl. We will pick two different time periods of Uber Movement speeds data and explore spatial-temporal insights. Tutorial #2 Next, we will dive into a more advanced tutorial where we will combine data sources for more complex insights. We will visualize the layers of additional data sources (for example, datasets regarding transit, safety, and economic development, among others.) and explore more complex urban challenges. DIY At the end of the workshop, you will have an opportunity to create your own story with a focus on transit datasets. We will also show you how to export and share your beautiful insights with the world! Optional showcase of work + Q&A Note: We must collect your first and last name for security reasons prior to the event. You will also need to sign an NDA when entering the building.

  • The Brooklyn iOS April Meetup @ Uber

    * RSVP to the Meetup here: https://www.meetup.com/The-Brooklyn-iPhone-and-iPad-Developer-Meetup/events/259963436/ * Doors open at 6, and presentations will begin around 6:30. Please bring a photo ID to check in on the ground floor reception and then again through Uber's reception on the 12th floor. ~Erich Graham~ Erich is a staff engineer at Uber where he works to make writing code for the Uber Eats iOS app as delightful as ordering food on the Uber Eats iOS app. He previously worked at Yahoo Finance and was a graduate of the inaugural class at Cornell's NYC Tech masters program in Computer Science. His favorite app is his very own Bike Share NYC, with which he's logged over 5,000 miles on a Citi Bike.

  • Data Engineering and Machine Learning behind Uber Eats Marketplace

    *** RSVP here: https://www.eventbrite.com/e/machine-learning-and-data-analysis-behind-uber-eats-dispatch-system-tickets-57637042947 *** Uber Eats works with over 160,000 restaurants in 350 markets in 35 countries across 6 continents to deliver your favorite foods fast - averaging 31-minutes global delivery time. Our massive scale and global presence bring unique and challenging data science challenges. With great problems come the need for top talent, diverse perspectives, and an appetite for challenging the food delivery status quo. This event is about celebrating and sharing some of the work done by data scientists and engineers on the Uber Eats team. Attendees will learn about how we apply machine learning, data science, and data modeling to real-time data analysis, and time prediction, as well as outfit the Uber Eats mobile architecture to ensure the health and efficiency of our three-sided marketplace between eaters, driver-partners, and restaurant-partners. In addition, the event will feature a discussion and Q&A that will give audience members a firsthand look at what it's like to work in one of the largest data science organizations in the industry on some of the field’s most interesting challenges. Schedule: 6:00-6:30pm: checkin & food/snack 6:30-6:40pm: welcome and intro 6:40-7:10pm: Talk1: Real-time data analytical application for Uber Eats, by Rob Cornacchia, Kevin Kim To ensure the health of hundreds of Uber Eats markets around the world, we have designed and built real-time tools to monitor and optimize our marketplace. We'll go over the open source technologies we use at Uber for real-time data analytics. Then, we’ll discuss the current web applications we’ve built for our global operations teams and the next generation of tools being built for the platform. 7:10-7:40pm: Talk 2: Time Prediction for the Uber Eats Marketplace, by Katherine Chen, Zi Wang In an ever-growing market for food delivery services, the ability to accurately predict delivery times is paramount to customer satisfaction and retention. Additionally, estimates are important on the supply side as they inform when to dispatch driver-partners. In this talk, we’ll discuss the technologies and data science we use to Uber Eats to address these challenges. 7:40-8:10pm: Talk 3: Balancing marketplace efficiency and user experience, by Pei Wu, Jeff Hu. Bringing the best food delivery experience to Uber Eats customers is our top priority. Meanwhile, improving marketplace efficiency is also critical to further scale the Uber Eats business. In this talk, we will go over the unique engineering challenges and opportunities to build a better dispatch experience in the Uber Eats three-sided marketplace. We will also dive into Uber's mobile architecture, featuring a design that was built for the scalability and reliability. 8:10-8:30pm: Mingle, Q&A, and close. Directions: Close to the BDFM, 123 & NQR Or better yet, take an Uber! Join Uber Eng NYC meetup group for more tech meetups hosted by Uber Eng.

  • Building A Tracing System at Dropbox and Deriving Insights from Traces

    ***RSVP here: https://www.meetup.com/Distributed-Tracing-NYC/events/258933554/ *** We're very excited to announce our third Distributed Tracing - NYC meetup at the Uber NYC office! Pizza, beer and wine will be available at 6:20 p.m. and the talks will begin at 7:00 p.m. First talk: Building a Tracing System at Dropbox Presenter: Ross Delinger Distributed tracing is a challenge that is both technical and organizational. In this talk, we’ll explore how Dropbox is solving these challenges. We’ll also cover how our tracing infrastructure has evolved incrementally to keep pace with the migrations and architecture changes required by Dropbox’s move to a service-oriented architecture. Ross is an SRE at Dropbox and leads the Reliability-Frameworks team, which is building a distributed tracing solution. Prior to that Ross worked on a variety of observability and service infrastructure tooling on the Traffic team at Dropbox. Second talk: Gaining Insights from Distributed Traces Presenter: Joe Farro In this talk, we'll explore several techniques for deriving value from distributed traces. The techniques discussed will be human-centric; our objective is to gain insight into our software system and to facilitate decision-making. We'll cover the strengths and weaknesses of each approach, and how they relate to one another. We'll finish with a look at several emerging directions and how they relate to the techniques covered. Joe is a software engineer and member of the Observability team at Uber. He's a core contributor to the Jaeger and OpenTracing CNCF projects. A big thanks to the event's sponsor and host (and my employer), Uber! *Call for speakers* If you have learnings and insights you'd like to share, we'd love to hear from you. Let us know if you're interested in speaking at an upcoming event!

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  • Data Science Behind Uber Eats Dispatch System

    ***RSVP to the event here: https://www.eventbrite.com/e/data-science-behind-uber-eats-dispatch-system-tickets-51734366884 Uber Eats works with over 160,000 restaurants in 350 markets in 35 countries across 6 continents to deliver your favorite foods fast - averaging 31-minutes global delivery time. Our massive scale and global presence bring unique and challenging data science challenges. With great problems come the need for top talent, diverse perspectives, and an appetite for challenging the food delivery status quo. This event is about celebrating and sharing some of the work done by data scientists and engineers on the Uber Eats team. Attendees will learn about how we apply data science and data modeling to ensure the health and efficiency of Uber Eats' three-sided marketplace. In addition, the event will feature discussion and Q&A that will give audience members a firsthand look at what it's like to work in one of the largest data science organizations in the industry on some of the field’s most interesting challenges. Schedule: 6:00-6:30pm: checkin & food/snack 6:30-6:40pm: welcome and intro 6:40-7:10pm: Talk1: Modeling Uber Eats Dispatch, by Matt Hlavacek How does Uber Eats determine the best way to deliver your food? What makes a good delivery? The Uber Eats Logistics Data Science team creates algorithms to balance the often competing interests of the eater, courier, and restaurant when getting the food to your door. Learn their fundamental optimization and machine learning challenges and how they're thinking about solving them. 7:10-7:40pm: Talk 2: The Uber Eats Marketplace Simulator, by Jason Wien, Lu Bai Developing algorithms for a dynamic, highly-interconnected marketplace presents a unique set of both data science and engineering challenges. We dive deeper into some of these challenges and describe how we address them using the Eats Marketplace Simulator. 7:40-8:00pm: Talk 3: TBD 8:00-8:30pm: Mingle, Q&A, and close. Directions: Close to the BDFM, 123 & NQR Or better yet, take an Uber!

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