Resources

MongoDB @ Viacom

How do you build a general purpose data collection tool that can be integrated into 100+ sites, handle 15,000 1K writes/second, and have nearly zero downtime? How do you do that and have an architecture virtually unchanged for 3+ years? Start with using Mongo. Michael Makunas and Ramesh Nuthalapati from Viacom Media Networks, home of MTV, Comedy Central, Nickelodeon, and dozens of other brands, detail the architecture of the voting, polling, and data collection system that powers everything from voting for the MTV Video Music Awards, to sliming celebrities at the Nickelodeon Kids Choice Awards, to contests to meet Miley Cyrus.

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Advanced Document Modeling Techniques from a High-Scale Commerce Platform

The Mozu Commerce Platform’s Content Management System empowers merchants to model, author, publish and query their commerce and website content. In this talk, we will discuss inventive techniques used to build a high-scale Content Management System on MongoDB. This presentation will explore tangible, real world examples of compensating actions, virtual joins and benign writes and wrongs. If you’re ready to move beyond simple document modeling and CRUD operations or if you’d just like to see what is possible with MongoDB, then this talk will provide you with advanced patterns and use cases that take advantage of them.

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I Am MongoDB – And So Can You!

This is the story of a how small team at Rakuten made its first foray into MongoDB and agile development. In this talk, we'll describe how a group of MongoDB newbies approached development, schema design, ODMs, and AWS best practices. We'll discuss how we evaluated MongoDB and other new databases; things we did to speed up development, like automated testing; and how we worked with ops to make this a success. Finally, we'll share some positive outcomes, like how we got to production faster than ever before.

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Starting from Scratch with the MEAN Stack

We created a user-generated content tool called SUB to help a diverse group of teams create dynamic forms and curate responses at The Washington Post. SUB is built on the MEAN stack (MongoDB, ExpressJS, AngularJS, and NodeJS) and ElasticSearch. We will describe what our application is, the internal success it has helped us achieve, and what each layer of the stack does. Next, we will talk about using MongooseJS, how the MEAN stack works within our application, as well as how we wrote custom middleware for MongoDB and ElasticSearch. To wrap up the presentation, we’ll talk about our future with SUB, specifically modular development, our SaaS initiatives and how MongoDB lends itself to fully automated and quick environment set up.

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Standardizing Our Drivers Through Specifications: A Look at the CRUD API

Over the past year, MongoDB's driver team has prioritized publishing specifications for essential driver functionality. In doing so, we hope to improve consistency and collaboration between our internal and community drivers. This session will look at our CRUD specification, which defines an API for querying, aggregation, and write operations: something that every MongoDB developer will interact with at some point. We'll also discuss the challenges in devising a single API that must be applicable to dozens of programming languages.

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Building an AI Startup with MongoDB at x.ai

x.ai is a personal assistant that schedules meetings for you. You speak to amy@x.ai as you would to any other person – and you can have her do all the tedious email ping pong that comes along with arranging a meeting. In this session, we'll describe where our data model began and how it evolved over time. We're solving a problem that involves multiple collections, types of documents and schemas – meetings, participants and emails, for instance – and we often have to merge them together to create different representations of the data. We'll discuss the different queries we use and how we've managed to keep our data model sane. We will also describe the high-level architecture of x.ai, including access patterns from internal Node.js apps using Mongoose and Scala modules for analytics. Finally, the core of x.ai is data science, and we'll discuss how our data science modules interact with MongoDB.

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Chapman: Building a High-Performance Distributed Task Service with MongoDB

When you're building a web application, you want to respond to every request as quickly as possible. The usual approach is to use an asynchronous job queue like Sidekiq, Resque, Celery, RQ, or a number of other frameworks to handle those tasks outside the request/response cycle in a separate 'worker' process. Unfortunately, many of these frameworks either require the deployment of Redis, RabbitMQ, or some other request broker, or they resort to polling a database for new work to do. Chapman is a distributed task queue built on MongoDB that avoids gratuitous polling, using tailable cursors with the oplog to provide notifications of incoming work. Inspired by Celery, Chapman also supports task graphs, where multiple tasks that depend on each other can be executed by the system asynchronously. Come learn how Synapp.io is using MongoDB and Chapman to handle its core data processing needs.

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Modernizing National Health Care Provider Information with Document-Oriented Data Models

As a result of the Health Insurance Portability and Accountability Act of 1996 (HIPAA), HHS/CMS has enumerated all health care providers in United States. Most of the collected information about providers is publicly available. The enumeration system, called the “National Plan and Provider Enumeration System (NPPES)”, manages about 4.5 million health provider records of individuals and organizations. Riddled with problems, NPPES was identified by CMS and HHS as a system in need of modernization to improve usability, scalability and data quality. Part of the overall modernization strategy includes representing health providers as JSON documents and creating RESTFul APIs for record updates and public search. Storing provider information as JSON documents allows CMS to more easily adapt to changing requirements. The NPPES Modernization effort resulted in a collection of open source tools for quickly building a RESTful API atop MongoDB.

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IoT – The Machine Guys Meet the Internet Guys

The sky is the limit in current IoT projections. However, in order to reap the benefits of the IoT opportunity, companies must successfully bridge the culture gap between the manufacturing world and the Internet world. This presentation is a view from the trenches, based on a real world example of success from Bosch Software Innovations.

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Adopting MongoDB for ADP's Next Generation Portal Platform

ADP's Next Generation Portal Platform enables the client service team by bringing together legacy mainframe data, unstructured knowledge bases, online forums and other collaborative technologies into a single experience. It enables a single pane of glass across client data making for a better overall experience and less time spent in training, while engaging born-on-the-web talent in the latest development techniques. This talk will share the journey from technology selection, organizational agility, skill building, sketching out the ROI argument and through to creating a common platform for ADP. We will demo our first application leveraging the platform to fully illustrate how critical MongoDB has been to delivering significant value.

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Testing with Mongo Orchestration

MongoDB focused over the last year on conforming to common APIs and algorithms across drivers. After doing so, we needed a way to validate our consistency. Mongo Orchestration is an HTTP server with a REST API for creating and managing MongoDB configurations on a single host. In this session, we will look at how the drivers team has used YAML to define common integration tests using Mongo Orchestration and how you can use the service to test your own code.

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Diagnostics and Debugging 3.0: The Return of Sherlock Holmes

In an updated repeat of the most popular talk from 2014 MongoDB World, Asya will look at ways to debug performance issues in your MongoDB cluster, using examples from real life, and introducing a variety of tools to help every budding detective.

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