If you are going, please come connect with us at booth #306, meet our speakers at the sessions listed below, or come to the Apache Geode Meetup where the winners of over $1500 in prizes will be announced for the Amazing App Challenge for Apache Geode.
If you haven’t signed up yet, you can also use “Pivotal25” to get a 25% discount.
OSCON is one of the world’s greatest platforms for the open source movement—as their website says, “Open source has moved from disruption to default.” Those who have attended know that the cross-disciplinary group of 4000 open source enthusiasts brings a significant energy and network with the creators of the most successful open source projects. Companies like O’Reilly, Mozilla, Nginx, PayPal, Cloud Foundry Foundation, CoreOS, Docker, Twitter, GitHub, Battery Ventures, Netflix, and Google will be presenting.
We also have several Pivots speaking on the topics of:
- Microservices with Spring Cloud and Netflix OSS
- Hands-On Workshop: Building Internet of Things (IoT) Apps on Open Source
- Scalable Graph Analysis with Apache Giraph and Spark GraphX
We are also sponsoring a Meetup—a mini In-Memory Computing Conference at a local hotel.
Here is more information about the topics we are speaking about.
Title: Microservices with Spring Cloud and Netflix OSS
Speaker: Spencer Gibb
Day/Time: Tuesday, 07/21 @ 9:00am–12:30pm
Location: Portland 251
Do you want to build an application using microservices and don’t know where to start? How do services find each other? How do I configure many instances of each service? How do I see what’s going on with my services?
If you’ve ever asked any of these questions, this session will give you some answers using Spring Cloud and Netflix OSS to create microservices that are robust, discoverable, scalable and configurable.
Learn basic concepts about Spring Cloud and Netflix OSS and how they are integrated. We will be building a distributed application using:
- Spring Cloud Config Server (distributed configuration)
- Eureka (service registration and discovery)
- Hystrix (circuit breaker/fault tolerance library)
- Hystrix Dashboard (service health dashboard)
- Ribbon (client side load balancing, including RestTemplate integration)
- Feign (easy rest clients)
- Zuul (routing)
- Spring Cloud Bus (distributed Spring Boot actuator)
- Spring Cloud Security
- Reactive programming patterns
Title: Build Your First Internet of Things App Today with Open Source
Speaker: Fred Melo and William Markito Oliveira
Day/Time: Tuesday, 07/21 @ 9:00am–12:30pm
The Internet of Things requires new applications to consume data that streams in from connected devices, and apply advanced real-time analytics. It also demands the ability to scale horizontally in order to support a large number of devices, while keeping extreme low latency for immediate data insights.
How can you leverage open source software like Apache Geode, Spring XD, Docker, Cloud Foundry, and Lattice to quickly build a complete IoT solution?
In less than half a day, this hands-on workshop will show you how to:
- Ingest data from sensors, small devices, and micro-processors like Raspberry Pi
- Easily create data-streaming pipelines without source code, using a descriptive language
- Transact and process information reliably in-memory, using distributed and scalable technologies
- React to data changes, triggering events, and processors
- Generate real-time analytics based on data coming from different sources and devices
- Deploy and scale applications and services using lightweight containers
Get hands-on training with several open source projects:
- Apache Geode: An open source, distributed, in-memory database for scale-out applications
- Spring XD: A data pipeline system that provides ingest and orchestration of data flows between sources and processing steps at scale
- Docker: An application container engine
- Cloud Foundry: A fully integrated cloud-native platform solution
Title: Scalable Graph Analysis with Apache Giraph and Spark GraphX
Speaker: Roman Shaposhnik
Day/time: Thursday, 07/23 @ 2:30pm–3:10pm
Location: Portland 252
Graph relationships are everywhere. In fact, more often than not, analyzing relationships between points in your datasets lets you extract more business value from your data.
Consider social graphs, or relationships of customers to each other and products they purchase, as two of the most common examples. Now, if you think you have a scalability issue just analyzing points in your datasets, imagine what would happen if you wanted to start analyzing the arbitrary relationships between those data points: the amount of potential processing will increase dramatically, and the kind of algorithms you would typically want to run would change as well.
If your Hadoop batch-oriented approach with MapReduce works reasonably well, scalable graph processing requires more—you have to embrace an in-memory, explorative, and iterative approach. One of the best ways to tame this complexity is known as the Bulk Synchronous Parallel approach. Its two most widely used implementations are available as Hadoop ecosystem projects—Apache Giraph (used at Facebook) and Apache GraphX (as part of an Apache Spark™ project).
In this talk, we will give practical advice on how to get up and running with Apache Giraph and GraphX, start analyzing simple datasets with built-in algorithms, and how to implement your own graph processing applications using the APIs provided by the projects. We will finally compare and contrast the two and lay out some principles of when to use one versus the other.
Meetup: In-memory Computing Meetup
Day/Time: Thursday, 7/23 @ 6:00pm to 9:00pm
Location: Eastlund Hotel, Salon A
Just a few days ago, we created this challenge for creating an app with linear scale using Apache Geode (incubating). Our meetup at OSCON will give an overview of this in-memory database, and we will also be announcing over $1500 in prizes for the winners of the challenge.
Editor’s Note: Apache, Apache Spark, Apache Giraph and Apache Geode (incubating) are either registered trademarks or trademarks of the Apache Software Foundation in the United States and/or other countries.
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