Category: Cloud & Big Data

Talks that are part of the Cloud & Big Data track.

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Cloud & Big Data

The Art of Clean Code

Victor Rentea is a  Senior Software Engineer, Tech Team Lead, Independent Consultant and Passionate Trainer on Java Enterprise technology and design.

How can you write beautiful, elegant clean code? What guidelines should you follow? How should a professional engineer behave in code? This classic training session, held over 10 times until now, will cover the major topics of what Clean Code means. No matter your favourite programming language or your experience level, this intense hour will leave you with a lot of ideas on how to improve your coding style.

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Cloud & Big Data

Adrien Blind Interview

Q. You’re speaking at Voxxed Days Bucharest in March. Tell us a bit about your session. 

I think Docker is a best fit to achieve Continuous Delivery: far beyond being an app isolation technology, it also represents a new universal type of app artifact; it also have organizational impacts. It suits perfectly the “You build it, you run it” statement from Werner Voegls. My session attempts to exposes this holistic view of Docker, based on my experimentation at Societe Generale.

Q. Why is the subject matter important?

Continuous delivery is not only something cool, satisfying tech people: it really helps the IT department delivering more rapidly and secuerly value to its customers, bringing them a competitive advantage to run their business. Moreover, all the subsequent automation it implies contributes to lowering deployment and run costs of applications.

Q. Who should attend your session?

Everybody! This presentation is built to propose different layers of outcomes, helping beginners to get the global picture, while providing more advanced tricks for veterans.

Q. What are the key things attendees will take away from your session?

With this session, you’ll understand continuous delivery pipeline principles, and be able to start building your own delivering Docker artifacts (here illustrated with the Jenkins ecosystem).

Q. Aside from speaking at Voxxed Days Bucharest, what else are you excited about for 2016?

Regarding the technical landscape, I’m quite excited by the announcements regarding Unikernels, growing interest of people for ARM micro platforms, or even the DWave’s quantum computer: does this slowly prefigures future the end of traditional systems? I’m also quite interested by VIV technology, which may revolutionize some human-internet interactions in the upcoming years.

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Cloud & Big Data

Continuous Delivery at Docker age

Continuous Delivery at Docker age

adrien-blind

Adrien is a former consultant from Octo Technology, a french IT consulting firm. He joined Societe Generale as a DevOps coach and Infrastructure as Code product owner, driving the developers new needs toward infrastructure and helping them to leverage on those new principles and tools. Fond of Docker, he’s also co-organizer of the Paris Docker Meetup.

Reduced time-to-market, calmer deployments or possible source of savings … Promises of continued deployment are numerous.

To achieve this, the IT department can rely on a wide range of practices such as Agile, collaboration and automation preached by the DevOps culture, or modern architecture patterns such as micro-services. All of this is also backed by an entire ecosystem of appropriate tools, among which we find particularly Docker.

In this session, I propose to explore a fully automated continuous deployment process, leveraging on Docker containers. I’ll also present some recommendations for for the application architecture, and discuss roles and responsibilities shifts, which often accompanies such an approach.

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Cloud & Big Data

Galder Zamarreño interview

Q. You’re speaking at Voxxed Days Bucharest in March. Tell us a bit about your session.

The session is about how to use Java 8 Stream API to process and analyse data stored in distributed Infinispan data grid instances. The talk will start with a short presentation about Infinispan and Java 8 Stream API and then it will follow with a demonstration on how to combine both to do distributed data processing.

Q. Why is the subject matter important?

The Java 8 Stream API is a very popular API to get started with processing data in a single node environment. Infinispan has extended the Java 8 Stream API so that lambda functions are shipped to where data is located, rather than bringing all data to a single node, and hence it can take full advantage of the parallel data processing capabilities of multiple nodes.

Q. Who should attend your session?

This is a beginner talk for Java developers and architects interested in data processing and distributed computing. Previous knowledge of Java 8 Streams and Map/Reduce is desirable but not mandatory.

Q. What are the key things attendees will take away from your session?

The key message is that the Java 8 Stream API can be extended to process large data sets in a distributed environment, taking advantage of the parallelism offered by multi-node environments. The attendees will also learn about the differences of Java 8 Stream API and other data processing APIs exposed by Infinispan.

Q. Aside from speaking at Voxxed Days Bucharest, what else are you excited about for 2016?

I’m very excited about enhancements we’ll be doing to a new Functional Map API we designed for Infinispan 8 which takes advantage of lambdas functions to define how data is modified and manipulated. Being able to distributed the functions that lead to a particular state as opposed to distributed latest values is a very powerful concept, enabling strong eventual consistent data structures such as conflict-free replicated data type (CRDT).

I’m also very excited with the work we’ve been doing at Infinispan to integrate with other data processing projects at Apache, such as Hadoop, Spark, etc., so you can use Infinispan as an alternative backend for the data. These integrations expose Infinispan’s in-memory data grid capabilities to a new audience expanding our user base.

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Cloud & Big Data

DuyHai Doan Interview

Q. You’re speaking at Voxxed Days Bucharest in March. Tell us a bit about your session.

My session is about Apache Zeppelin, an open-source web-based notebook for your Big Data (or Small Data) technologies.
In this talk, I will show all Zeppelin features, highlight its modular architecture and show you how to develop your own interpreter/plugin for your technology to work with Zeppelin, if it doesn’t already exist!

Q. Why is the subject matter important?

With the rise of Big Data, the need for a easy-to-use front-end is more and more a must-have. And Zeppelin is gaining momentum right now, being used a lot for live coding demo but also as a tool for Data Scientists working with Spark.

Q. Who should attend your session?

Anyone working in the Big Data space, developer or end-user (consumer) of Big Data projects

Q. What are the key things attendees will take away from your session?

a. Zeppelin offers a free front-end for your big data project
b. Zeppelin architecture is modular enough so that you can add your own interpreter/plugin
c. The community is growing and proposing an impressive list of plugins for all major Big Data technologies (Cassandra, ElasticSearch, Flink, …)

Q. Aside from speaking at Voxxed Days Bucharest, what else are you excited about for 2016?

I’m excited about new features to come in Apache Zeppelin that will make it the default choice front-end for many projects

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Cloud & Big Data

Our Cloud & Big Data Track

Cloud & Big Data

Do you want to stay up to date with cloud technologies? Do you want to know cutting edge frameworks used in big data processing ?

Come and find out from rock star speakers from all across Europe.

We will cover:

Connecting the Unconnected: IoT Made Simple – How to connect and collect data from all your devices

Distributed Data Processing with Infinispan and Java Streams – How to leverage Java 8 streams with Infinispan

ToroDB: NoSQL & relational Java database with SQL analytics – use SQL and NoSQL in the same database

Modular Infrastructure for IoT Applications – microservices in the IOT context

Apache Zeppelin, the missing GUI for your Big Data back-end – a visual interface for your big data trends

Our Agenda

Start Speaker Name Session title
11:00 Jean-Pierre (JP) LeGoaller Connecting the Unconnected: IoT Made Simple
12:00 Galder Zamarreño Distributed Data Processing with Infinispan and Java Streams
14:00 Alvaro Hernandez ToroDB: NoSQL & relational Java database with SQL analytics
15:00 Michal Stehlik Modular Infrastructure for IoT Applications
16:30 DuyHai DOAN Apache Zeppelin, the missing GUI for your Big Data back-end
17:30 TBD TBD

 

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Cloud & Big Data

Modular Infrastructure for IoT Applications

Modular Infrastructure for IoT Applications

Michal - Modular Infrastructure for IOT Applications

Michal joined IBM in 2013 as a Java Senior Developer, after earning over 5 years of experience in Java development, working across multiple technologies for companies with projects dedicated to transportation and entertainment industry. Currently he is working on Home Automation project for internationally leading provider of integral lighting solutions in Austria. He is a passionate engineer with a wide range of interests from electric circuits and microcontrollers to Internet of Things and cloud solutions.

Internet of Things (IoT) is a buzzword which has had everyone talking over the last couple of years. My presentation will demonstrate how to build a simply extensible and widely configurable gateway allowing protocols translation (HTTP with Apache Http Components, Serial and I2C with Pi4J and libbulldog). Compared with other existing products on the market, the proposed solution brings great performance even on multicore ARM processors using Fork/Join Framework, but also a simple manner to write and manage your own extensions via RESTfull API (by integrating Jetty-Jersey-Genson). The iGate [IotaGate] resource is not just one-purpose tool, but a reusable solution to integrate M2M and SCADA offerings with web portals or other tools such as IBM Bluemix, IBM Intelligent Operation for Transportation or custom complex solutions based on IoT data acquiring and control.

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Cloud & Big Data

Connecting the Unconnected – IoT Made Simple

Connecting the Unconnected IoT Made Simple

jean-pierre - Connecting the Unconnected IoT Made Simple

Jean-Pierre (JP) is senior manager of solutions architecture at Amazon Web Services, and has worked as an AWS solutions architect since 2011. Prior to AWS, he worked in the US as an IT director for an e-commerce startup and as a software development manager for Oracle and Teradata.

Connecting physical devices to the cloud can enhance the user experience. AWS IoT is a new managed service that enables Internet-connected things (sensors, actuators, devices, and applications) to easily and securely interact with each other and the cloud. In this session, we will discuss how constrained devices can send data to the cloud and receive commands back to the device. Devices can securely connect using MQTT, HTTP protocols and developers can leverage several features of AWS IoT such as the Rules Engine and Thing Shadows to quickly and easily build a real connected product. This session will take a practical approach to developing real-world IoT and mobile applications in which the back end is serverless and can scale from one to virtually unlimited users without any infrastructure or servers to manage.

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Cloud & Big Data

ToroDB: NoSQL & relational Java database with SQL analytics

ToroDB: NoSQL & relational Java database with SQL analytics

alvaro ToroDB: NoSQL & relational Java database with SQL analytics

Álvaro Hernandez is a 36 year-old IT entrepreneur, based in Madrid, Spain. Founder and CTO at 8Kdata, a database R&D company, he spends most of his time working on the ToroDB project, the first NoSQL-on-SQL database, a MongoDB-compatible database that runs on top of PostgreSQL. He is a passionate software developer and open source advocate. Álvaro is a Java software developer, member of JavaSpecialists.eu, but also a DBA, trainer and frequent lecturer at international conferences. He also founded the PostgreSQL Spanish User Group, one of the largest PUGs in the world, with more than 500 members.

How do you cope with the rise of unstructured data? Do you have different systems for your NoSQL and your SQL databases? How do you perform analytics of NoSQL data? ToroDB is an open-source NoSQL & relational database written in Java. ToroDB transforms NoSQL documents to relational structures and stores them in relational databases like PostgreSQL. ToroDB speaks the MongoDB protocol, being compatible with MongoDB programs and tools. With ToroDB, you can use either SQL or the MongoDB API for queries. ToroDB automatically structures and partitions your NoSQL data. ToroDB also speaks the MongoDB protocol and can replicate live from it. And you can do analytics in pure SQL against Massively Parallel Databases like Greenplum or CitusDB. Join this talk to understand how ToroDB works, what advantages it may bring to your Big Data architecture, and how to hack ToroDB’s Java open source code.

 

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Cloud & Big Data

Distributed Data Processing with Infinispan and Java Streams

Distributed Data Processing with Infinispan and Java Streams

zamareno Distributed Data Processing with Infinispan and Java Streams

Galder Zamarreño is a core R&D engineer at JBoss, a division of Red Hat. He is one of the founding engineers of Infinispan, Red Hat’s distributed, in-memory key-value store and he currently spends most of his time developing Infinispan’s Functional Map API as well as other data grid and caching functionality. He is very keen on functional programming and has been developing in Scala since 2009. Galder has previously worked with JBoss customers helping them build highly distributed and massively scalable Application Server clusters based on technologies such as JGroups and JBoss Cache. Prior to joining Red Hat, Galder worked in the Retail industry where he was a software developer involved in the development of an EFT software switch solution based on JBoss technologies. The love for distributed systems and open source software comes from his days at ESIDE faculty at University of Deusto (Bilbao, Spain) where he studied a master’s degree in Computer Science.

Infinispan is a distributed in-memory key/value data store capable accelerating data processing using Hadoop, Spark and home-grown Map/Reduce APIs. Starting with Infinispan 8, you can now also use the Java 8 Stream API to process, transform and analyse the data stored in the grid, without burdening the architecture with external platforms. Processing can be applied to keys and/or values and it uses Infinispan’s data partitioning logic to distribute operations to nodes where data lives so that they can be executed locally. In this talk you’ll learn about this new extension to Java 8’s Stream class to process data in Infinispan and how it compares with existing APIs.