EIA 2015 Why future Unicorns will be powered by Bluemix
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Dan O'Riordan – Cloud Technical Leader, EcoD, Europe, IBM France
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EIA 2015 Why future Unicorns will be powered by Bluemix
- 1. #EIA2015 IBM Bluemix, your life saver @danoriordan © 2014 IBM Corporation Dan O’Riordan Cloud Technical Lead EcoD Europe
- 2. Who I am? (Yeah.. Dream on...) 2
- 3. Introduction • Who I am? • IBM Bluemix (What it is and what it isn’t) • Demo • Quickstart #EIA2015 Architecture • IBM Mentor Team 3
- 4. IBM Bluemix • IaaS, PaaS, SaaS • What it is PaaS API Economy Built on SoftLayer – IaaS Platform • What it isn’t Magic Code Generator 4
- 5. 5
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- 8. 8
- 9. Introduction • Who I am? • IBM Bluemix (What it is and what it isn’t) • Demo • Quickstart #EIA2015 Architecture • IBM Mentor Team 9
- 11. Introduction • Who I am? • IBM Bluemix (What it is and what it isn’t) • Demo • Quickstart #EIA2015 Architecture • IBM Mentor Team 11
- 12. Quickstart #EIA2015 Architecture 12 • Developers – As rare as… • Mobile • iOS • Android • Windows • Ionic • IoT – NodeRed • MEAN • MongoLab (Cloudant) • Express • AngularJS • Node.js • NoSQL • DBaaS – Cloudant
- 13. Java is Dead ! 13
- 14. Introduction • Who I am? • IBM Bluemix (What it is and what it isn’t) • IoT Demo • Quickstart #EIA2015 Architecture • IBM Mentor Team 14
- 16. How to win a T-Shirt ? Register on IBM Bluemix and be one of the first 300! https://ibm.biz/BluemixEurope
- 18. How to win a Smartphone Mini Cube Speaker? Build your application on IBM Bluemix and be one of the best! 3 will be selected on July 17th
- 20. How to win a GoPro Hero? Build your application on IBM Bluemix and be the best! Winner will be selected on July 24th
- 22. How to win a Full Bluemix access for 1 year? Build your application on Bluemix and impress IBM with its potential!
- 23. Nitesh Analytics, Big Data Dan Mobile, IoT, NodeRed Clemence Mobile, IoT Xavier Analytics, Smarter City Nicolas Smarter City Sophie Ergonomist Emmanuel Analytics, Big Data Marc Arthur Bluemix SME Karim Bluemix SME Jeffrey IBM Watson Aroopratan IBM Watson Mario Bluemix SME Salil IBM Watson Maksym Bluemix SME Ondrej Bluemix SME Tejas IBM Watson Soheel IBM Watson
- 24. Nitesh Analytics, Big Data Dan Mobile, IoT, NodeRed Clemence Mobile, IoT Xavier Analytics, Smarter City Nicolas Smarter City Sophie Ergonomist Emmanuel Analytics, Big Data Marc Arthur Bluemix SME Karim Bluemix SME Jeffrey IBM Watson Aroopratan IBM Watson Mario Bluemix SME Salil IBM Watson Maksym Bluemix SME Ondrej Bluemix SME Tejas IBM Watson Soheel IBM Watson
- 25. Backup 25
- 26. 26 JDBCAPNS/GCMREST API MQTT What Did We Just See ? WEB REST
- 27. The Connected Patient 27 Patient wears portable Bluetooth ECG Monitor Android Phone acts as communicator Pan/Thompkins QRS Detection Algorithm Other Algos to detect possible problem Trigger sends 1 Hour of ECG Raw data Patient can also activate trigger
- 28. Wiring the Internet of Things 28 Low-cost Hardware Phone connection via MAC address Dataflow defined in JSON Real-time data analysis Node-RED Event Processing Engine Simplifies IoT Wiring Built on Node.js
- 29. Cloudant Data Delivery Database as a service (DBaaS) NoSQL Global Data Distribution Mobile Replication Monitoring Scalable Performance Low Latency Data Management free 29
- 30. Cloudant Data Delivery RAW ECG Data Recorded Time Node-RED directs the data to Cloudant Supports off-line device access Synchronization 30
- 31. Cloudant Data Delivery JSON format HrMean GPS Location 31
- 32. Flowing into Hadoop for Storage & Analytics 32 Distributed framework for storage and large scale processing of vast data sets Parallel processing of thousand’s of patient records IBM Big Insights provides Enterprise ready Hadoop services and tools ECG data pushed from Cloudant to HDFS
- 33. SPSS Modeler Data Mining and Text Analytics Build Predictive Analytics visually Connecting over JDBC to Big Insights on Bluemix Data extracted Execute Algorithms in R HRV (Heart Rate Variability) 33
- 34. Plot ECG Data onto a graph Specialists can annotate charts Abnormalities highlighted Potential Critical Heart conditions can be averted 34 Plot ECG Data
- 35. 35 Notification pushed to mobile device IBM Push for Bluemix service Push Notification
- 36. Thank You Dan O’Riordan - oriordan@fr.ibm.com
Editor's Notes
- 0-5 mins: Intro and first, Slides 1-5 (Paul) 5-15 mins: medtel24, Slides 6-9 (Lee) 15-25 mins: Demo video (Introduced and narrated by Dan). DO NOT talk about the tech parts too much as that is all covered in the next slides 25-35 mins: Technical breakdown pt 1, Slides 10-16 (Dan) 35-45 mins: Technical breakdown pt 2, Slides 17-22 (Paul) 45-50 mins: medtel24 summary. Slide 23 (Lee) 50-55 mins: Closing summary, Slides 24-30 (medtel24 for benefits to them and/Paul) 55-60 mins: Q&A (all) Introduce Myself, Dan and Lee Today we are going to speak about three things … the internet of things, Platform as a Service and Healthcare.
- So what did we see? …. And how did we put it together? Apple Push Notification Service (APNS) or Google Cloud Messaging (GCM) MQTT (formerly Message Queue Telemetry Transport) MQTT is a Client Server publish/subscribe messaging transport protocol. It is light weight, open, simple, and designed so as to be easy to implement. These characteristics make it ideal for use in many situations, including constrained environments such as for communication in Machine to Machine (M2M) and Internet of Things (IoT) contexts where a small code footprint is required and/or network bandwidth is at a premium. The protocol runs over TCP/IP, or over other network protocols that provide ordered, lossless, bi-directional connections.
- So what did we see? …. And how did we put it together? Apple Push Notification Service (APNS) or Google Cloud Messaging (GCM) MQTT (formerly Message Queue Telemetry Transport) MQTT is a Client Server publish/subscribe messaging transport protocol. It is light weight, open, simple, and designed so as to be easy to implement. These characteristics make it ideal for use in many situations, including constrained environments such as for communication in Machine to Machine (M2M) and Internet of Things (IoT) contexts where a small code footprint is required and/or network bandwidth is at a premium. The protocol runs over TCP/IP, or over other network protocols that provide ordered, lossless, bi-directional connections.
- Architecture diagram One slide for each part (mobile, cloudant, hadoop, SPSS) Android Application Cloudant as the data bucket Hadoop cleaning and preparing the data SPSS to do the predictive modeling Mobile Services (Push, Security)
- Node-red is a visual tool for wiring the Internet of Things. With it you can hardwire devices, APIs and Online Services in new and interesting ways. Node-RED provides a browser-based flow editor that makes it easy to wire together flows using the wide range nodes in the palette. Flows can be then deployed to the runtime in a single-click. JavaScript functions can be created within the editor using the rich capabilities of the embedded Eclipse Orion. A built-in library allows you to save useful functions, templates or flows for re-use. Just as a spreadsheet lets you to play around with numbers, Node-RED is a tool that's good for playing around with events. "People who aren't programmers can start thinking 'I've got Twitter here and I want to analyse what's being said and publish it into a document over here, how can I do that?'. For instance you could have a Twitter feed coming in, do a bit of sentiment analysis on the tweets and send all the good ones to an email address. The light-weight runtime is built on Node.js, taking full advantage of its event-driven, non-blocking model. This makes it ideal to run at the edge of the network on low-cost hardware such as the Raspberry Pi as well as in the cloud. With over 60 thousand modules in Node's package repository, it is easy to extend the range of palette nodes to add new capabilities.
- Cloudant provides a Highly scalable NoSQL Database as a Service facilty. Cloudant is able to distribute application data across a global network of data centers while providing non-stop data access with low latency for its customers. It has 23,000 users operating it with high velocity, web, mobile, IoT applications ending the drudgery & risk of scale-it- yourself . Cloudant provides global data distribution, mobile replication and synchronization (application developers build their back ends on the Cloudant Data Layer cloud database), monitoring and scalable performance. It serves government agencies, enterprises, and SMBs. It accelerates time-to-market and time-to-innovation because it frees developers from the mechanics of data management so they can focus exclusively on creating great applications. Any device using HTTP(s) and JSON can sync with Cloudant. It works with self-describing JSON documents through a RESTful API that makes every document in your Cloudant database accessible as JSON via a URL. Documents can be retrieved, stored, or deleted individually or in bulk and can also have files attached. The provisioning, management, and scalability of the data store is taken care of by IBM, freeing up your time to focus on your application.
- For many people, big data is synonymous with Hadoop. Certainly, the ability to store and processing vast amounts of data on commodity hardware has fueled a new generation of applications. It provides the landing zone for collecting data, structured or unstructured, for integration, cleansing and analysis
- IBM® SPSS® Modeler is a powerful data mining and text analytics workbench that helps you build accurate predictive models quickly and intuitively without the need for programming. It enables the creation of predictive models that organizations can use proactively and repeatedly to reduce costs and increase productivity. Data wrangling is a new term that has been coined to convey the challenges with sifting through the morass of big data to glean insights. IBM SPSS Modeler provides the advanced and predictive capabilities needed to assess data stored not only in Hadoop but also in RDBMS and files. The SPSS Modeler models can also be imported into InfoSphere Streams, providing a single interface for time-pressed data scientists to define their analytical models for both streaming data and data at rest. To accelerate the analytic process, SPSS Analytic Catalyst automates portions of data preparation, automatically interpreting results and presenting analyses in interactive visuals with plain language summaries. This product is aimed at those that understand how to interpret statistical results but lack the time or skills to define the analytic models. When the data contains large amounts of unstructured text, IBM Content Analytics is used to automate the text analytics to rapidly classify text and provide industry-specific metrics.
- Redo to make clearer esp plot