This is an IBM sponsored Big Data meetup group. Geared towards developers, data scientists and ALL Big Data enthusiasts, our meetups provide an opportunity to work hands on with the solutions and tools in our Big Data portfolio. Our Meetups typically include a 45-60 min (max) presentation that serves as an introduction and overview for a specific Big Data technology. It is followed by ~3 hours to collaborate with fellow developers and apply your Big Data skills.� We provide a cloud environment that you can run through the browser of your laptop at NO cost to you. Our meetups are FREE.
Meetup topics include:
- Hadoop-based analytics - Stream Computing - Text Analytics - Visualization and Discovery tools for Big Data - Big Data App Development - Deep dives into the technologies that makes big data processing possible - Anything and everything about Big Data
Join us today for a hands on software development experience.
All information about our meetups (starting with our last meetup on "kubernets @IBM Cloud - Code Camp") is public accessable:
Building AI solutions end to end - from setting up a Data Lake, building Machine Learning models and their deployment
Data analysis, combining internal and external data sources and creation/deployment of machine learning models are challenges for companies that want to become data-driven. Data has to be easy accessible and analysed in self-service but governance and control is still needed. Data may be in your own data center and is not allowed to leave it, but has to be combined with data stored on public clouds. After building a model it is necessary to control its accuracy, monitor its decision behavior, and rebuild it if necessary. We will explain and demonstrate how IBM Solutions for Data & AI can help you coping with these challenges.
Developers are moving away from large monolithic apps in favor of small, focused microservices that speed up implementation and improve resiliency. Microservices and containers changed application design and deployment patterns, but along with them brought challenges like service discovery, routing, failure handling, security and visibility to microservices.
"Service mesh" architecture was born to handle these features. Applications are getting decoupled internally as microservices, and the responsibility of maintaining coupling between these microservices is passed to the service mesh. Istio, a joint collaboration between IBM, Google and Lyft provides an easy way to create a service mesh that will manage many of these complex tasks automatically, without the need to modify the microservices themselves.
In this meet-up, you will learn and see how Istio can be used to manage traffic of microservice based applications. We will learn why kubernetes need “service mesh” and how does Istio improve network traffic management.