A hitchhiker's guide to cloud native API gateways
March 4, 2020
Mario-Leander Reimer guides you through cloud native API gateways. Good APIs are the centerpiece of any successful digital product, with proper management of the utmost importance. The API gateway pattern is well established to handle concerns like routing, versioning, rate limiting, access control, or diagnosability in a microservice architecture.
AGL-based Container Technology Applied to Mass Production of RSE (Rear Seat Entertainment) - Guktae Kim &
March 2, 2020
Rear Seat Entertainment (RSE) has been widely used on the Android platform to take advantage of a variety of games and media programs. DrimAES Inc. wanted to find a way to utilize the pre-built Androi …
Building a data ecosystem at Sweden's Television: Lessons and pitfalls
February 29, 2020
Sweden's Television manages online products that range from providing news to TV series and are used by millions of people. To make sure that it creates content that engages, entertains, and educates, it started its own platform for collecting and analyzing user data. Ismail Elouafiq highlights the architectural choices the company made and the lessons it learned in building its data ecosystem.
Using Open Source Software to Build an Industrial-grade Embedded Linux Platform from Scratch
February 29, 2020
Building an embedded Linux platform is like a puzzle; placing the suitable software components in the right positions will constitute an optimal platform. However, selecting suitable components is dif …
Knative: A Kubernetes framework to manage serverless workloads
February 27, 2020
Knative is a Kubernetes-based platform to build, deploy, and manage modern serverless workloads. It provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere. Join Nikhil Barthwal to explore using Knative to build and deploy modern serverless workloads in a vendor neutral fashion.
A novel solution for a data augmentation and bias problem in NLP using TensorFlow
February 24, 2020
Join KC Tung to discover a way to use TensorFlow to solve a natural language processing (NLP) model bias problem with data augmentation for an enterprise customer (one of the largest airlines in the world). KC leveraged hidden gems in tf.data and the new API to easily find a novel use for text generation and found it surprisingly improved his NLP model.
Make Alexa and Siri speak with each other: Toward a universal grammar in AI
February 18, 2020
More than 50% of all interactions between humans and machines are expected to be speech-based by 2022. The challenge: Every AI interprets human language slightly different. Tobias Martens details current issues in NLP interoperability and uses Chomsky's theory of universal hard-wired grammar to outline a framework to make the human voice in AI universal, accountable, and computable.
ROCm and Hopsworks for end-to-end deep learning pipelines
February 18, 2020
The Radeon open ecosystem (ROCm) is an open source software foundation for GPU computing on Linux. ROCm supports TensorFlow and PyTorch using MIOpen, a library of highly optimized GPU routines for deep learning. Jim Dowling and Ajit Mathews outline how the open source Hopsworks framework enables the construction of horizontally scalable end-to-end machine learning pipelines on ROCm-enabled GPUs.
Now you see me; now you compute: Building event-driven architectures with Apache Kafka
February 11, 2020
Would you cross the street with traffic information that's a minute old? Certainly not. Modern businesses have the same needs. Michael Noll explores why and how you can use Kafka and its growing ecosystem to build elastic event-driven architectures. Specifically, you look at Kafka as the storage layer, at Kafka Connect for data integration, and at Kafka Streams and KSQL as the compute layer.
The evolution of metadata: LinkedIns story
February 9, 2020
Imagine scaling metadata to an organization of 10,000 employees, 1M+ data assets, and an AI-enabled company that ships code to the site three times a day. Shirshanka Das and Mars Lan dive into LinkedIns metadata journey from a two-person back-office team to a central hub powering data discovery, AI productivity, and automatic data privacy. They reveal metadata strategies and the battle scars.