News

The Service Mesh: It’s About Traffic

Oliver Gould talks about the Linkerd project, a service mesh hosted by the Cloud Native Computing Foundation, to give operators control over the traffic between their microservices. He shares the lessons they’ve learned helping dozens of organizations get to production with Linkerd and how they’ve applied these lessons to tackle complexity with Linkerd.

Introducing EvoGrad: A Lightweight Library for Gradient-Based Evolution

Tools that enable fast and flexible experimentation democratize and accelerate machine learning research. Take for example the development of libraries for automatic differentiation, such as Theano, Caffe, TensorFlow, and PyTorch: these libraries have been instrumental in catalyzing machine learning research, enabling gradient descent training without the tedious work of hand-computing derivatives. In these frameworks, it’s simple to experiment by adjusting the size and depth of a neural network, by changing the error function that is to be optimized, and even by inventing new architectural elements, like layers and activation functions–all without having to worry about how to derive the resulting gradient of improvement.

Secure Control of Egress Traffic in Istio, part 3

Welcome to part 3 in our series about secure control of egress traffic in Istio. In the first part in the series, I presented the attacks involving egress traffic and the requirements we collected for a secure control system for egress traffic. In the second part in the series, I presented the Istio way of securing egress traffic and showed how you can prevent the attacks using Istio.

How should pipelines be monitored?

For online serving systems it’s fairly well known that you should look for request rate, errors and duration. What about offline processing pipelines though? For a typical web application, high latency or error rates are the sort of thing you want to wake someone up about as they usually negatively affect the end-user’s experience.

Panel: First Steps with Machine Learning

This panel is a very diverse group, and I’m actually going to let them introduce themselves rather than me trying to butcher any names. This is all about answering my need, literally, my first steps. What should I be focused on as a software engineer wanting to get into ML and start using ML more convinced leadership on things that I want to do?

Remote-controlled Salmon Farms to Operate Off Norway by 2020

Tucked within Norway’s fjord-riddled coast, nearly 3,500 fish pens corral upwards of 400 million salmon and trout. Not only does the country raise and ship more salmonoid overseas than any other in the world (1.1 million tons in 2018), farmed salmon is Norway’s third largest export behind crude petroleum and natural gas. In a global industry expected to quintuple by 2050, farmed salmon is a fine kettle of fish.

Deprecated APIs Removed In Kubernetes 1.16

As the Kubernetes API evolves, APIs are periodically reorganized or upgraded. When APIs evolve, the old API is deprecated and eventually removed. The 1.16 release will deprecate APIs for four services: None of these resources will be removed from Kubernetes or deprecated in any way.

Making Apache Spark Effortless for All of Uber

Apache Spark is a foundational piece of Uber’s Big Data infrastructure that powers many critical aspects of our business. We currently run more than one hundred thousand Spark applications per day, across multiple different compute environments. Spark’s versatility, which allows us to build applications and run them everywhere that we need, makes this scale possible.

Secure your service mesh with Istio and keep an eye on it with Kiali

Amenity Detection and Beyond—New Frontiers of Computer Vision at Airbnb