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We are excited to announce the public availability of HashiCorp Vault 1.2. Vault is a tool to provide secrets management, data encryption, and identity management for any infrastructure and application. Vault 1.2 is focused on supporting new architectures for automated credential and cryptographic key management at a global, highly-distributed scale. This release introduces new mechanisms for users and applications to manage sensitive data such as cryptographic keys and database accounts, and exposes new interfaces that improve Vault’s ability to automate secrets management, encryption as a service, and privileged access management.

Uber Poet, an open source mock application generator, helped us determine if refactoring the application part of our code into a few large modules would make our overall Swift build times faster. Given the scope and scale of Uber’s business, our Swift applications are some of the largest in the world. Each application possesses 500,000 to 1 million lines of shipping Swift and Objective-C code and about three times more lines of code in the form of tests and auto-generated mocks.

Creating accurate maps today is a painstaking, time-consuming manual process, even with access to satellite imagery and mapping software. Many regions — particularly in the developing world — remain largely unmapped. To help close this gap, Facebook AI researchers and engineers have developed a new method that uses deep learning and weakly supervised training to predict road networks from commercially available high-resolution satellite imagery. The resulting model sets a new bar for the state of the art for accuracy, and because it is able to accommodate regional differences in road networks, it can effectively predict roads around the globe.

Since iOS 7, Dynamic Type has allowed users to choose a prefered font size for their phone. At Airbnb, we try to build an app that our entire community can use — since Dynamic Type is a critical accessibility feature, we knew supporting it would make more people able to effectively use our app, some of them probably for the first time. To validate the importance of this feature, we examined the data and saw as much as 30% of people using our app had a preferred font size that was not the default.

Computer power supplies don’t get much respect. As a tech enthusiast, you probably know what microprocessor is in your computer and how much physical memory it has, but odds are you know nothing about the power supply. Don’t feel bad—even for manufacturers, designing the power supply is an afterthought. That’s a shame, because it took considerable effort to create the power supplies found in personal computers, which represent a huge improvement from the circuits that powered other kinds of consumer electronics up until about the late 1970s.

Recently I came across this excellent post from Cindy Sridharan, which throws a bunch of good ideas about how to improve the troubleshooting experience with microservices. I think that Kiali already has a good approach in that regard, which doesn’t mean there’s no room for improvement. Kiali is meant to be the Istio console. This has been a constant focus of the development team since the beginning of the project.

Late last week, the U.S. House of Representatives passed legislation to mandate federal research on a radically ‘retro’approach to protect power grids from cyber attack: unplugging or otherwise isolating the most criticalequipment from grid operators’ digital control systems. Angus King, an independent senator from Maine whose identical bill passedthe Senate last month, says such a managed retreat from networked controls may berequired to thwart the grid’s most sophisticated online adversaries.

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. Source: infoq.com

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.

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. In this installment, I compare secure control of egress traffic in Istio with alternative solutions such as using Kubernetes network policies and legacy egress proxies and firewalls.