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The Physalia configuration store for chain replication of EBS is implemented as key-value stores maintained over a large number of these cells. They built a test harness, called SimWorld, which abstracts networking, performance, and other systems concepts. The goal of this approach is to allow developers to write distributed systems tests, including tests that simulate packet loss, server failures, corruption, and other failure cases, as unit tests in the same language as the system itself.

Almost all of the billions of devices connected to the internet have onboard clocks, which need to be accurate to properly perform their functions. Many clocks contain inaccurate internal oscillators, which can cause seconds of inaccuracy per day and need to be periodically corrected. Incorrect time can lead to issues, such as missing an important reminder or failing a spacecraft launch. Devices all over the world rely on Network Time Protocol (NTP) to stay synchronized to a more accurate clock over packet-switched, variable-latency data networks.

NASA needs 215 more petabytes of storage by the year 2025, and expects Amazon Web Services to provide the bulk of that capacity. However, the space agency didn’t realize this would cost it plenty in cloud egress charges. As in, it will have to pay as scientists download its data. That omission alone has left NASA’s cloud strategy pointing at the ground rather than at the heavens. The data in question will come from NASA’s Earth Science Data and Information System (ESDIS) program, which collects information from the many missions that observe our planet.

Hi! I’m one of Embox RTOS developers, and in this article I’ll tell you about one of the typical problems in the world of embedded systems and how we were solving it. Control and responsibility is a key point for a wide range of embedded systems. On the one hand, sensors and detectors must notify some other devices that some event occurred, on the other hand, other systems should react as soon as possible.

The company is expanding its US network in a big way, and it’s turned to two edge data center startups for help. In January, Cloudflare, which helps companies make their web services run faster and be more secure – and which more recently started to use its global data center network to also provide cloud computing services – said it would expand the network in the US with three dozen new locations.

Samsung Electronics is planning to gradually lower its dependence on AWS (Amazon Web Service) and is looking to use its own cloud system because it believes that it is better for it to lower its dependency. Source: etnews.com

There may be an undiscovered tribe deep in some jungle somewhere that hasn’t made up their mind on microservices, but I doubt it. People love microservices or love to hate microservices. There’s not much in between. So it means something when even a team at a company like Uber announces a change away from microservices to something else. What? Macroservices. But we’ll get to that. Think what you want about Uber the company, but from a software perspective Uber has been a good citizen.

Last month, the Kubernetes team released Kubernetes 1.18, which extended Ingress. The two most exciting features include a new IngressClass resource and the new pathType field. To minimize the risk for our users who want to try out these exciting new features, the Ambassador Edge Stack supports the latest version of the Kubernetes Ingress specifications. As a team, we believe strongly in continually supporting evolving standards such as Kubernetes ingress, which we adopted and announced our initial support back in September 2019.

In this post, we’re going to take a deeper dive into the Postgres and PostGIS internals to find out how this actually works. By the time we surface you will have a better understanding of the advanced technical capabilities and unparalleled extensibility of Postgres. You’ll also appreciate how the open philosophy of Postgres has fostered a development community whose collaboration over many years has provided powerful features that benefit numerous users.

Executing a full rewrite of the Dropbox sync engine was pretty daunting. (Read more about our goals and how we made the decision in our previous post here.) Doing so meant taking the engine that powers Dropbox on hundreds of millions of user’s machines and swapping it out mid-flight. To pull this off, we knew we would need a serious investment in automated testing. Our testing strategy gave us confidence that we were on the right track throughout the rewrite, and today it allows us to continue building and shipping new features on a quick release cycle.