With the new year in full swing, adult video company Pornhub has taken a look back at the trends and insights of the previous year. It recently published its annual yearly review online, and we could say, it’s quite interesting.
To start off, the company welcomed 23 billion sessions in the past twelve months, which registered nearly 92 billion video views. This is equal to 64 million visitors a day, watching 4.6 billion hours of porn in just a year. The United States is still the biggest visitor of the adult website, followed by the United Kingdom, Canada, India, Japan, and France, among many others.
Pornhub acknowledges the gradual shift of today’s technology to mobile browsing, and with this in consideration, they found that 61% of their visitors stream content from their smartphones, an increase from 2015’s 53%. Meanwhile, desktop usage is still covering a significant chunk at 28%. Tablets come third, registering only 11% of Pornhub’s trafffic.
Moving to operating system usage, Pornhub found that Windows visitors dominate the desktop, garnering 80% share. While this is indeed a controlling chunk of the pie, it is noted that macOS and Linux users are on the rise, with 8% and 14% rise in usage, respectively. With mobile OSes, Android and iOS are almost at par with each other, with the former recording 50%, and the latter at 47%. Windows users are still hanging with 3% share.
When it comes to web browsers used to access Pornhub, 51% of desktop users prefer Google Chrome. Surprisingly enough, Internet Explorer is second best, recording a small yet still significant 14%. Mozilla Firefox and Safari, on the other hand, are on third and fourth place, respectively. Microsoft’s newest browser, Edge, while it may come in 5th place, registered an 845% rise in usage. Pornhub attributes this to migrations from the Internet Explorer browser, which dropped 21%.
It doesn’t end on desktop computers and smartphones, however; Pornhub reports that more and more people are choosing to view adult content on gaming consoles. PlayStations are the most popular among the crowd, with 53%, up from 2015’s 46%. Xbox comes in quite close in second, recording 34% share. The Nintendo Wii, Nintendo 3DS and Sony PS Vita also make the top five, though their shares are less significant than the two leaders.
Lastly, with Pornhub taking advantage of virtual reality technology, the website registered over 300% increase in views. It also found that Asian countries like China, Thailand, Hong Kong, and the Philippines are leading when it comes to watching such videos.
You can check out a more in-depth report on Pornhub’s 2016 statistics here , covering statistics per country, most popular categories, and more.
Source: Pornhub via The Next Web

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A number of PC manufacturers made some interesting announcements this week at CES 2017, but as far as the gaming market goes, Razer takes the cake. The company announced Project Valerie , which it claims to be the world’s first triple-display laptop.
Those three displays are 17.3-inches each, and they all have a 4K resolution, coming to a total of 11,520 x 2,160px. That’s almost 25 million pixels, and it’s all powered by an Nvidia GeForce GTX 1080 GPU.
I hunted down the Razer booth at CES this week to see this beast in person. It was covered in a glass case, so I couldn’t actually touch it, but it was beautiful.
The company confirmed to me that the model inside was a prototype, and the displays roll out of it. Ultimately, the final product will have them automatically expand and retract, by simply pressing the button.
In the video below, you’ll see Project Valerie, but I also did a quick tour of the Razer booth, where there are all kinds of gaming setups, and it includes Project Ariana .
Neowin is at CES to bring you all the coverage from the show floor, click here for other articles.

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Migrating an existing system towards microservices is very different from building a new system, Joris Kuipers , claims in a presentation describing an ongoing process of refactoring a large monolithic application towards a more distributed or microservices-based architecture.
Kuipers, architect at Trifork Amsterdam , describes the application as an electronic patient record system for health care, created six years ago, that for the first two years was a single monolithic application with a few business-to-business (B2B) integrations. From the very beginning it has been based on Command Query Responsibility Segregation (CQRS) using Axon , an open source framework developed by Trifork. It worked very well but as the system and number of customers grow, new requirements came along, including a requirement for insurance expensing that had to be a separate application but still requiring data from the current application. This was a significant change since they now had to move towards multiple applications that is sharing state.
Today the core application is still relatively large, surrounded by three separate applications for insurance expensing, together with almost 40 third-party integrations implemented in a dozen of deployable applications. It hosts about 65 tenants and 12,000 users.
A lot of the integrations have a much shorter lifecycle than the core application, so their major reason for moving to microservices was the need to scale their development to be able to adapt to these different lifecycles. Scaling the development teams and scaling the pace of development was the real drivers for the move.
Since they had an application based on CQRS and events when starting with the refactoring, they decided to use events as a point of integration and broadcast all events through a message broker to other interested applications. They extracted all the existing B2B integration-related code into separate applications and connected them to the broker to get all emitted events. For extracted applications with a need to communicate back to the core application, they are using the CQRS commands already present in the core.
A typical example of the flow of data is when a user is using the core application making a change to some data. This change will result in events published which the integration applications are reading asynchronously, and based on the logic this may trigger a notification sent to an external partner. Kuipers sees this as a hub and spoke architecture with their core application being the hub, surrounded by several smaller applications. He notes that this type of decomposing, by consumers, is a way of moving towards microservices that fits them very well.
For Kuipers, events are a huge help in splitting up a system because they are asynchronous by nature, describes something that has already happened, and is something that other systems can listen for and react to. He notes that using events also introduces some challenges, especially important to think about when events becomes the backbone for integration:
In conclusion, Kuipers notes that they are now able to quickly develop and deploy new integrations in isolation from the core application, which also means a reduced risk since the core systems can be left untouched, all of which Kuipers claims have given them an important and competitive advantage.

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Amazon’s Simple Queue Service (SQS) recently gained FIFO (first-in, first-out) queues, which are designed to «guarantee that messages are processed exactly once, in the order that they are sent, and without duplicates». AWS rolled out this new queue type in the US East (Ohio) and US West (Oregon) regions and «plans to make it available in many others in early 2017».
Amazon SQS is described as a «fast, reliable, scalable, fully managed message queuing service [designed to] decouple the components of a cloud application [and] transmit any volume of data, without losing messages or requiring other services to be always available».
Accordingly, a notable characteristic of the service has been the de facto absence of scaling limits for the now called ‘standard’ queues, insofar users can create an unlimited number of queues, and each queue provides «nearly unlimited throughput» by default. However, this effortless scaling mode requires a message processing architecture that can only guarantee best-effort ordering and at-least-once delivery.
These standard SQS queues are now complemented by a new FIFO queue type, which trades unlimited scaling for stronger message ordering and processing guarantees, based on AWS’ observation that «customers have told us that FIFO applications are generally lower-throughput – 10 messages per second or lower»:
The underlying architectural tradeoffs and resulting constraints are described in more detail in a technical blog post on how the Amazon SQS FIFO API works. The authors emphasize, that while «many apps perform well with SQS’s traditional super-scalable at-least-once message processing», there are some use cases that require ordering or exactly-once processing, such as «a stream of price updates» or «commands in an interactive shell session».
The default settings for FIFO queues should be appropriate to achieve strict ordering and exactly-once processing for most use cases «if your network connections don’t drop for minutes at a time, and your messages have unique identifiers». For more granular requirements, it is possible to facilitate message groups (each message that belongs to the same group is processed in order) and a dedicated deduplication ID (which otherwise defaults to the SHA256 hash of the message content).
Microsoft Azure’s Service Bus also optionally guarantees FIFO message ordering and exactly-once delivery. In contrast, Google Cloud Platform’s Cloud Pub/Sub service neither supports FIFO message ordering nor exactly-once delivery, since Google argues that «there are very few use cases that actually require strict ordering».
The Amazon SQS documentation features a developer guide , including a dedicated section on FIFO queues that also provides a checklist for moving from a standard queue, as well as the API reference. A separate FAQ is also available. SQS is priced per API request (rather than per message: one request can contain up to ten messages) and the new FIFO queues are priced similarly to how standard queues have been priced before, while the pricing for standard queues has been reduced by twenty percent. Support is provided via the Amazon SQS forum.

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