According to the Survey Reports, there are almost 1.84 million apps available on iOS and on Google Play there are 2.9 million apps. However, the usage of mobile applications is increasing constantly. Due to the high demand for Android and iOS applications, it leads mobile app development services to high competition.

In the digital world, mobile app developers don’t only have to focus on the backend and frontend coding process and functionalities. Apart from this, to launch successful apps, they have to be creative and require knowledge about market trends and guidelines.

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It’s always interesting to find companies focused on innovating the underlying infrastructural layers that makes amazing things happen in IoT. One of these is Helium, which was co-founded by Shawn Fanning (Napster co-creator) and Amir Haleem in 2013, with a mission to make it easier to build decentralized wireless networks.

They’ve created what they call "The People’s network, the world’s first sharing-economy wireless network to simplify connecting anything to the internet by rewarding anyone to become a network operator. There are now over 2700 Hotspots in over 745 U.S. cities across every state with the exception of West Virginia (even Puerto Rico is online). 

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When I think of use cases where IoT will really come into its own in future decades, data monetization remains one of my favorite examples of where sensor creates new marketplaces, insights, and industries as a new data economy emerges. 

But where I get really excited is when I see a use case that neatly combines several of the most explosive trends of the future. German founded company UZE Mobility and has done just this, combining mobility, digital out of home advertising, IoT, and data monetization.

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In this article, I will share coding examples some of the key aspects of TumblingWindow in Flink. Those not familiar with Flink streaming can get an introduction here. 

Before we get into TumblingWindow, let us get a basic understanding of  "Window" when it comes to stream processing or streaming computation.  In a data stream you have a source that is continuously producing data, making it unfeasible to compute a final value.  

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In WSO2, we can implement the Splitter and Aggregator EIP using the Iterate and Aggregate mediators. With the Splitter pattern, we can split a message composed by different elements that need to be processed individually, and then we use the Aggregator pattern to aggregate the results of each individual call and then perform some processing over the aggregated results.

Happy Path Example

In a happy path example, all the requests and processing done inside the iterate mediator will occur with no failures, and the aggregate mediator will handle the results of all the requests made. We can see that in the proxy below:

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What’s this “Producer/Consumer” thing? It’s around us, everywhere. Every time you see some kind of workflow with multiple serial steps, that’s an example. A production line in a car factory, a fast-food kitchen, even the postal service.

So why do we care about it? Well, that’s easy: in almost every piece of software we write, there’s a pipeline to fulfill. And as every pipeline, once a step is completed the output is redirected to the next one in line, freeing up space for another execution.

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What the Game of Thrones Night’s Watch Can Teach Us About DevOps Security

If you are reading this, you probably got sucked into watching Game of Thrones when it first aired on HBO in 2011. It is amazing how much has changed during the eight seasons of the series, but, as a developer and security guy, I find the Night’s Watch story the most interesting. The series debuts with the men in black – a.k.a the Night’s Watch – patrolling the wall. Soon, we learn that, contrary to popular belief, there really are supernatural threats lurking in the darkness that put all of Westeros at risk.

The Wall that the Night’s Watch guard is the only thing standing between the country of Westeros and the deadly White Walkers. However, rather than immediately getting all the resources they need to tackle this danger, the people of the Night’s Watch spend the next seven seasons convincing the rest of Westeros that these threats are real and that leaving the Wall woefully understaffed and poorly defended endangers everyone. Hmm…sounds familiar?

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Couchbase N1QL is a SQL-like language for JSON data. To retrieve and manipulate JSON data effectively, we need appropriate indexes. The rules for creating these indexes can be read here. But that involves too much reading, hence we now have an Index Advisor service that accepts a query and gives out an index recommendation that would meet the expectations of the Couchbase query engine — all without downloading the latest Couchbase server.

This service will provide index recommendations to help DBAs, developers, and architects optimize query performance and meet the SLAs.

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This week, we check out a recent API vulnerability in Twitter. In addition, it looks like API vulnerabilities are a bit of a theme in apps by political parties: vulnerabilities were discovered in apps by Israel’s Likud and the Democratic Party in the USA. We also have two API security talks: one recorded and one upcoming webinar.

Vulnerability: Twitter

Twitter has disclosed a recent API exploit. The API endpoints to make finding friends in Twitter by their phone numbers easier were abused, possibly by state-sponsored actors, to mine accounts by mapping them to phone numbers. Detecting and throttling the exploit was hard because the phone numbers were not sequential and attackers used multiple accounts and IP addresses in their attacks.

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DDoS (Distributed Denial Of Service)

A Distributed Denial-of-Service (DDoS) is any type of attack where the attackers attempt to prevent legitimate users from accessing the service. In a DDoS attack, the attacker usually sends excessive messages asking the network or server to authenticate requests that have invalid return addresses.

How to Prevent DDoS Attacks

There are different ways we can prevent DDoS attacks; we can do IP blacklisting to avoid traffic from sources of attack, rate limit your application to prevent it from being overwhelmed, or use both of them to provide multiple layers of security.

Source de l’article sur DZONE